Boosting and lassoing new prostate cancer SNP risk factors and their connection to selenium

We begin by arguing that the often used algorithm for the discovery and use of disease risk factors, stepwise logistic regression, is unstable. We then argue that there are other algorithms available that are much more stable and reliable (e.g. the lasso and gradient boosting). We then propose a protocol for the discovery and use of risk factors using lasso or boosting variable selection. We then illustrate the use of the protocol with a set of prostate cancer data and show that it recovers known risk factors. Finally, we use the protocol to identify new and important SNP based risk factors for prostate cancer and further seek evidence for or against the hypothesis of an anticancer function for Selenium in prostate cancer. We find that the anticancer effect may depend on the SNP-SNP interaction and, in particular, which alleles are present.

The effect of CYP7B1 polymorphisms on the risk of coronary heart disease in Hainan Han population

Background Coronary heart disease (CHD) is the leading cause of human death worldwide. Genetic factors play an important role in the occurrence of CHD. Our study is designed to investigate the influence of CYP7B1 polymorphisms on CHD risk. Methods In this case–control study, 508 CHD patients and 510 healthy individuals were recruited to determine the correlation between CYP7B1 polymorphisms (rs7836768, rs6472155, and rs2980003) and CHD risk. The associations were evaluated by computing odds ratios (OR) and 95% confidence intervals (CI) with logistic regression analysis. The association between SNP-SNP interaction and CHD susceptibility was carried out by multifactor dimensionality reduction analyses. Results Our study found that rs6472155 is significantly associated with an increased risk of CHD in age > 60 years (OR 2.20, 95% CI = 1.07–4.49, p = 0.031), women (OR 3.17, 95% CI = 1.19–8.44, p = 0.021), and non-smokers (3.43, 95% CI = 1.16–10.09, p = 0.025). Rs2980003 polymorphism has a lower risk of CHD in drinkers (OR 0.47, 95% CI = 0.24–0.91, p = 0.025). Further analyses based on false-positive report probability validated these significant results. Besides, it was found that rs6472155 polymorphism was associated with uric acid level (p = 0.034). Conclusion Our study indicated that CYP7B1 polymorphisms are related to the risk of CHD, which provides a new perspective for prevent of CHD.

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Germline polymorphisms in genes maintaining replication fork to predict the efficacy of oxaliplatin and irinotecan in metastatic colorectal cancer (mCRC) patients enrolled in MAVERICC trial.

3139 Background: Protection of replication forks is critical for the survival of cancer cells. Chemotherapeutic drugs such as oxaliplatin and irinotecan can impede the progression of replication forks by inducing DNA lesions, which cause fork collapse and generate double-strand breaks. We hypothesized that functional genetic variants in genes involved in the maintenance of replication forks may predict the efficacy of cytotoxic drugs in mCRC patients. Methods: We analyzed genomic and clinical data from MAVERICC, a phase II trial which compared mFOLFOX6 and FOLFIRI in combination with bevacizumab in untreated mCRC patients. Genomic DNA extracted from blood samples was genotyped using an OncoArray (Illumina, Inc., San Diego, CA, USA). Candidate six missense single nucleotide polymorphisms (SNPs) ( SLFN11 rs9898983, SLFN11 rs12453150, RPA1 rs5030749, MCM3 rs2230240, TIMELESS rs2291739, and TIMELESS rs774047) were tested for association with progression-free survival (PFS) and overall survival (OS), using Cox proportional hazards model. To confirm the predictive value, the treatment-by-SNP interaction was tested. Results: A total of 324 patients were available for the SNP analyses (mFOLFOX6 plus bevacizumab arm [OHP arm]: n = 161; FOLFIRI plus bevacizumab arm [IRI arm]: n = 163). In the OHP arm, univariable analysis showed a significantly better PFS in patients with G/G genotype of TIMELESS rs2291739 compared to those with any A allele, and in patients with T/T genotype of TIMELESS rs774047 compared to those with any C allele. However, neither of these SNP’s associations were confirmed by multivariable analysis: TIMELESS rs2291739 (any A allele vs G/G, hazard ratio [HR] = 0.60, 95% confidence interval [CI] = 0.31–1.17, p = 0.12) and TIMELESS rs774047 (any C allele vs T/T, HR = 0.74, 95% CI = 0.41–1.36, p = 0.33). In the IRI arm, univariable analysis showed a significantly worse OS in patients with G/G genotype of TIMELESS rs2291739 compared to those with any A allele, and in patients with T/T genotype of TIMELESS rs774047 compared to those with any C allele. Multivariable analysis confirmed the significant associations in these SNPs: TIMELESS rs2291739 (any A allele vs G/G, HR = 3.06, 95% CI = 1.49–6.25, p < 0.01) and TIMELESS rs774047 (any C allele vs T/T, HR = 2.95, 95% CI = 1.43–6.08, p < 0.01). Treatment-by-SNP interaction test confirmed the significant predictive value of both SNPs, both on PFS and OS. Conclusions: Germline polymorphisms in the TIMELESS gene involved in the protection of replication forks may predict efficacy of oxaliplatin and irinotecan in mCRC patients. Our novel findings warrant further validation studies.

Predictive SNPs for β0-thalassemia/HbE disease severity

Abstractβ-Thalassemia/HbE disease has a wide spectrum of clinical phenotypes ranging from asymptomatic to dependent on regular blood transfusions. Ability to predict disease severity is helpful for clinical management and treatment decision making. A thalassemia severity score has been developed from Mediterranean β-thalassemia patients. However, different ethnic groups may have different allele frequency and linkage disequilibrium structures. Here, Thai β0-thalassemia/HbE disease genome-wild association studies (GWAS) data of 487 patients were analyzed by SNP interaction prioritization algorithm, interacting Loci (iLoci), to find predictive SNPs for disease severity. Three SNPs from two SNP interaction pairs associated with disease severity were identifies. The three-SNP disease severity risk score composed of rs766432 in BCL11A, rs9399137 in HBS1L-MYB and rs72872548 in HBE1 showed more than 85% specificity and 75% accuracy. The three-SNP predictive score was then validated in two independent cohorts of Thai and Malaysian β0-thalassemia/HbE patients with comparable specificity and accuracy. The SNP risk score could be used for prediction of clinical severity for Southeast Asia β0-thalassemia/HbE population.

KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10–9) and 3145 (P < 1 × 10–5) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

Endocannabinoid Gene × Gene Interaction Association to Alcohol Use Disorder in Two Adolescent Cohorts

Genetic markers of the endocannabinoid system have been linked to a variety of addiction-related behaviors that extend beyond cannabis use. In the current study we investigate the relationship between endocannabinoid (eCB) genetic markers and alcohol use disorder (AUD) in European adolescents (14–18 years old) followed in the IMAGEN study (n = 2,051) and explore replication in a cohort of North American adolescents from Canadian Saguenay Youth Study (SYS) (n = 772). Case-control status is represented by a score of more than 7 on the Alcohol Use Disorder Identification Test (AUDIT). First a set-based test method was used to examine if a relationship between the eCB system and AUDIT case/control status exists at the gene level. Using only SNPs that are both independent and significantly associated to case-control status, we perform Fisher's exact test to determine SNP level odds ratios in relation to case-control status and then perform logistic regressions as post-hoc analysis, while considering various covariates. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the most robust SNP×SNP interaction of the five eCB genes with positive AUDIT screen. While no gene-sets were significantly associated to AUDIT scores after correction for multiple tests, in the case/control analysis, 7 SNPs were significantly associated with AUDIT scores of &gt; 7 (p &lt; 0.05; OR&lt;1). Two SNPs remain significant after correction by false discovery rate (FDR): rs9343525 in CNR1 (pcorrected =0.042, OR = 0.73) and rs507961 in MGLL (pcorrected = 0.043, OR = 0.78). Logistic regression showed that both rs9353525 (CNR1) and rs507961 (MGLL) remained significantly associated with positive AUDIT screens (p &lt; 0.01; OR &lt; 1) after correction for multiple covariables and interaction of covariable × SNP. This result was not replicated in the SYS cohort. The GMDR model revealed a significant three-SNP interaction (p = 0.006) involving rs484061 (MGLL), rs4963307 (DAGLA), and rs7766029 (CNR1) predicted case-control status, after correcting for multiple covariables in the IMAGEN sample. A binomial logistic regression of the combination of these three SNPs by phenotype in the SYS cohort showed a result in the same direction as seen in the IMAGEN cohort (BETA = 0.501, p = 0.06). While preliminary, the present study suggests that the eCB system may play a role in the development of AUD in adolescents.