Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia

Genome-wide association studies (GWAS) have advanced our understanding of susceptibility to B-cell precursor acute lymphoblastic leukemia (BCP-ALL); however, much of the heritable risk remains unidentified. Here, we perform a GWAS and conduct a meta-analysis with two existing GWAS, totaling 2442 cases and 14,609 controls. We identify risk loci for BCP-ALL at 8q24.21 (rs28665337, P = 3.86 × 10-9, odds ratio (OR) = 1.34) and for ETV6-RUNX1 fusion-positive BCP-ALL at 2q22.3 (rs17481869, P = 3.20 × 10-8, OR = 2.14). Our findings provide further insights into genetic susceptibility to ALL and its biology.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium

This corrects the article DOI: 10.1038/bjc.2017.231.

External validation of risk prediction models for incident colorectal cancer using UK Biobank

BACKGROUND

This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire.

METHODS

External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries.

RESULTS

There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals.

CONCLUSIONS

Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.

The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study

BACKGROUND

The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer.

METHODS

We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality.

RESULTS

The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p < 0.0001). The CPGs were significantly better at stratified prediction of PCM compared to the current three-tiered system (concordance index (C-index) 0.81 vs. 0.77, p < 0.0001). This superiority was maintained for every age group division (p < 0.0001). Also in the ethnically different Singapore cohort of 2550 men with 142 prostate cancer deaths, the CPG model outperformed the three strata categories (C-index 0.79 vs. 0.76, p < 0.0001). The model also retained superior prognostic discrimination in the treatment sub-groups: radical prostatectomy (n = 20,586), C-index 0.77 vs. 074; radiotherapy (n = 11,872), C-index 0.73 vs. 0.69; and conservative management (n = 14,950), C-index 0.74 vs. 0.73. The CPG groups that sub-divided the old intermediate-risk (CPG2 vs. CPG3) and high-risk categories (CPG4 vs. CPG5) significantly discriminated PCM outcomes after radical therapy or conservative management (p < 0.0001).

CONCLUSIONS

This validation study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.

Validation of loci at 2q14.2 and 15q21.3 as risk factors for testicular cancer

Testicular germ cell tumor (TGCT), the most common cancer in men aged 18 to 45 years, has a strong heritable basis. Genome-wide association studies (GWAS) have proposed single nucleotide polymorphisms (SNPs) at a number of loci influencing TGCT risk. To further evaluate the association of recently proposed risk SNPs with TGCT at 2q14.2, 3q26.2, 7q36.3, 10q26.13 and 15q21.3, we analyzed genotype data on 3,206 cases and 7,422 controls. Our analysis provides independent replication of the associations for risk SNPs at 2q14.2 (rs2713206 at P = 3.03 × 10-2; P-meta = 3.92 × 10-8; nearest gene, TFCP2L1) and rs12912292 at 15q21.3 (P = 7.96 × 10-11; P-meta = 1.55 × 10-19; nearest gene PRTG). Case-only analyses did not reveal specific associations with TGCT histology. TFCP2L1 joins the growing list of genes located within TGCT risk loci with biologically plausible roles in developmental transcriptional regulation, further highlighting the importance of this phenomenon in TGCT oncogenesis.

DNA repair gene panel mutations in young onset prostate cancer cases in the

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Background: Prostate cancer (PrCa) is the most common solid tumour in men in the Western world. There is substantial evidence that PrCa predisposition is due both to common and rare germline variation. Methods: We screened 167 genes from DNA damage response and repair pathways, within a UK based cohort of young onset cases (diagnosed at < 65 years) and controls. Samples were sequenced using a custom Agilent SureSelectXT bait library and Illumina HiSeq technology and processed using a BWA/GATK 2.8 pipeline. Following sample QC, data were analysed from 1,285 PrCa cases and 1,163 controls. Results: We identified 5,086 single nucleotide variants (SNVs) and 175 indels; 233 unique protein truncating variants (PTVs) with MAF < 0.5% in controls were found in 97 genes of the screening panel. The total proportion of PTV carriers in cases was higher than in controls (14.5% vs. 11.6%, P = 0.036; OR = 1.29, 95% CI 1.01-1.64). This enrichment was greater within the previously reported BROCA gene set of 22 tumour suppressor genes (4.5% vs 2.2%, P = 2.5x10-3; OR = 2.07, 95% CI 1.28-3.34). To identify genes which best to distinguish PrCa cases from controls, we applied the adaptive combination of P values algorithm, ADA, for genes with at least 2 carriers of PTVs. This analysis selected 10 genes, (OR = 3.37, 95% CI 2.05-5.66, PADA= 5.99x10-3); men with PTVs in these were about 3.4-fold more likely to have PrCa (5.8% vs. 1.8%). We subsequently compared aggressive cases (Gleason score ≥ 8, n = 204) with non-aggressive cases (Gleason score ≤ 7, n = 1049) and lethal PrCa cases (cause of death PrCa, n = 183) with indolent cases (Gleason score ≤ 6, n = 563) to evaluate genes associated with poor clinical prognosis. Using ADA, 4 genes were selected for aggressive PrCa ( PADA= 0.006) and 2 of these also for lethal PrCa ( PADA= 0.057). Conclusions: These gene sets provide an 11 gene panel which could be used for clinical testing and will help to facilitate the development of a PrCa specific sequencing panel with both predictive and prognostic potential.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts

OBJECTIVES

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

DESIGN

Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

SETTING

Multiple institutions that were members of international PRACTICAL consortium.

PARTICIPANTS

All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

MAIN OUTCOME MEASURES

Prediction with hazard score of age of onset of aggressive cancer in validation set.

RESULTS

In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

CONCLUSIONS

Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Responses to provision of personalised cancer risk information: a qualitative interview study with members of the public

BACKGROUND

It is estimated that nearly 600,000 cancer cases in the UK could have been avoided in the past five years if people had healthier lifestyles. A number of theories of behaviour change suggest that before people will change health behaviours, they must accept that a risk applies to them. This study aimed to explore the views of the public on receiving personalised cancer risk information and the potential for that information to motivate behaviour change.

METHODS

We conducted 27 interviews with members of the public (mean age 49 ± 23 years). Each participant completed a questionnaire to allow calculation of their risk of developing the most common cancers (10 for women, 8 for men). During the interviews we presented their risk using a web-based tool developed for the study and discussions covered their views on receiving that information. Each interview was audio-recorded and then analysed using thematic analysis.

RESULTS

Participants generally viewed the concept of personalised cancer risk positively. The first reaction of almost all when presented with their 10-year risk of an individual cancer without any further context was that it was low and not concerning. Views on what constituted a high risk ranged widely, from 0.5 to 60%. All felt seeing the impact of changes in lifestyle was helpful. For some this led to intentions to change behaviour, but reductions in risk were not always motivating as the risks were considered low and differences small.

CONCLUSIONS

Provision of personalised cancer risk was well received and may be a useful addition to other cancer prevention initiatives. Further work is needed in particular to develop ways to present cancer risk that reflect the general perception of what constitutes a risk high enough to motivate behaviour change and help patients contextualise a less well known health risk by providing a frame of reference.

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

Several susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and 16,749 controls. We identify risk loci for all classical Hodgkin lymphoma at 6q22.33 (rs9482849, P = 1.52 × 10-8) and for nodular sclerosis Hodgkin lymphoma at 3q28 (rs4459895, P = 9.43 × 10-17), 6q23.3 (rs6928977, P = 4.62 × 10-11), 10p14 (rs3781093, P = 9.49 × 10-13), 13q34 (rs112998813, P = 4.58 × 10-8) and 16p13.13 (rs34972832, P = 2.12 × 10-8). Additionally, independent loci within the HLA region are observed for nodular sclerosis Hodgkin lymphoma (rs9269081, HLA-DPB1*03:01, Val86 in HLA-DRB1) and mixed cellularity Hodgkin lymphoma (rs1633096, rs13196329, Val86 in HLA-DRB1). The new and established risk loci localise to areas of active chromatin and show an over-representation of transcription factor binding for determinants of B-cell development and immune response.

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Reproductive profiles and risk of breast cancer subtypes: a multi-center case-only study

BACKGROUND

Previous studies have shown that reproductive factors are differentially associated with breast cancer (BC) risk by subtypes. The aim of this study was to investigate associations between reproductive factors and BC subtypes, and whether these vary by age at diagnosis.

METHODS

We used pooled data on tumor markers (estrogen and progesterone receptor, human epidermal growth factor receptor-2 (HER2)) and reproductive risk factors (parity, age at first full-time pregnancy (FFTP) and age at menarche) from 28,095 patients with invasive BC from 34 studies participating in the Breast Cancer Association Consortium (BCAC). In a case-only analysis, we used logistic regression to assess associations between reproductive factors and BC subtype compared to luminal A tumors as a reference. The interaction between age and parity in BC subtype risk was also tested, across all ages and, because age was modeled non-linearly, specifically at ages 35, 55 and 75 years.

RESULTS

Parous women were more likely to be diagnosed with triple negative BC (TNBC) than with luminal A BC, irrespective of age (OR for parity = 1.38, 95% CI 1.16-1.65, p = 0.0004; p for interaction with age = 0.076). Parous women were also more likely to be diagnosed with luminal and non-luminal HER2-like BCs and this effect was slightly more pronounced at an early age (p for interaction with age = 0.037 and 0.030, respectively). For instance, women diagnosed at age 35 were 1.48 (CI 1.01-2.16) more likely to have luminal HER2-like BC than luminal A BC, while this association was not significant at age 75 (OR = 0.72, CI 0.45-1.14). While age at menarche was not significantly associated with BC subtype, increasing age at FFTP was non-linearly associated with TNBC relative to luminal A BC. An age at FFTP of 25 versus 20 years lowered the risk for TNBC (OR = 0.78, CI 0.70-0.88, p < 0.0001), but this effect was not apparent at a later FFTP.

CONCLUSIONS

Our main findings suggest that parity is associated with TNBC across all ages at BC diagnosis, whereas the association with luminal HER2-like BC was present only for early onset BC.

Association analysis identifies 65 new breast cancer risk loci

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium

BACKGROUND

Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer.

METHODS

We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions.

RESULTS

The results suggest that height is associated with high-grade prostate cancer risk. Men with height >180 cm are at a 22% increased risk as compared to men with height <173 cm (OR 1.22, 95% CI 1.01-1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group.

CONCLUSIONS

There was no evidence of gene-environment interaction between height and the selected candidate SNPs.Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.

Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor

Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Defective microtubule assembly and dysregulation of KIT-MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

BRCA2 Hypomorphic Missense Variants Confer Moderate Risks of Breast Cancer

Breast cancer risks conferred by many germline missense variants in the BRCA1 and BRCA2 genes, often referred to as variants of uncertain significance (VUS), have not been established. In this study, associations between 19 BRCA1 and 33 BRCA2 missense substitution variants and breast cancer risk were investigated through a breast cancer case-control study using genotyping data from 38 studies of predominantly European ancestry (41,890 cases and 41,607 controls) and nine studies of Asian ancestry (6,269 cases and 6,624 controls). The BRCA2 c.9104A>C, p.Tyr3035Ser (OR = 2.52; P = 0.04), and BRCA1 c.5096G>A, p.Arg1699Gln (OR = 4.29; P = 0.009) variant were associated with moderately increased risks of breast cancer among Europeans, whereas BRCA2 c.7522G>A, p.Gly2508Ser (OR = 2.68; P = 0.004), and c.8187G>T, p.Lys2729Asn (OR = 1.4; P = 0.004) were associated with moderate and low risks of breast cancer among Asians. Functional characterization of the BRCA2 variants using four quantitative assays showed reduced BRCA2 activity for p.Tyr3035Ser compared with wild-type. Overall, our results show how BRCA2 missense variants that influence protein function can confer clinically relevant, moderately increased risks of breast cancer, with potential implications for risk management guidelines in women with these specific variants. Cancer Res; 77(11); 2789-99. ©2017 AACR.

Abstract B16: Development of breast cancer risk prediction for the UK population using the UK Biobank dataset

Breast cancer is the most common female cancer and is the second most common cause of cancer death among females. The UK has the highest age standardised incidence and mortality rates in the world, with two in every 1000 women aged 50 and above developing breast cancer annually. Several risk prediction models have been developed to estimate the likelihood for developing breast cancer based on specific risk factors in currently healthy individuals within a specific period of time. The available models are derived principally from either genetic or non-genetic factors. The majority of these models are however not user-friendly, do not focus on modifiable factors entirely and are not specifically designed for the general public.

Our research group is developing an individualised risk prediction model for breast cancer focusing on the modifiable risk factors using the UK Biobank data. A nested case-control study within the 273,467 female participants is being used to develop the model. We have split the data into training and testing sets and will carry out all statistical tests to ensure our model calibrates well. For model validation, we will further seek external validation cohorts. The model will provide risk scores derived from the presence or absence of specific risk factors and will be compared to the general public score. The model will allow people to modify their risk profile with appropriate prevention measures. The main goal of the model is to be used in cancer education and prevention.

The results from exploratory analyses suggested positive associations between breast cancer risk and age, breast cancer family history, menopause age, age at first child, BMI, height, null-parity, smoking, alcohol intake, and family history of other cancer. An algorithmic model will be developed based on these factors. We will also evaluate public perceptions using focus group technique. We will be presenting the results of the model development from the training set and the results of the internal validation from the testing set.

In conclusion, we are developing an individualised breast cancer risk prediction model for the UK population based on the modifiable risk factors. The model will enable us to educate and to design appropriate interventions tailored to the individual with the aim of assisting them to make appropriate changes to modify their cancer risk profile.

Citation Format: Kawthar Alajmi, Artitaya Lophatananon, Kenneth Muir. Development of breast cancer risk prediction for the UK population using the UK Biobank dataset. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B16.

Evaluating genetic variants associated with breast cancer risk in high and moderate-penetrance genes in Asians

Over the past 20 years, high-penetrance pathogenic mutations in genes BRCA1, BRCA2, TP53, PTEN, STK11 and CDH1 and moderate-penetrance mutations in genes CHEK2, ATM, BRIP1, PALB2, RAD51C, RAD50 and NBN have been identified for breast cancer. In this study, we investigated whether there are additional variants in these 13 genes associated with breast cancer among women of Asian ancestry. We analyzed up to 654 single nucleotide polymorphisms (SNPs) from 6269 cases and 6624 controls of Asian descent included in the Breast Cancer Association Consortium (BCAC), and up to 236 SNPs from 5794 cases and 5529 controls included in the Shanghai Breast Cancer Genetics Study (SBCGS). We found three missense variants with minor allele frequency (MAF) <0.05: rs80358978 (Gly2508Ser), rs80359065 (Lys2729Asn) and rs11571653 (Met784Val) in the BRCA2 gene, showing statistically significant associations with breast cancer risk, with P-values of 1.2 × 10-4, 1.0 × 10-3 and 5.0 × 10-3, respectively. In addition, we found four low-frequency variants (rs8176085, rs799923, rs8176173 and rs8176258) in the BRCA1 gene, one common variant in the CHEK2 gene (rs9620817), and one common variant in the PALB2 gene (rs13330119) associated with breast cancer risk at P < 0.01. Our study identified several new risk variants in BRCA1, BRCA2, CHEK2, and PALB2 genes in relation to breast cancer risk in Asian women. These results provide further insights that, in addition to the high/moderate penetrance mutations, other low-penetrance variants in these genes may also contribute to breast cancer risk.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns

Motivation

Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped.

Results

We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns.

Availability and Implementation

The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ .

Contact

hlin1@lsuhsc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Sex and Stroke in Thrombolyzed Patients and Controls

Background and Purpose—

We hypothesized that any sex-related difference in outcome poststroke is explained by other prognostic factors and that the response to intravenous recombinant tissue-type plasminogen activator (r-tPA) is equal in males and females after adjustment for such factors.

Methods—

We accessed an independent collection of randomized clinical trials—the VISTA (Virtual International Stroke Trials Archive). Data were preprocessed by selecting complete cases (n=8028) and matching females to males (coarsened exact matching, n=4575, 24.3% r-tPA). Outcome was assessed by the 7-point modified Rankin Scale (mRS) measured at 90 days after ischemic stroke. Relationship among variables was estimated by adjusted regression analysis.

Results—

In nonthrombolyzed patients, ordinal analysis of mRS adjusting for stroke- and sex-related prognostic factors suggested comparable outcomes for females and males (odds ratio, 0.96; 95% confidence interval, 0.85–1.06). Females responded comparably to r-tPA as did males, irrespective of the outcome definition of mRS (ordinal: P Interaction =0.46, relative excess risk because of interaction=0). The number needed to treat was 6.8 and 11.2 for 1 female to achieve mRS score of 0 to 2 and 0 to 1, which was highly congruent with males. Analysis for a nonlinear variation of age-by-sex revealed a good outcome for females <45 years with significant disadvantage thereafter (mRS score of 0–2: P Interaction =0.004). No relationship between sex, r-tPA, and bleeding complications was evident.

Conclusions—

Functional outcome (mRS) without r-tPA was overall similar between the sexes, as was the response to r-tPA. Nonlinear sex-by-age interaction improved estimates of functional independence; this should be considered in sex-related studies in stroke.

Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis

Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high-grade compared to low-grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all-cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer-specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression.

Alcohol consumption and prostate cancer incidence and progression: A Mendelian randomisation study

Prostate cancer is the most common cancer in men in developed countries, and is a target for risk reduction strategies. The effects of alcohol consumption on prostate cancer incidence and survival remain unclear, potentially due to methodological limitations of observational studies. In this study, we investigated the associations of genetic variants in alcohol-metabolising genes with prostate cancer incidence and survival. We analysed data from 23,868 men with prostate cancer and 23,051 controls from 25 studies within the international PRACTICAL Consortium. Study-specific associations of 68 single nucleotide polymorphisms (SNPs) in 8 alcohol-metabolising genes (Alcohol Dehydrogenases (ADHs) and Aldehyde Dehydrogenases (ALDHs)) with prostate cancer diagnosis and prostate cancer-specific mortality, by grade, were assessed using logistic and Cox regression models, respectively. The data across the 25 studies were meta-analysed using fixed-effect and random-effects models. We found little evidence that variants in alcohol metabolising genes were associated with prostate cancer diagnosis. Four variants in two genes exceeded the multiple testing threshold for associations with prostate cancer mortality in fixed-effect meta-analyses. SNPs within ALDH1A2 associated with prostate cancer mortality were rs1441817 (fixed effects hazard ratio, HRfixed  = 0.78; 95% confidence interval (95%CI):0.66,0.91; p values = 0.002); rs12910509, HRfixed  = 0.76; 95%CI:0.64,0.91; p values = 0.003); and rs8041922 (HRfixed  = 0.76; 95%CI:0.64,0.91; p values = 0.002). These SNPs were in linkage disequilibrium with each other. In ALDH1B1, rs10973794 (HRfixed  = 1.43; 95%CI:1.14,1.79; p values = 0.002) was associated with prostate cancer mortality in men with low-grade prostate cancer. These results suggest that alcohol consumption is unlikely to affect prostate cancer incidence, but it may influence disease progression.

Telomere structure and maintenance gene variants and risk of five cancer types

Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10-5 ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry

BACKGROUND

Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry.

METHODS

We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk.

RESULTS

We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P < 0.05. Compared with women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively.

CONCLUSION

Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

BACKGROUND

The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.

METHODS

We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.

RESULTS

For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.

CONCLUSIONS

This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.