Epidemiology of Brain and Other CNS Tumors.

PURPOSE OF REVIEW: Brain and other central nervous system (CNS) tumors, while rare, cause significant morbidity and mortality across all ages. This article summarizes the current state of the knowledge on the epidemiology of brain and other CNS tumors. RECENT FINDINGS: For childhood and adolescent brain and other CNS tumors, high birth weight, non-chromosomal structural birth defects and higher socioeconomic position were shown to be risk factors. For adults, increased leukocyte telomere length, proportion of European ancestry, higher socioeconomic position, and HLA haplotypes increase risk of malignant brain tumors, while immune factors decrease risk. Although no risk factor accounting for a large proportion of brain and other CNS tumors has been discovered, the use of high throughput omics approaches and improved detection/measurement of environmental exposures will help us refine our current understanding of these factors and discover novel risk factors for this disease

An independently validated nomogram for isocitrate dehydrogenase-wild-type glioblastoma patient survival.

BackgroundIn 2016, the World Health Organization reclassified the definition of glioblastoma (GBM), dividing these tumors into isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant GBM, where the vast majority of GBMs are IDH-wild-type. Nomograms are useful tools for individualized estimation of survival. This study aimed to develop and independently validate a nomogram for IDH-wild-type patients with newly diagnosed GBM.MethodsData were obtained from newly diagnosed GBM patients from the Ohio Brain Tumor Study (OBTS) and the University of California San Francisco (UCSF) for diagnosis years 2007-2017 with the following variables: age at diagnosis, sex, extent of resection, concurrent radiation/temozolomide (TMZ) status, Karnofsky Performance Status (KPS), O6-methylguanine-DNA methyltransferase (MGMT) methylation status, and IDH mutation status. Survival was assessed using Cox proportional hazards regression, random survival forests, and recursive partitioning analysis, with adjustment for known prognostic factors. The models were developed using the OBTS data and independently validated using the UCSF data. Models were internally validated using 10-fold cross-validation and externally validated by plotting calibration curves.ResultsA final nomogram was validated for IDH-wild-type newly diagnosed GBM. Factors that increased the probability of survival included younger age at diagnosis, female sex, having gross total resection, having concurrent radiation/TMZ, having a high KPS, and having MGMT methylation.ConclusionsA nomogram that calculates individualized survival probabilities for IDH-wild-type patients with newly diagnosed GBM could be useful to physicians for counseling patients regarding treatment decisions and optimizing therapeutic approaches. Free software for implementing this nomogram is provided: https://gcioffi.shinyapps.io/Nomogram_For_IDH_Wildtype_GBM_H_Gittleman/

APOE and FABP2 Polymorphisms and History of Myocardial Infarction, Stroke, Diabetes, and Gallbladder Disease

Dysfunctional lipid metabolism plays a central role in pathogenesis of major chronic diseases, and genetic factors are important determinants of individual lipid profiles. We analyzed the associations of two well-established functional polymorphisms (FABP2 A54T and APOE isoforms) with past and family histories of 1492 population samples. FABP2-T54 allele was associated with an increased risk of past history of myocardial infarction (odds ratio (OR) = 1.51). Likewise, the subjects with APOE4, compared with E2 and E3, had a significantly increased risk of past history myocardial infarction (OR = 1.89). The OR associated with APOE4 was specifically increased in women for past history of myocardial infarction but decreased for gallstone disease. Interactions between gender and APOE isoforms were also significant or marginally significant for these two conditions. FABP2-T54 allele may be a potential genetic marker for myocardial infarction, and APOE4 may exert sex-dependent effects on myocardial infarction and gallbladder disease

Replication of GWAS “Hits” by Race for Breast and Prostate Cancers in European Americans and African Americans

In this study, we assessed association of genome-wide association studies (GWAS) “hits” by race with adjustment for potential population stratification (PS) in two large, diverse study populations; the Carolina Breast Cancer Study (CBCS; N total = 3693 individuals) and the University of Pennsylvania Study of Clinical Outcomes, Risk, and Ethnicity (SCORE; N total = 1135 individuals). In both study populations, 136 ancestry information markers and GWAS “hits” (CBCS: FGFR2, 8q24; SCORE: JAZF1, MSMB, 8q24) were genotyped. Principal component analysis was used to assess ancestral differences by race. Multivariable unconditional logistic regression was used to assess differences in cancer risk with and without adjustment for the first ancestral principal component (PC1) and for an interaction effect between PC1 and the GWAS “hit” (SNP) of interest. PC1 explained 53.7% of the variance for CBCS and 49.5% of the variance for SCORE. European Americans and African Americans were similar in their ancestral structure between CBCS and SCORE and cases and controls were well matched by ancestry. In the CBCS European Americans, 9/11 SNPs were significant after PC1 adjustment, but after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs1219648 in FGFR2); for CBCS African Americans, 6/11 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, all six SNPs remained significant and an additional SNP now became significant. In the SCORE European Americans, 0/9 SNPs were significant after PC1 adjustment and no changes were seen after additional adjustment for the PC1 by SNP interaction effect; for SCORE African Americans, 2/9 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs16901979 at 8q24). We show that genetic associations by race are modified by interaction between individual SNPs and PS

Analysis of gene × environment interactions in sibships using mixed models

BACKGROUND: Gene × environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to assess gene × environment interactions with respect to systolic blood pressure on sibships adjusting for repeated measures and hierarchical nesting structures. A data set containing 410 sibships from the Framingham Heart Study offspring cohort (part of the Genetic Analysis Workshop 13 data) was used for all analyses. Three mixed gene × environment models, all adjusting for repeated measurement and varying levels of nesting, were compared for precision of estimates: 1) all sibships with adjustment for two levels of nesting (sibs within sibships and sibs within pedigrees), 2) all sibships with adjustment for one level of nesting (sibs within sibships), and 3) 100 data sets containing random draws of one sibship per extended pedigree adjusting for one level of nesting. RESULTS: The main effects were: gender, baseline age, body mass index (BMI), hypertensive treatment, cigarettes per day, grams of alcohol per day, and marker GATA48G07A. The interaction fixed effects were: baseline age by gender, baseline age by cigarettes per day, baseline age by hypertensive treatment, baseline age by BMI, hypertensive treatment by BMI, and baseline age by marker GATA48G07A. The estimates for all three nesting techniques were not widely discrepant, but precision of estimates and determination of significant effects did change with the change in adjustment for nesting. CONCLUSION: Our results show the importance of the adjustment for all levels of hierarchical nesting of sibs in the presence of repeated measures

Susceptibility scoring in family-based association testing

BACKGROUND: Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a susceptibility residual method of adjustment for covariates. RESULTS: Through simulation, we show that environmental adjustments that down-weight persons who are "destined" to be affected decrease the power to detect genetic association. We used the residual adjusted method on the Framingham Heart Study offspring data, provided for Genetic Analysis Workshop 13, and got mixed results. CONCLUSION: When the genetic effect and environmental effects are independent, a susceptibility residual method of adjustment for environmental covariates reduces the power of the association test. Further study is necessary to determine if residual adjustment is appropriate in more complex disease models

Proteins Inform Survival-Based Differences in Patients with Glioblastoma

Background: Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery. Methods: For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography-mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months). Results: Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset. Conclusions: These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets

Influence of County-Level Geographic/Ancestral Origin on Glioma Incidence and Outcomes in Us Hispanics

BACKGROUND: Glioma incidence is 25% lower in Hispanics than White non-Hispanics. The US Hispanic population is diverse, and registry-based analyses may mask incidence differences associated with geographic/ancestral origins. METHODS: County-level glioma incidence data in Hispanics were retrieved from the Central Brain Tumor Registry of the United States. American Community Survey data were used to determine the county-level proportion of the Hispanic population of Mexican/Central American and Caribbean origins. Age-adjusted incidence rate ratios and incidence rate ratios (IRRs) quantified the glioma incidence differences across groups. State-level estimates of admixture in Hispanics were obtained from published 23andMe data. RESULTS: Compared to predominantly Caribbean-origin counties, predominantly Mexican/Central American-origin counties had lower age-adjusted risks of glioma (IRR = 0.83; P \u3c 0.0001), glioblastoma (IRR = 0.86; P \u3c 0.0001), diffuse/anaplastic astrocytoma (IRR = 0.78; P \u3c 0.0001), oligodendroglioma (IRR = 0.82; P \u3c 0.0001), ependymoma (IRR = 0.88; P = 0.012), and pilocytic astrocytoma (IRR = 0.76; P \u3c 0.0001). Associations were consistent in children and adults and using more granular geographic regions. Despite having lower glioma incidence, Hispanic glioblastoma patients from predominantly Mexican/Central American-origin counties had poorer survival than Hispanics living in predominantly Caribbean-origin counties. Incidence and survival differences could be partially explained by state-level estimates of European admixture in Hispanics with European admixture associated with higher incidence and improved survival. CONCLUSIONS: Glioma incidence and outcomes differ in association with the geographic origins of Hispanic communities, with counties of predominantly Mexican/Central American origin at significantly reduced risk and those of Caribbean origin at comparatively greater risk. Although typically classified as a single ethnic group, appreciating the cultural, socioeconomic, and genetic diversity of Hispanics can advance cancer disparities research