Citations

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

ABSTRACT Community-dwellers aged ≥ 60 years enrolled in the Atahualpa Project underwent brain MRI and were interviewed with the Pittsburgh Sleep Quality Index. Of 290 participants, 94 (32%) had poor sleep quality and 143 (49%) had global cortical atrophy (GCA). In a logistic regression model (adjusted for demographics, cardiovascular risk factor, severe edentulism, symptoms of depression, the MoCA score, and neuroimaging signatures of cerebrovascular damage), poor sleep quality was associated with GCA (p=0.004). A multivariate probability model showed that the probability of moderate-to-severe GCA significantly increased in individuals with poor sleep quality aged ≥ 67 years. This study provides evidence for an association between poor sleep quality and GCA in older adults and the important interaction of age in this association.