The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

Principles and methods for transferring polygenic risk scores across global populations

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Clinical consequences of a genetic predisposition toward higher benign prostate-specific antigen levels

BACKGROUND

Prostate-specific antigen (PSA) levels are influenced by genetic variation unrelated to prostate cancer risk. Whether a genetic predisposition to a higher PSA level predisposes to a diagnostic work-up for prostate cancer is not known.

METHODS

Participants were 3110 men of African and European ancestries ages 45-70, without prostate cancer and with a baseline PSA < 4 ng/mL, undergoing routine clinical PSA screening. The exposure was a polygenic score (PGS) comprising 111 single nucleotide polymorphisms associated with PSA level, but not prostate cancer. We tested whether the PGS was associated with a: 1) PSA value > 4 ng/mL, 2) International Classification of Diseases (ICD) code for an elevated PSA, 3) encounter with a urologist, or 4) prostate biopsy. Multivariable Cox proportional hazards models were adjusted for age and genetic principal components. Analyses were stratified by age (45-59 years, and 60-70 years old). Association estimates are per standard deviation change in the PGS.

FINDINGS

The median age was 56.6 years, and 2118 (68%) participants were 45-59 years. The median (IQR) baseline PSA level was 1.0 (0.6-1.7) ng/mL. Among men ages 45-59, the PGS was associated with a PSA > 4 (hazard ratio [HR] = 1.35 [95% CI, 1.17-1.57], p = 4.5 × 10-5), an ICD code for elevated PSA (HR = 1.30 [1.12-1.52], p = 8.0 × 10-4), a urological evaluation (HR = 1.34 [1.14-1.57], p = 4.8 × 10-4), and undergoing a prostate biopsy (HR = 1.35 [1.11-1.64], p = 0.002). Among men ages 60-70, association effect sizes were smaller and not significant.

INTERPRETATION

A predisposition toward higher PSA levels was associated with clinical evaluations of an elevated PSA among men ages 45-59 years.

FUNDING

National Institutes of Health (NIH).

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.

A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects

The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.

Re-envisioning community genetics: community empowerment in preventive genomics

As genomic technologies rapidly develop, polygenic scores (PGS) are entering into a growing conversation on how to improve precision in public health and prevent chronic disease. While the integration of PGS into public health and clinical services raises potential benefits, it also introduces potential harms. In particular, there is a high level of uncertainty about how to incorporate PGS into clinical settings in a manner that is equitable, just, and aligned with the long-term goals of many healthcare systems to support person-centered and value-based care. This paper argues that any conversation about whether and how to design and implement PGS clinical services requires dynamic engagement with local communities, patients, and families. These parties often face the consequences, both positive and negative, of such uncertainties and should therefore drive clinical translation. As a collaborative effort between hospital stakeholders, community partners, and researchers, this paper describes a community-empowered co-design process for addressing uncertainty and making programmatic decisions about the implementation of PGS into clinical services. We provide a framework for others interested in designing clinical programs that are responsive to, and inclusive and respectful of, local communities.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry

BACKGROUND

Genetic factors play an important role in prostate cancer (PCa) susceptibility.

OBJECTIVE

To discover common genetic variants contributing to the risk of PCa in men of African ancestry.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.

RESULTS AND LIMITATIONS

Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).

CONCLUSIONS

This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.

PATIENT SUMMARY

In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

The full spectrum of OCT1 (SLC22A1) mutations bridges transporter biophysics to drug pharmacogenomics

Membrane transporters play a fundamental role in the tissue distribution of endogenous compounds and xenobiotics and are major determinants of efficacy and side effects profiles. Polymorphisms within these drug transporters result in inter-individual variation in drug response, with some patients not responding to the recommended dosage of drug whereas others experience catastrophic side effects. For example, variants within the major hepatic Human organic cation transporter OCT1 (SLC22A1) can change endogenous organic cations and many prescription drug levels. To understand how variants mechanistically impact drug uptake, we systematically study how all known and possible single missense and single amino acid deletion variants impact expression and substrate uptake of OCT1. We find that human variants primarily disrupt function via folding rather than substrate uptake. Our study revealed that the major determinants of folding reside in the first 300 amino acids, including the first 6 transmembrane domains and the extracellular domain (ECD) with a stabilizing and highly conserved stabilizing helical motif making key interactions between the ECD and transmembrane domains. Using the functional data combined with computational approaches, we determine and validate a structure-function model of OCT1s conformational ensemble without experimental structures. Using this model and molecular dynamic simulations of key mutants, we determine biophysical mechanisms for how specific human variants alter transport phenotypes. We identify differences in frequencies of reduced function alleles across populations with East Asians vs European populations having the lowest and highest frequency of reduced function variants, respectively. Mining human population databases reveals that reduced function alleles of OCT1 identified in this study associate significantly with high LDL cholesterol levels. Our general approach broadly applied could transform the landscape of precision medicine by producing a mechanistic basis for understanding the effects of human mutations on disease and drug response.

Genetically adjusted PSA levels for prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

A complex systems model of breast cancer etiology: The Paradigm II Model

BACKGROUND

Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers.

METHODS AND FINDINGS

We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.

CONCLUSIONS

The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

Development and testing of a polygenic risk score for breast cancer aggressiveness

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility to screen for prostate cancer (PCa). We thus conducted a transcriptome-wide association study (TWAS) of PSA levels using genome-wide summary statistics from 95,768 PCa-free men, the MetaXcan framework, and gene prediction models trained in Genotype-Tissue Expression (GTEx) project data. Tissue-specific analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10e-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61e-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses that combined associations across 45 tissues identified 155 genes that were statistically significantly (p < 0.05/22,249 = 2.25e-6) associated with PSA levels. Based on conditional analyses that assessed whether TWAS associations were attributable to a lead GWAS variant, we found 20 novel genes (11 single-tissue, 9 cross-tissue) that were associated with PSA levels in the TWAS. Of these novel genes, five showed evidence of colocalization (colocalization probability > 0.5): EXOSC9, CCNA2, HIST1H2BN, RP11-182L21.6, and RP11-327J17.2. Six of the 20 novel genes are not known to impact PCa risk. These findings yield new hypotheses for genetic factors underlying PSA levels that should be further explored toward improving our understanding of PSA biology.

A Polygenic Risk Score for Prostate Cancer Risk Prediction

This retrospective cohort study compares 2 risk calculator systems that compute the probabilities of finding high-grade or any cancer on biopsy results in men undergoing a first prostate biopsy.

Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies

BACKGROUND

Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored.

METHODS

To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers.

RESULTS

We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer.

CONCLUSIONS

Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

Inflammatory bowel disease induces inflammatory and pre-neoplastic changes in the prostate

BACKGROUND

Inflammatory bowel disease (IBD) has been implicated as a risk factor for prostate cancer, however, the mechanism of how IBD leads to prostate tumorigenesis is not known. Here, we investigated whether chronic intestinal inflammation leads to pro-inflammatory changes associated with tumorigenesis in the prostate.

METHODS

Using clinical samples of men with IBD who underwent prostatectomy, we analyzed whether prostate tumors had differences in lymphocyte infiltrate compared to non-IBD controls. In a mouse model of chemically-induced intestinal inflammation, we investigated whether chronic intestinal inflammation could be transferred to the wild-type mouse prostate. In addition, mouse prostates were evaluated for activation of pro-oncogenic signaling and genomic instability.

RESULTS

A higher proportion of men with IBD had T and B lymphocyte infiltration within prostate tumors. Mice with chronic colitis showed significant increases in prostatic CD45 + leukocyte infiltration and elevation of three pro-inflammatory cytokines-TIMP-1, CCL5, and CXCL1 and activation of AKT and NF-kB signaling pathways. Lastly, mice with chronic colitis had greater prostatic oxidative stress/DNA damage, and prostate epithelial cells had undergone cell cycle arrest.

CONCLUSIONS

These data suggest chronic intestinal inflammation is associated with an inflammatory-rich, pro-tumorigenic prostatic phenotype which may explain how gut inflammation fosters prostate cancer development in men with IBD.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Random field modeling of multi-trait multi-locus association for detecting methylation quantitative trait loci

MOTIVATION

CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.

RESULTS

We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.

AVAILABILITY AND IMPLEMENTATION

https://github.com/chenlyu2656/Multi-MRF.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Abstract 1441: Genetic determinants of PSA levels improve prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer (PCa) remains controversial due to poor sensitivity and specificity that lead to overdiagnosis and overtreatment. The aim of our study is to characterize genetic determinants of PSA levels in cancer-free men in order to personalize PCa screening. We hypothesize that test accuracy may be improved by accounting for PSA variation that is due to genetic factors and does not reflect PCa.

We conducted the largest ever genome-wide association study (GWAS) of PSA in men without PCa (N=95,768; 85,924 predominantly European ancestry) using data from the UK Biobank, BioVU, PLCO, and Kaiser Permanente cohorts. Our GWAS discovered 129 PSA-associated variants (P&lt;5×10-8), 82 of which were novel. A polygenic score (PGSPSA) comprised of these 129 variants was successfully validated in two cancer prevention trials: PCPT (n=5737) and SELECT (n=22,247). PGSPSA explained 7.3% (p=7.0×10-98) of variation in baseline PSA in PCPT and 8.7% (p=7.0×10-476) in SELECT. Importantly, PGSPSA was not associated with PCa status in PCPT (OR=0.98, p=0.71) or SELECT (OR=1.04, p=0.98), which confirms that it reflects benign PSA variation.

Potential clinical utility of PSA genetic adjustment was explored by examining reclassification at thresholds used for biopsy referrals in a real-world setting at Kaiser Permanente. We estimated that correction using PGSPSA would have avoided 21.2% of negative biopsies in non-cases. Reclassification below the biopsy referral threshold was also more common in cases, particularly with low-grade disease with Gleason score &lt;7 (7.3% below vs. 2.6% above). Overall, genetic correction of PSA appeared to improve the accuracy of referral decisions, with a Net Reclassification Index of 0.148.

Next, we evaluated genetically adjusted PSA in the context of detection of aggressive PCa, defined as Gleason score ≥7, PSA ≥10 ng/mL, T3-T4 stage, and/or distant or nodal metastases. Genetically adjusted baseline PSA was more robustly associated with aggressive PCa than observed PSA and yielded a higher area under the curve (AUC) in PCPT (OR=3.03, p=3.5×10-7; AUC: 0.72 vs. 0.68) and SELECT (OR=3.37, p=3.5×10-11; AUC: 0.78 vs. 0.74) when added to a baseline model with age and trial arm. Furthermore, genetically adjusted PSA provides complementary information to PCa risk variants. In PCPT, a logistic regression model that included genetically corrected PSA and the 269-variant PGSPCa achieved a significantly higher AUC than PGSPCa-269 alone for aggressive PCa (AUC: 0.73 vs. 0.65, p=3.3×10-4) and overall PCa (AUC=0.69 vs. 0.66, p=3.3×10-6).

Our work provides evidence that accounting for genetic determinants of PSA has the potential to reduce unnecessary testing and overdiagnosis of low-risk PCa, as well as increase detection of aggressive disease. Larger and more diverse study populations are required to fully characterize the genetic basis of PSA variation and optimize its clinical utility.

Citation Format: Linda Kachuri, Rebecca E. Graff, Sonja I. Berndt, Mitchell Machiela, Neal D. Freedman, Stephen J. Chanock, John P. Shelley, Kerry Schaffer, Jonathan D. Mosley, Phyllis J. Goodman, Cathee Till, Ian Thompson, Robert J. Klein, Stephen K. Van Den Eeden, Thomas J. Hoffmann, John S. Witte. Genetic determinants of PSA levels improve prostate cancer screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1441.

Abstract 1446: Genetic risk factors for the development of multiple primary cancers

Introduction: Individuals with one cancer are at greater risk of new primary cancers than the general population. While several hereditary cancer syndromes are known, genetic risk factors for multiple primary cancers in an individual are not well understood. Identification of susceptibility variants to multiple primary tumors could enhance screening for subsequent cancers among those at highest risk.

Methods: We conducted a pan-cancer genome-wide association study (GWAS) of multiple primary cancers among participants from 2 prospective cohorts: Kaiser Permanente and the UK Biobank. The primary GWAS within cohorts used logistic regression to estimate associations for diagnosis with ≥2 invasive or in situ primary cancers other than non-melanoma skin (N=11,773, 8,928 invasive only) compared to cancer-free controls (N=420,101). Case-case analyses were conducted to distinguish associations with multiple cancers from single-cancer (N=90,576) susceptibility signals. Regression models were adjusted for age, sex, first 10 genetic ancestry principal components, and array. Cohort-specific GWAS results were meta-analyzed. We highlight genome-wide significant (p&lt;5×10-8) results with consistent effect direction across the 2 studies.

Results: We identified 8 variants associated with multiple primary cancers.

Discussion: To our knowledge, rs192703567 has no previous cancer associations. Three identified variants are in known cancer predisposition genes (rs2293607 in TERC, rs6983267 in CASC8, rs35850753 in TP53). Three variants (rs34379047, rs612611, and rs9419958) are previously associated with multiple cancers, 2 (rs2293607 and rs6983267) with cancer pleiotropy, and 2 (rs283732 and rs35850753) with individual cancers. Most variants from the cancer-free control analyses had consistent effects in the single-cancer case-case analyses, suggesting pleiotropic mechanisms. Our preliminary findings offer insight into genetic risk factors associated with developing multiple primary cancers.

Multiple vs. none Multiple invasive vs. none Multiple vs. single Multiple invasive vs. single Chr Position rsID A1 A2 Gene OR P OR P OR P OR P 3 169482335 rs2293607 T C TERC 1.11 1.0×10-9 1.10 2.2×10-7 1.06 2.0×10-3 1.05 0.01 8 128281644 rs283732 C T Intergenic 1.09 2.3×10-7 1.11 9.2×10-9 1.06 3.8×10-4 1.09 3.9×10-5 8 128413305 rs6983267 G T CASC8 POU5F1B CCAT2 PCAT1 1.08 4.1×10-7 1.09 2.9×10-8 1.00 0.83 1.02 0.34 10 105644473 rs34379047 T A OBFC1 1.16 8.5×10-12 1.19 6.0×10-11 1.19 2.3×10-4 1.10 4.0×10-4 10 105675946 rs9419958 T C STN1 1.14 1.8×10-11 1.16 4.5×10-11 1.08 3.1×10-4 1.09 2.8×10-4 11 69307463 rs612611 G A Intergenic 1.11 3.7×10-8 1.10 5.3×10-6 1.06 9.6×10-4 1.05 0.02 17 7578671 rs35850753 T C TP53 1.27 4.9×10-7 1.34 1.6×10-8 1.16 2.8×10-3 1.24 8.8×10-5 22 40738280 rs192703567 C T Intergenic 1.37 5.2×10-8 1.37 1.8×10-6 1.43 4.9×10-9 1.43 2.8×10-7 Chr=Chromosome; A1=Effect allele; A2=Other allele; OR=Odds ratio.

Citation Format: Jovia L. Nierenberg, Linda Kachuri, Taylor B. Cavazos, Rebecca E. Graff, Thomas J. Hoffmann, Jie Zhang, Stacey Alexeeff, Laurel Habel, Douglas Corley, Stephen Van Den Eeden, Elad Ziv, Lori C. Sakoda, John S. Witte. Genetic risk factors for the development of multiple primary cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1446.

Cancer systems epidemiology: Overcoming misconceptions and integrating systems approaches into cancer research

Patricia Mabry and coauthors discuss application of systems approaches in cancer research.

A genome-wide association study of obstructive heart defects among participants in the National Birth Defects Prevention Study

Obstructive heart defects (OHDs) share common structural lesions in arteries and cardiac valves, accounting for ~25% of all congenital heart defects. OHDs are highly heritable, resulting from interplay among maternal exposures, genetic susceptibilities, and epigenetic phenomena. A genome-wide association study was conducted in National Birth Defects Prevention Study participants (N_discovery  = 3978; N_replication  = 2507), investigating the genetic architecture of OHDs using transmission/disequilibrium tests (TDT) in complete case-parental trios (N_{discovery_TDT}  = 440; N_{replication_TDT}  = 275) and case-control analyses separately in infants (N_{discovery_CCI}  = 1635; N_{replication_CCI}  = 990) and mothers (case status defined by infant; N_{discovery_CCM}  = 1703; N_{replication_CCM}  = 1078). In the TDT analysis, the SLC44A2 single nucleotide polymorphism (SNP) rs2360743 was significantly associated with OHD (p_discovery  = 4.08 × 10^-9 ; p_replication  = 2.44 × 10^-4 ). A CAPN11 SNP (rs55877192) was suggestively associated with OHD (p_discovery  = 1.61 × 10^-7 ; p_replication  = 0.0016). Two other SNPs were suggestively associated (p < 1 × 10^-6 ) with OHD in only the discovery sample. In the case-control analyses, no SNPs were genome-wide significant, and, even with relaxed thresholds ( × _discovery  < 1 × 10^-5 and p_replication  < 0.05), only one SNP (rs188255766) in the infant analysis was associated with OHDs (p_discovery  = 1.42 × 10^-6 ; p_replication  = 0.04). Additional SNPs with p_discovery  < 1 × 10^-5 were in loci supporting previous findings but did not replicate. Overall, there was modest evidence of an association between rs2360743 and rs55877192 and OHD and some evidence validating previously published findings.

Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment

Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.

Residential particulate matter, proximity to major roads, traffic density and traffic volume as risk factors for preterm birth in California

BACKGROUND

While pollution from vehicle sources is an established risk factor for preterm birth, it is unclear whether distance of residence to the nearest major road or related measures like major road density represent useful measures for characterising risk.

OBJECTIVE

To determine whether major road proximity measures (including distance to major road, major road density and traffic volume) are more useful risk factors for preterm birth than other established vehicle-related measures (including particulate matter <2.5 μm in diameter (PM_2.5 ) and diesel particulate matter (diesel PM)).

METHODS

This retrospective cohort study included 2.7 million births across the state of California from 2011-2017; each address at delivery was geocoded. Geocoding was used to calculate distance to the nearest major road, major road density within a 500 m radius and major road density weighted by truck volume. We measured associations with preterm birth using risk ratios adjusted for target demographic, clinical, socioeconomic and environmental covariates (aRRs). We compared these to the associations between preterm birth and PM_2.5 and diesel PM by census tract of residence.

RESULTS

Findings showed that whereas higher mean levels of PM_2.5 and diesel PM by census tract were associated with a higher risk of preterm birth, living closer to roads or living in higher traffic density areas was not associated with higher risk. Residence in a census tract with a mean PM_2.5 in the top quartile compared with the lowest quartile was associated with the highest observed risk of preterm birth (aRR 1.04, 95% CI 1.04, 1.05).

CONCLUSIONS

Over a large geographical region with a diverse population, PM2.5 and diesel PM were associated with preterm birth, while measures of distance to major road were not, suggesting that these distance measures do not serve as a proxy for measures of particulate matter in the context of preterm birth.

Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

OBJECTIVE

Sulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.

RESEARCH DESIGN AND METHODS

As an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.

RESULTS

After establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.

CONCLUSIONS

We have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

The role of dementia diagnostic delay in the inverse cancer-dementia association

BACKGROUND

Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history.

METHODS

We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to US population and cohort data. We varied the average lapse between dementia onset and diagnosis, including non-differential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis.

RESULTS

Non-differential dementia diagnosis delay introduced minimal bias (IRRs=0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR=0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias.

CONCLUSIONS

Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.

Detecting methylation quantitative trait loci using a methylation random field method

DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.

Genetic determinants of blood-cell traits influence susceptibility to childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Despite overlap between genetic risk loci for ALL and hematologic traits, the etiological relevance of dysregulated blood-cell homeostasis remains unclear. We investigated this question in a genome-wide association study (GWAS) of childhood ALL (2,666 affected individuals, 60,272 control individuals) and a multi-trait GWAS of nine blood-cell indices in the UK Biobank. We identified 3,000 blood-cell-trait-associated (p < 5.0 × 10-8) variants, explaining 4.0% to 23.9% of trait variation and including 115 loci associated with blood-cell ratios (LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio). ALL susceptibility was genetically correlated with lymphocyte counts (rg = 0.088, p = 4.0 × 10-4) and PLR (rg = -0.072, p = 0.0017). In Mendelian randomization analyses, genetically predicted increase in lymphocyte counts was associated with increased ALL risk (odds ratio [OR] = 1.16, p = 0.031) and strengthened after accounting for other cell types (OR = 1.43, p = 8.8 × 10-4). We observed positive associations with increasing LMR (OR = 1.22, p = 0.0017) and inverse effects for NLR (OR = 0.67, p = 3.1 × 10-4) and PLR (OR = 0.80, p = 0.002). Our study shows that a genetically induced shift toward higher lymphocyte counts, overall and in relation to monocytes, neutrophils, and platelets, confers an increased susceptibility to childhood ALL.

Abstract NG03: Multiethnic prostate cancer GWAS meta-analysis identifies novel variants, improves genetic risk prediction across populations, and informs biological mechanisms of prostate cancer

Prostate cancer (PCa) is a highly heritable disease with large disparities in incidence rates across racial and ethnic populations. The inadequate representation of diverse populations in current genome-wide association studies (GWAS) limits the translational potential of findings to the world's populations and could result in biased risk prediction, further exacerbating health disparities. To improve our understanding of genetic risk of PCa, we conducted the largest multiethnic PCa GWAS meta-analysis to date with 107,247 cases and 127,006 controls from the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) consortium, including 85,554 cases and 91,972 controls of European ancestry, 10,368 cases and 10,986 controls of African ancestry, 8,611 cases and 18,809 controls of Asian ancestry, and 2,714 cases and 5,239 controls of Hispanic ethnicity. We identified 269 genetic risk variants independently associated with PCa risk, 86 of which were novel. Of the 183 previously reported prostate cancer risk variants, we identified stronger markers of risk for 62 variants using fine-mapping. To understand the aggregate effect of the 269 variants, we constructed a genetic risk score (GRS) using the multiethnic weights of the risk variants. Compared to men in the average 40-60% GRS category, the estimated OR for men in the top GRS decile (90-100%) was 5.06 [95% CI 4.84-5.29] for men of European ancestry, 3.74 [95% CI 3.36-4.17] for men of African ancestry, 4.47 [95% CI 3.52-5.68] for men of Asian ancestry, and 4.15 [95% CI 3.33-5.17] for Hispanic men. Men of African ancestry were estimated to have a 2.18-times higher mean GRS [95% CI 2.14-2.22], and men of Asian ancestry 0.73-times lower [95% CI 0.71-0.76], than men of European ancestry. Age significantly modified the GRS association with PCa risk, such that in men of European ancestry, the top decile GRS category was associated with an OR of 6.71 [95 % CI 5.99-7.52] for men ages 55 years or younger and 4.39 [95% CI 4.19-4.60] for men older than 55 years. Similarly, in men of African ancestry, the top GRS decile category was associated with an OR of 4.70 [95 % CI 3.65-6.07] for men ages 55 years or younger and 3.37 [95% CI 2.99-3.80] for men older than 55 years. We found that 51% of aggressive cases of European ancestry and 45% of aggressive cases of African ancestry were within the top 20% of the GRS. The lifetime absolute risk of PCa for men in the top decile of the GRS reached 38% for both African Americans [95% CI 36-41%] and Whites [95% CI 37-39%], 31% [95% CI 27-36%] for Hispanics and 26% [95% CI 22-30%] for Asians. For comparison, we constructed a genome-wide GRS, including the 269 variants and variants associated with PCa with P&lt;1.0 × 10−5. ORs calculated with genome-wide GRS were similar and had nearly identical discriminative ability as the 269 GRS in independent samples of 6,852 cases and 193,117 controls of European ancestry and 1,586 cases and 1,047 controls of African ancestry. This suggests that a genome-wide GRS may not have improved ability to predict PCa risk compared to the 269 GRS. To understand the biological mechanisms impacted by genetic risk of PCa, we conducted integrative analyses of the GRS and serum metabolomics in 611 African ancestry men from the Multiethnic Cohort. We found that a higher GRS was associated with lower sphingolipid levels (beta=-0.08, P=3.1 × 10−4), lower androgenic steroids (beta=-0.06, P=0.003), and higher sarcosine levels (beta=0.11, P=0.002). Further, using a latent clustering approach, we found that these metabolites in conjunction with the GRS contributed to the clustering of men with low-risk, intermediate-risk, and high-risk of PCa. These findings support the role of germline variation contributing to racial and ethnic disparities in PCa risk, with the GRS offering an approach for personalized risk prediction across populations and informing the biological mechanisms underlying PCa risk.

Citation Format: Burcu F. Darst, Lilit Moss, Edward J. Saunders, Nicholas Mancuso, Xin Sheng, Alisha Chou, Tokhir Dadaev, Sonja I. Berndt, Stephen K. Van Den Eeden, Stephen J. Chanock, Michael B. Cook, Tracy M. Layne, Demetrius Albanes, Hidewaki Nakagawa, John S. Witte, Practical Consortium, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, Christopher A. Haiman. Multiethnic prostate cancer GWAS meta-analysis identifies novel variants, improves genetic risk prediction across populations, and informs biological mechanisms of prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr NG03.

The Association Between Cancer and Spousal Rate of Memory Decline: A Negative Control Study to Evaluate (Unmeasured) Social Confounding of the Cancer-memory Relationship

Cancer diagnoses are associated with better long-term memory in older adults, possibly reflecting a range of social confounders that increase cancer risk but improve memory. We used spouse's memory as a negative control outcome to evaluate this possible confounding, since spouses share social characteristics and environments, and individuals' cancers are unlikely to cause better memory among their spouses. We estimated the association of an individual's incident cancer diagnosis (exposure) with their own (primary outcome) and their spouse's (negative control outcome) memory decline in 3601 couples from 1998 to 2014 in the Health and Retirement Study, using linear mixed-effects models. Incident cancer predicted better long-term memory for the diagnosed individual. We observed no association between an individual's cancer diagnosis and rate of spousal memory decline. This negative control study suggests that the inverse association between incident cancer and rate of memory decline is unlikely to be attributable to social/behavioral factors shared between spouses.

Abstract LB011: Meta-analysis in more than 80,000 men of African ancestry identified nine novel variants associated with prostate cancer

In search for common genetic variants contributing to the risk of prostate cancer in men of African ancestry, we conducted a meta-analysis of GWAS summary statistics from the African Ancestry Prostate Cancer Consortium (AAPC; 12,643 cases and 16,627 controls) and the VA Million Veteran Program (6,107 cases and 47,412 controls). A total of 29,896,808 common (minor allele frequency (MAF) &gt; 0.01) genotyped and imputed variants (r2 &gt; 0.3) were meta-analyzed in a total of 18,750 prostate cancer cases and 64,039 controls. Of the 269 established risk variants for prostate cancer, 265 were polymorphic and 168 were nominally (P&lt;0.05) associated with prostate cancer risk with directionally consistent effect estimates, of which 44 reached the genome-wide significance (P&lt;5x10-8). Of the 3,018 genome-wide significant variants, eight were considered novel susceptibility loci for prostate cancer in men of African ancestry. Of the eight variants, five were only found in populations of African ancestry (MAF 2% - 34%) but not in European or Asian populations, and two were substantially more common in African ancestry populations (MAF 40%) than in other populations (MAF &lt; 8%). One of the novel variants, rs60985508 (odds ratio (OR) = 1.12 [1.08 - 1.15]; P = 2.93×10-13; MAF = 34%), introduces a stop codon in exon 24 in the prostate-specific gene anoctamin 7 (ANO7), a known prostate cancer susceptibility gene. A polygenic risk score including 273 variants (265 of 269 established risk variants and 8 novel variants from this analysis) conferred an increased prostate cancer risk for men in the 90 - 100th percentile (OR = 3.91 [3.50 - 4.36]) and those in the 99 - 100th percentile (OR = 7.05 [5.51 - 9.02]), compared to men in the 40-60th percentile. These estimates were higher than what was observed with the PRS of 265 variants (90 - 100th percentile: OR = 3.49 [3.13 - 3.90]; 99 - 100th percentile: OR = 6.40 [4.99 - 8.21]). Our finding of 8 novel susceptibility loci for prostate cancer may improve risk prediction for men of African Ancestry and provide further insight into the underlying biology of prostate cancer.

Citation Format: Fei Chen, Ravi K. Madduri, Xin Sheng, Alex Rodriguez, Alisha Chou, Todd L. Edwards, Stephen K. Van Den Eeden, Rosalind A. Eeles, John S. Witte, Michael B. Cook, William J. Blot, David V. Conti, John M. Gaziano, Amy C. Justice, Christopher A. Haiman, VA Million Veteran Program and PRACTICAL/ELLIPSE Consortium. Meta-analysis in more than 80,000 men of African ancestry identified nine novel variants associated with prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB011.

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease

Background

Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.

Results

We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.

Conclusions

Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00975-2.

Cell-Free DNA Detection of Tumor Mutations in Heterogeneous, Localized Prostate Cancer Via Targeted, Multiregion Sequencing

Cell-free DNA (cfDNA) may allow for minimally invasive identification of biologically relevant genomic alterations and genetically distinct tumor subclones. Although existing biomarkers may detect localized prostate cancer, additional strategies interrogating genomic heterogeneity are necessary for identifying and monitoring aggressive disease. In this study, we aimed to evaluate whether circulating tumor DNA can detect genomic alterations present in multiple regions of localized prostate tumor tissue.

METHODS

Low-pass whole-genome and targeted sequencing with a machine-learning guided 2.5-Mb targeted panel were used to identify single nucleotide variants, small insertions and deletions (indels), and copy-number alterations in cfDNA. The majority of this study focuses on the subset of 21 patients with localized disease, although 45 total individuals were evaluated, including 15 healthy controls and nine men with metastatic castration-resistant prostate cancer. Plasma cfDNA was barcoded with duplex unique molecular identifiers. For localized cases, matched tumor tissue was collected from multiple regions (one to nine samples per patient) for comparison.

RESULTS

Somatic tumor variants present in heterogeneous tumor foci from patients with localized disease were detected in cfDNA, and cfDNA mutational burden was found to track with disease severity. Somatic tissue alterations were identified in cfDNA, including nonsynonymous variants in FOXA1, PTEN, MED12, and ATM. Detection of these overlapping variants was associated with seminal vesicle invasion (P = .019) and with the number of variants initially found in the matched tumor tissue samples (P = .0005).

CONCLUSION

Our findings demonstrate the potential of targeted cfDNA sequencing to detect somatic tissue alterations in heterogeneous, localized prostate cancer, especially in a setting where matched tumor tissue may be unavailable (ie, active surveillance or treatment monitoring).

A Large-Scale Association Study Detects Novel Rare Variants, Risk Genes, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility

To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th-60th percentile OR = 2.62, P = 2.55 × 10-191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits. SIGNIFICANCE: This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637.

Cell-free DNA concentration and fragment size as a biomarker for prostate cancer

Prostate cancer is the most commonly diagnosed neoplasm in American men. Although existing biomarkers may detect localized prostate cancer, additional strategies are necessary for improving detection and identifying aggressive disease that may require further intervention. One promising, minimally invasive biomarker is cell-free DNA (cfDNA), which consist of short DNA fragments released into circulation by dying or lysed cells that may reflect underlying cancer. Here we investigated whether differences in cfDNA concentration and cfDNA fragment size could improve the sensitivity for detecting more advanced and aggressive prostate cancer. This study included 268 individuals: 34 healthy controls, 112 men with localized prostate cancer who underwent radical prostatectomy (RP), and 122 men with metastatic castration-resistant prostate cancer (mCRPC). Plasma cfDNA concentration and fragment size were quantified with the Qubit 3.0 and the 2100 Bioanalyzer. The potential relationship between cfDNA concentration or fragment size and localized or mCRPC prostate cancer was evaluated with descriptive statistics, logistic regression, and area under the curve analysis with cross-validation. Plasma cfDNA concentrations were elevated in mCRPC patients in comparison to localized disease (OR_5ng/mL = 1.34, P = 0.027) or to being a control (OR_5ng/mL = 1.69, P = 0.034). Decreased average fragment size was associated with an increased risk of localized disease compared to controls (OR_5bp = 0.77, P = 0.0008). This study suggests that while cfDNA concentration can identify mCRPC patients, it is unable to distinguish between healthy individuals and patients with localized prostate cancer. In addition to PSA, average cfDNA fragment size may be an alternative that can differentiate between healthy individuals and those with localized disease, but the low sensitivity and specificity results in an imperfect diagnostic marker. While quantification of cfDNA may provide a quick, cost-effective approach to help guide treatment decisions in advanced disease, its use is limited in the setting of localized prostate cancer.

Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts

Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.

A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes

MOTIVATION

While gene-environment (GxE) interactions contribute importantly to many different phenotypes, detecting such interactions requires well-powered studies and has proven difficult. To address this, we combine two approaches to improve GxE power: simultaneously evaluating multiple phenotypes and using a two-step analysis approach. Previous work shows that the power to identify a main genetic effect can be improved by simultaneously analyzing multiple related phenotypes. For a univariate phenotype, two-step methods produce higher power for detecting a GxE interaction compared to single step analysis. Therefore, we propose a two-step approach to test for an overall GxE effect for multiple phenotypes.

RESULTS

Using simulations we demonstrate that, when more than one phenotype has GxE effect (i.e., GxE pleiotropy), our approach offers substantial gain in power (18%-43%) to detect an aggregate-level GxE effect for a multivariate phenotype compared to an analogous two-step method to identify GxE effect for a univariate phenotype. We applied the proposed approach to simultaneously analyze three lipids, LDL, HDL and Triglyceride with the frequency of alcohol consumption as environmental factor in the UK Biobank. The method identified two loci with an overall GxE effect on the vector of lipids, one of which was missed by the competing approaches.

AVAILABILITY

We provide an R package MPGE implementing the proposed approach which is available from CRAN: https://cran.r-project.org/web/packages/MPGE/index.html.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Inclusion of variants discovered from diverse populations improves polygenic risk score transferability

The majority of polygenic risk scores (PRSs) have been developed and optimized in individuals of European ancestry and may have limited generalizability across other ancestral populations. Understanding aspects of PRSs that contribute to this issue and determining solutions is complicated by disease-specific genetic architecture and limited knowledge of sharing of causal variants and effect sizes across populations. Motivated by these challenges, we undertook a simulation study to assess the relationship between ancestry and the potential bias in PRSs developed in European ancestry populations. Our simulations show that the magnitude of this bias increases with increasing divergence from European ancestry, and this is attributed to population differences in linkage disequilibrium and allele frequencies of European-discovered variants, likely as a result of genetic drift. Importantly, we find that including into the PRS variants discovered in African ancestry individuals has the potential to achieve unbiased estimates of genetic risk across global populations and admixed individuals. We confirm our simulation findings in an analysis of hemoglobin A1c (HbA1c), asthma, and prostate cancer in the UK Biobank. Given the demonstrated improvement in PRS prediction accuracy, recruiting larger diverse cohorts will be crucial—and potentially even necessary—for enabling accurate and equitable genetic risk prediction across populations.

Abstract PO-146: Multiethnic GWAS meta-analysis identifies novel variants and informs genetic risk prediction for prostate cancer across populations

Prostate cancer (PCa) is a highly heritable disease with large disparities in incidence rates across racial and ethnic populations. The inadequate representation of diverse populations in current genome-wide association studies (GWAS) limits the translational potential of findings to the world’s populations and could result in biased risk prediction, further exacerbating health disparities. To improve our understanding of genetic risk of PCa, we conducted a multiethnic meta-analysis of PCa GWAS using 107,247 cases and 127,006 controls from the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) consortium, including 85,554 cases and 91,972 controls of European ancestry, 10,368 cases and 10,986 controls of African ancestry, 8,611 cases and 18,809 controls of Asian ancestry, and 2,714 cases and 5,239 controls of Hispanic ancestry. We identified 269 genetic risk variants independently associated with PCa risk, 86 of which were novel. To understand the aggregate effect of the 269 variants, we constructed a genetic risk score (GRS) using the multiethnic weights of the risk variants. Compared to men in the average 40-60% GRS category, the estimated OR for men in the top GRS decile (90-100%) was 5.06 [95% CI 4.84-5.29] for men of European ancestry, 3.74 [95% CI 3.36-4.17] for men of African ancestry, 4.47 [95% CI 3.52-5.68] for men of Asian ancestry, and 4.15 [95% CI 3.33-5.17] for men of Hispanic ancestry. Men of African ancestry were estimated to have a 2.18-times higher mean GRS [95% CI 2.14-2.22], and men of Asian ancestry 0.73-times lower [95% CI 0.71- 0.76], than men of European ancestry. Age significantly modified the GRS association with PCa risk, such that in men of European ancestry, the top decile GRS category was associated with an OR of 6.71 [95 % CI 5.99-7.52] for men ages 55 years or younger and 4.39 [95% CI 4.19-4.60] for men older than 55 years. Similarly, in men of African ancestry, the top decile GRS category was associated with an OR of 4.70 [95% CI 3.65-6.07] for men ages 55 years or younger and 3.37 [95% CI 2.99-3.80] for men older than 55 years. We found that 51% of aggressive cases of European ancestry and 45% of aggressive cases of African ancestry were within the top 20% of the GRS. The lifetime absolute risk of PCa for men in the top decile of the GRS reached 38% for both African Americans [95% CI 36-41%] and Whites [95% CI 37-39%], 31% [95% CI 27-36%] for Hispanics and 26% [95% CI 22-30%] for Asians. For comparison, we constructed a genome-wide GRS, including the 269 variants and variants associated with PCa with P&lt;1.0 × 10-5. ORs calculated with genome-wide GRS were similar and had nearly identical discriminative ability as the 269 GRS in independent samples of 6,852 cases and 193,117 controls of European ancestry and 1,586 cases and 1,047 controls of African ancestry. These findings support the role of germline variation contributing to racial and ethnic disparities in PCa risk, with the GRS offering an approach for personalized risk prediction across populations.

Citation Format: David V. Conti, Burcu F. Darst, Lilit Moss, Edward J. Saunders, Xin Sheng, Alisha Chou, Tokhir Dadaev, Sonja I. Berndt, Stephen K. Van Den Eeden, Stephen J. Chanock, Michael B. Cook, Hidewaki Nakagawa, John S. Witte, Rosalind A. Eeles, Zsofia Kote-Jarai, Christopher A. Haiman. Multiethnic GWAS meta-analysis identifies novel variants and informs genetic risk prediction for prostate cancer across populations [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-146.

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.

Association between inflammatory bowel disease and prostate cancer: A large-scale, prospective, population-based study

Inflammatory bowel disease (IBD) is an established risk factor for colorectal cancer. Recent reports suggesting IBD is also a risk factor for prostate cancer (PC) require further investigation. We studied 218 084 men in the population-based UK Biobank cohort, aged 40 to 69 at study entry between 2006 and 2010, with follow-up through mid-2015. We assessed the association between IBD and subsequent PC using multivariable Cox regression analyses, adjusting for age at assessment, ethnic group, UK region, smoking status, alcohol drinking frequency, body mass index, Townsend Deprivation Index, family history of PC and previous prostate-specific antigen testing. Mean age at study entry was 56 years, 94% of the men were white, and 1.1% (n = 2311) had a diagnosis of IBD. After a median follow-up of 78 months, men with IBD had an increased risk of PC (adjusted hazard ratio [aHR] = 1.31, 95% confidence interval [CI] = 1.03-1.67, P = .029). The association with PC was only among men with the ulcerative colitis (UC; aHR = 1.47, 95% CI = 1.11-1.95, P = .0070), and not Crohn's disease (aHR 1.06, 95% CI = 0.63-1.80, P = .82). Results are limited by lack of data on frequency of health care interactions. In a large-scale, prospective cohort study, we detected an association between IBD, and UC specifically, with incident PC diagnosis.

Association Between Alzheimer Disease and Cancer With Evaluation of Study Biases: A Systematic Review and Meta-analysis

IMPORTANCE

Observational studies consistently report inverse associations between cancer and Alzheimer disease (AD). Shared inverse etiological mechanisms might explain this phenomenon, but a systematic evaluation of methodological biases in existing studies is needed.

OBJECTIVES

To systematically review and meta-analyze evidence on the association between cancer and subsequent AD, systematically identify potential methodological biases in studies, and estimate the influence of these biases on the estimated pooled association between cancer and AD.

DATA SOURCES

All-language publications were identified from PubMed, Embase, and PsycINFO databases through September 2, 2020.

STUDY SELECTION

Longitudinal cohort studies and case-control studies on the risk of AD in older adults with a history of any cancer type, prostate cancer, breast cancer, colorectal cancer, or nonmelanoma skin cancer, relative to those with no cancer history.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently abstracted the data and evaluated study biases related to confounding, diagnostic bias, competing risks, or survival bias. Random-effects meta-analysis was used to provide pooled estimates of the association between cancer and AD. Metaregressions were used to evaluate whether the observed pooled estimate could be attributable to each bias. The study was designed and conducted according to the Preferring Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.

MAIN OUTCOMES AND MEASURES

Incidence, hazard, or odds ratios for AD comparing older adults with vs without a previous cancer diagnosis.

RESULTS

In total, 19 cohort studies and 3 case-control studies of the associations between any cancer type (n = 13), prostate cancer (n = 5), breast cancer (n = 1), and nonmelanoma skin cancer (n = 3) with AD were identified, representing 9 630 435 individuals. In all studies combined, cancer was associated with decreased AD incidence (cohort studies: random-effects hazard ratio, 0.89; 95% CI, 0.79-1.00; case-control studies: random-effects odds ratio, 0.75; 95% CI, 0.61-0.93). Studies with insufficient or inappropriate confounder control or greater likelihood of AD diagnostic bias had mean hazard ratios closer to the null value, indicating that these biases could not explain the observed inverse association. Competing risks bias was rare. Studies with greater likelihood of survival bias had mean hazard ratios farther from the null value.

CONCLUSIONS AND RELEVANCE

The weak inverse association between cancer and AD may reflect shared inverse etiological mechanisms or survival bias but is not likely attributable to diagnostic bias, competing risks bias, or insufficient or inappropriate control for potential confounding factors.