Citations

Abstract The etiology of ovarian cancer is poorly understood but there is clearly a heritable component. Efforts to identify susceptibility alleles rarely consider interactions among alleles or their joint effects because it quickly becomes computationally intractable. In this study, we sought to identify multi-SNP effects jointly with a pathway-based analysis (GSEA-SNP) of 1,952 EOC cases and 2,042 frequency-matched controls genotyped with the Illumina 610K array. All subjects were self-reported non-Hispanic non-Jewish Caucasians, with SNP and sample call rates > 95%. Subjects with ambiguous gender, unresolved identical genotypes and < 80% European ancestry were excluded. SNPs with MAF < 1% were excluded. Missing genotypes were inferred using Mach based on the HapMap CEU population. SNPs not within introns were annotated to genes within 100 bp. We retrieved the following databases of gene sets (GSs) from a compiled database, MsigDB: human chromosome and cytogenetic band, chemical and genetic perturbations, canonical pathways, microRNA binding targets, transcription factor targets (TFT), cancer gene neighborhood (CGN), Cancer modules and Gene Ontology. The GSEA-SNP approach calculates and rank orders the trend statistic for association between each SNP and EOC risk. The Enrichment Score (ES) estimates the overrepresentation of top-ranked SNPs for each GS; the statistical significance was estimated using 10,000 permutations. The ES was normalized according to the size of GS to yield Normalized Enrichment Score (NES). The false discovery (FDR) rate was estimated using NES to adjust for multiple hypothesis testing. A total of 5181 gene-sets were included in the analysis. When controlling the FDR at 15%, 14 of the GSs were highly enriched with association signals, including two chromosomal regions, 8q13 (p = 0.0055, FDR = 0.15) and 6p24 (p = 0.0012, FDR = 0.08). BIOCARTA_LYM_PATHWAY, a pathway related to cell adhesion and diapedesis of lymphocytes, was also significant (p = 0.0002, FDR = 0.12). A TFT GS, composed of genes with promoter regions around transcription start sites containing the motif GGCNRNWCTTYS, was associated with risk (p = 0.0004, FDR = 0.08). Currently, no known transcription factors bind to this computationally predicted motif. Molecular function of double stranded RNA binding was also enriched (p = 0.005, FDR = 0.10). The remaining enriched sets were CGN sets, for which the neighborhoods around the cancer genes were originally defined using correlation of gene expression from 4 large data sets of various cancer types. The enriched CGN included: CD48 (p = 0.011), CD53 (p = 0.009), CD97 (p = 0.011), INPP5D (p = 0.010), PTPN6 (p = 0.008), VAV1 (p = 0.011), ITGAL (p = 0.012), PTPRC (p = 0.012), and STAT6 (p = 0.010). In summary, these analyses detected biologically plausible GSs related to etiology of EOC, highlighting SNPs in core enrichment groups that were not identified using individual SNP tests. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4729. doi:10.1158/1538-7445.AM2011-4729

AbstractMutations in the all-trans retinoic acid (ATRA)–targeted ligand binding domain of PML-RARα (PRα/LBD+) have been implicated in the passive selection of ATRA-resistant acute promyelocytic leukemia clones leading to disease relapse. Among 45 relapse patients from the ATRA/chemotherapy arm of intergroup protocol C9710, 18 patients harbored PRα/LBD+ (40%), 7 of whom (39%) relapsed Off-ATRA selection pressure, suggesting a possible active role of PRα/LBD+. Of 41 relapse patients coanalyzed, 15 (37%) had FMS-related tyrosine kinase 3 internal tandem duplication mutations (FLT3-ITD+), which were differentially associated with PRα/LBD+ depending on ATRA treatment status at relapse: positively, On-ATRA; negatively, Off-ATRA. Thirteen of 21 patients (62%) had additional chromosome abnormalities (ACAs); all coanalyzed PRα/LBD mutant patients who relapsed off-ATRA (n = 5) had associated ACA. After relapse Off-ATRA, ACA and FLT3-ITD+ were negatively associated and were oppositely associated with presenting white blood count and PML-RARα type: ACA, low, L-isoform; FLT3-ITD+, high, S-isoform. These exploratory results suggest that differing PRα/LBD+ activities may interact with FLT3-ITD+ or ACA, that FLT3-ITD+ and ACA are associated with different intrinsic disease progression pathways manifest at relapse Off-ATRA, and that these different pathways may be short-circuited by ATRA-selectable defects at relapse On-ATRA. ACA and certain PRα/LBD+ were also associated with reduced postrelapse survival.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β‐amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau‐mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [ 18 F]‐fluorodeoxyglucose‐PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β‐amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU , CR1 , and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI‐like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease‐modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

BackgroundThe majority of studies relating amyloid pathology with brain volumes have been cross‐sectional. Apolipoprotein ɛ4 (APOE ɛ4), a genetic risk factor for Alzheimer's disease, is also known to be associated with hippocampal volume loss. No studies have considered the effects of amyloid pathology and APOE ɛ4 together on longitudinal volume loss.MethodsWe evaluated whether an abnormal level of cerebrospinal fluid beta‐amyloid (CSF Aβ) and APOE ɛ4 carrier status were independently associated with greater hippocampal volume loss over 1 year. We then assessed whether APOE ɛ4 status and CSF Aβ acted synergistically, testing the significance of an interaction term in the regression analysis. We included 297 participants: 77 cognitively normal, 144 with mild cognitive impairment (MCI), and 76 with Alzheimer's disease.ResultsAn abnormal CSF Aβ level was found to be associated with greater hippocampal volume loss over 1 year in each group. APOE ɛ4 was associated with hippocampal volume loss only in the cognitively normal and MCI groups. APOE ɛ4 carriers with abnormal CSF Aβ in the MCI group acted synergistically to produce disproportionately greater volume loss than noncarriers.ConclusionBaseline CSF Aβ predicts progression of hippocampal volume loss. APOE ɛ4 carrier status amplifies the degree of neurodegeneration in MCI. Understanding the effect of interactions between genetic risk and amyloid pathology will be important in clinical trials and our understanding of the disease process.

The widespread use of actigraphy has led to the recognition that a number of methodological issues have to be addressed to facilitate an increased acceptability of this relatively new method. These methodological issues include actigraph placement, reliability, and sensitivity, and the phenomenon known as the “first night effect.” Our findings have demonstrated that actigraphy is a reliable instrument for assessment of sleep and wakefulness. In addition, actigraph placement and reliability do not constitute a significant methodological problem as no differences were found in all of these studies. We have also observed no first-night effects associated with sleep-wake monitoring with actigraphy.

Decades of empirical observations have established the validity of actigraphy primarily in individuals without sleep disorders. Methodological problems encountered thus far coupled with the widespread use of actigraphy signal the need for concentrated efforts to establish a consensus regarding scoring procedures. Currently available scoring methods show less reliability in clinical populations. To address these issues two validation studies were conducted: one for individuals without sleep disorders and the other for patients diagnosed with insomnia. The results of these two studies using the Actigraph Data Analysis Software as the scoring method have shown that the described system is fairly precise. It can be used for actigraphs with different features and mode of operation and is applicable to individuals with insomnia. These findings corroborate previous research showing that actigraphy is a valid instrument for assessment of sleep and wakefulness.

Abstract Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered. Cancer Epidemiol Biomarkers Prev; 20(8); 1793–7. ©2011 AACR.

Abstract Background: Mitochondria contribute to oxidative stress, a phenomenon implicated in ovarian carcinogenesis. We hypothesized that inherited variants in mitochondrial-related genes influence epithelial ovarian cancer (EOC) susceptibility. Methods: Through a multicenter study of 1,815 Caucasian EOC cases and 1,900 controls, we investigated associations between EOC risk and 128 single nucleotide polymorphisms (SNPs) from 22 genes/regions within the mitochondrial genome (mtDNA) and 2,839 nuclear-encoded SNPs localized to 138 genes involved in mitochondrial biogenesis (BIO, n = 35), steroid hormone metabolism (HOR, n = 13), and oxidative phosphorylation (OXP, n = 90) pathways. Unconditional logistic regression was used to estimate OR and 95% CI between genotype and case status. Overall significance of each gene and pathway was evaluated by using Fisher's method to combine SNP-level evidence. At the SNP level, we investigated whether lifetime ovulation, hormone replacement therapy (HRT), and cigarette smoking were confounders or modifiers of associations. Results: Interindividual variation involving BIO was most strongly associated with EOC risk (empirical P = 0.050), especially for NRF1, MTERF, PPARGC1A, ESRRA, and CAMK2D. Several SNP-level associations strengthened after adjustment for nongenetic factors, particularly for MTERF. Statistical interactions with cigarette smoking and HRT use were observed with MTERF and CAMK2D SNPs, respectively. Overall variation within mtDNA, HOR, and OXP was not statistically significant (empirical P > 0.10). Conclusion: We provide novel evidence to suggest that variants in mitochondrial biogenesis genes may influence EOC susceptibility. Impact: A deeper understanding of the complex mechanisms implicated in mitochondrial biogenesis and oxidative stress may aid in developing strategies to reduce morbidity and mortality from EOC. Cancer Epidemiol Biomarkers Prev; 20(6); 1131–45. ©2011 AACR.