Enes Makalic

Variants in the VEGFA Gene and Treatment Outcome after Anti-VEGF Treatment for Neovascular Age-related Macular Degeneration

PURPOSE To determine the association of genetic variants of the VEGFA gene with outcome of anti-vascular endothelial growth factor (VEGF) treatment in neovascular age-related macular degeneration (AMD). DESIGN A prospective cohort study. PARTICIPANTS We included 201 consecutive patients receiving anti-VEGF injections for neovascular AMD. METHODS Patients were followed over 12 months. They were treated with 3 initial monthly ranibizumab or bevacizumab injections. Thereafter, the decision to retreat was made by clinicians at each follow-up visit on the basis of retreatment criteria. Seven tagged single nucleotide polymorphisms (tSNPs) in the VEGFA gene were selected and examined. Multivariate data analysis was used to determine the role of each tSNP in treatment outcome. MAIN OUTCOME MEASURES The influence of selected VEGFA tSNPs on visual acuity (VA) outcome at 6 months. RESULTS Mean baseline VA was 51±17 Early Treatment Diabetic Retinopathy Study (ETDRS) letter scores. Overall, the mean change in VA from baseline was +6.5±12, +4.4±13.4, and +2.3±14.6 letters at 3, 6, and 12 months, respectively. The tSNP rs3025000 was the only SNP significantly associated (P<1 × 10(-4)) with visual outcome at 6 months with multiple correction. The presence of the T allele (TC or TT genotypes) at this tSNP predicted a better outcome of +7 letters at 6 months compared with the CC genotype. In a subgroup analysis, presence of the T allele predicted a significantly higher chance of the patients belonging to the responder group (gain of ≥5 letters from baseline) after 3, 6, and 12 months treatment (odds ratio, 2.7, 3.5, and 2.4; 95% confidence interval, 1.46-5.07, 1.82-6.71, and 1.27-4.57, respectively) than any other outcome group. CONCLUSIONS Pharmacogenetic association with anti-VEGF treatments may influence the visual outcomes in neovascular AMD. In patients with the T allele in tSNP rs3025000, there was a significantly better visual outcome at 6 months and a greater chance of the patients belonging to the responder group with anti-VEGF treatment at 3, 6, and 12 months. The VA outcomes of patients harboring the T allele at SNP rs3025000 were comparable with those of the pivotal clinical trials but with fewer injections, making the treatment perhaps more cost effective in certain subgroups of patients. FINANCIAL DISCLOSURE(S) The authors have no proprietary or commercial interest in any of the materials discussed in this article.

A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10−8) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10−4) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10−6. In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer. Cancer Epidemiol Biomarkers Prev; 23(4); 658–69. ©2014 AACR.

Melanoma risk for CDKN2A mutation carriers who are relatives of population-based case carriers in Australia and the UK

Background CDKN2A mutations confer a substantial risk of cutaneous melanoma; however, the magnitude of risk is uncertain. Methods The study estimated the hazard ratio (HR) and the average age specific cumulative risk (ie, penetrance) of reported melanoma for CDKN2A mutation carriers in case families using a modified segregation analysis of the first and higher degree relatives of 35 population-based cases. The study sample included 223 relatives of 13 melanoma cases diagnosed when aged 18–39 years from Melbourne, Sydney and Brisbane, Australia, and 322 relatives of 22 melanoma cases diagnosed at any age from Yorkshire, UK. Results The estimated HR for melanoma for mutation carriers relative to the general population decreased with regions of increasing ambient ultraviolet (UV) irradiance, being higher for the UK than Australia (87, 95% CI 50 to 153 vs 31, 95% CI 20 to 50, p=0.008), and across Australia, 49 (95% CI 24 to 98) for Melbourne, 44 (95% CI 22 to 88) for Sydney, and 9 (95% CI 2 to 33) for Brisbane (p=0.02). Penetrance did not differ by geographic region. It is estimated that 16% (95% CI 10% to 27%) of UK and 20% (95% CI 13% to 30%) of Australian CDKN2A mutation carriers would be diagnosed with melanoma by age 50 years, and 45% (95% CI 29% to 65%) and 52% (95% CI 37% to 69%), respectively, by age 80 years. Conclusions Contrary to the strong association between UV radiation exposure and melanoma risk for the general population, CDKN2A mutation carriers appear to have the same cumulative risk of melanoma irrespective of the ambient UV irradiance of the region in which they live.

Identification of new genetic susceptibility Loci for breast cancer through consideration of gene-environment interactions

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Explaining Variance in the Cumulus Mammographic Measures That Predict Breast Cancer Risk: A Twins and Sisters Study

Background: Mammographic density, the area of the mammographic image that appears white or bright, predicts breast cancer risk. We estimated the proportions of variance explained by questionnaire-measured breast cancer risk factors and by unmeasured residual familial factors. Methods: For 544 MZ and 339 DZ twin pairs and 1,558 non-twin sisters from 1,564 families, mammographic density was measured using the computer-assisted method Cumulus. We estimated associations using multilevel mixed-effects linear regression and studied familial aspects using a multivariate normal model. Results: The proportions of variance explained by age, body mass index (BMI), and other risk factors, respectively, were 4%, 1%, and 4% for dense area; 7%, 14%, and 4% for percent dense area; and 7%, 40%, and 1% for nondense area. Associations with dense area and percent dense area were in opposite directions than for nondense area. After adjusting for measured factors, the correlations of dense area with percent dense area and nondense area were 0.84 and −0.46, respectively. The MZ, DZ, and sister pair correlations were 0.59, 0.28, and 0.29 for dense area; 0.57, 0.30, and 0.28 for percent dense area; and 0.56, 0.27, and 0.28 for nondense area (SE = 0.02, 0.04, and 0.03, respectively). Conclusions: Under the classic twin model, 50% to 60% (SE = 5%) of the variance of mammographic density measures that predict breast cancer risk are due to undiscovered genetic factors, and the remainder to as yet unknown individual-specific, nongenetic factors. Impact: Much remains to be learnt about the genetic and environmental determinants of mammographic density. Cancer Epidemiol Biomarkers Prev; 22(12); 2395–403. ©2013 AACR.

The Consistency of MDL for Linear Regression Models With Increasing Signal-to-Noise Ratio

Recent work by Ding and Kay has demonstrated that the Bayesian information criterion (BIC) is an inconsistent estimator of model order in nested model selection as the noise variance τ*→ 0. Unfortunately, Ding and Kay have erroneously concluded that the minimum description length (MDL) principle also leads to inconsistent estimates of model order in this setting by equating BIC with MDL. This correspondence shows that only the earlier MDL criterion based on asymptotic assumptions has this problem, and proves that the new MDL linear regression criteria based on normalized maximum likelihood and Bayesian mixture codes satisfy the notion of consistency as τ*→ 0. The main result may be used as a basis to easily establish similar consistency results for other closely related information theoretic regression criteria.

Universal Models for the Exponential Distribution

This paper considers the problem of constructing information theoretic universal models for data distributed according to the exponential distribution. The universal models examined include the sequential normalized maximum likelihood (SNML) code, conditional normalized maximum likelihood (CNML) code, the minimum message length (MML) code, and the Bayes mixture code (BMC). The CNML code yields a codelength identical to the Bayesian mixture code, and within O(1) of the MML codelength, with suitable data driven priors.

A Probabilistic Approach to the Interpretation of Spoken Utterances

In this paper we describe Scusi? , the speech interpretation component of a spoken dialogue module designed for an autonomous robotic agent. Scusi? postulates and maintains multiple interpretations of the spoken discourse, and employs a probabilistic formalism to assess and rank hypotheses regarding the meaning of spoken utterances. These constituents in combination enable Scusi? to cope gracefully with ambiguity and speech recognition errors. The results of our evaluation are encouraging, yielding good interpretation performance for utterances of different types and lengths.

Global measures of peripheral blood-derived DNA methylation as a risk factor in the development of mature B-cell neoplasms

AIM To examine whether peripheral blood methylation is associated with risk of developing mature B-cell neoplasms (MBCNs). MATERIALS & METHODS We conducted a case-control study nested within a large prospective cohort. Peripheral blood was collected from healthy participants. Cases of MBCN were identified by linkage to cancer registries. Methylation was measured using the Infinium(®) HumanMethylation450. RESULTS During a median of 10.6-year follow-up, 438 MBCN cases were evaluated. Global hypomethylation was associated with increased risk of MBCN (odds ratio: 2.27, [95% CI: 1.59-3.25]). Within high CpG promoter regions, hypermethylation was associated with increased risk (odds ratio: 1.76 [95% CI: 1.25-2.48]). Promoter hypermethylation was observed in HOXA9 and CDH1 genes. CONCLUSION Aberrant global DNA methylation is detectable in peripheral blood collected years before diagnosis and is associated with increased risk of MBCN, suggesting changes to DNA methylation are an early event in MBCN development.

A Simple Sampler for the Horseshoe Estimator

In this note we derive a simple Bayesian sampler for linear regression with the horseshoe hierarchy. A new interpretation of the horseshoe model is presented, and extensions to logistic regression and alternative hierarchies, such as horseshoe+, are discussed. Due to the conjugacy of the proposed hierarchy, Chibs algorithm may be used to easily compute the marginal likelihood of the model.