We executed a genome-wide association scan for age-related macular degeneration (AMD) in 2,157 cases and 1,150 controls. Our results validate AMD susceptibility loci near CFH (P < 10 −75), ARMS2 (P < 10 −59), C2/CFB (P < 10 −20), C3 (P < 10 −9 ), and CFI (P < 10 −6). We compared our top findings with the Tufts/Massachusetts General Hospital genome-wide association study of advanced AMD (821 cases, 1,709 controls) and genotyped 30 promising markers in additional individuals (up to 7,749 cases and 4,625 controls). With these data, we identified a susceptibility locus near TIMP3 (overall P = 1.1 × 10), a metalloproteinase involved in degradation of the extracellular matrix and previously implicated in early-onset maculopathy. In addition, our data revealed strong association signals with alleles at two loci (LIPC, P = 1.3 × 10 −7; CETP, P = 7.4 × 10 −7 ) that were previously associated with high-density lipoprotein cholesterol (HDL-c) levels in blood. Consistent with the hypothesis that HDL metabolism is associated with AMD pathogenesis, we also observed association with AMD of HDL-c-associated alleles near LPL (P = 3.0 × 10 −3) and ABCA1 (P = 5.6 × 10 −4). Multilocus analysis including all susceptibility loci showed that 329 of 331 individuals (99%) with the highest-risk genotypes were cases, and 85% of these had advanced AMD. Our studies extend the catalog of AMD associated loci, help identify individuals at high risk of disease, and provide clues about underlying cellular pathways that should eventually lead to new therapies.genome-wide association study | single nucleotide polymorphism A ge-related macular degeneration (AMD) is a progressive neurodegenerative disease and a common cause of blindness in the elderly population, particularly in developed countries (1). The disease affects primarily the macular region of the retina, which is necessary for sharp central vision. An early hallmark of AMD is the appearance of drusen, which are extracellular deposits of proteins and lipids under the retinal pigment epithelium (RPE). As the disease progresses, drusen grow in size and number. In advanced stages of AMD, atrophy of the RPE (geographic atrophy) and/or development of new blood vessels (neovascularization) result in death of photoreceptors and central vision loss.

On the basis of genomewide linkage studies of families affected with age-related maculopathy (ARM), we previously identified a significant linkage peak on 10q26, which has been independently replicated by several groups. We performed a focused SNP genotyping study of our families and an additional control cohort. We identified a strong association signal overlying three genes, PLEKHA1, LOC387715, and PRSS11. All nonsynonymous SNPs in this critical region were genotyped, yielding a highly significant association (P < .00001) between PLEKHA1/LOC387715 and ARM. Although it is difficult to determine statistically which of these two genes is most important, SNPs in PLEKHA1 are more likely to account for the linkage signal in this region than are SNPs in LOC387715; thus, this gene and its alleles are implicated as an important risk factor for ARM. We also found weaker evidence supporting the possible involvement of the GRK5/RGS10 locus in ARM. These associations appear to be independent of the association of ARM with the Y402H allele of complement factor H, which has previously been reported as a major susceptibility factor for ARM. The combination of our analyses strongly implicates PLEKHA1/LOC387715 as primarily responsible for the evidence of linkage of ARM to the 10q26 locus and as a major contributor to ARM susceptibility. The association of either a single or a double copy of the high-risk allele within the PLEKHA1/LOC387715 locus accounts for an odds ratio of 5.0 (95% confidence interval 3.2-7.9) for ARM and a population attributable risk as high as 57%.

Recent successful discoveries of potentially causal single nucleotide polymorphisms (SNPs) for complex diseases hold great promise, and commercialization of genomics in personalized medicine has already begun. The hope is that genetic testing will benefit patients and their families, and encourage positive lifestyle changes and guide clinical decisions. However, for many complex diseases, it is arguable whether the era of genomics in personalized medicine is here yet. We focus on the clinical validity of genetic testing with an emphasis on two popular statistical methods for evaluating markers. The two methods, logistic regression and receiver operating characteristic (ROC) curve analysis, are applied to our age-related macular degeneration dataset. By using an additive model of the CFH, LOC387715, and C2 variants, the odds ratios are 2.9, 3.4, and 0.4, with p-values of 10−13, 10−13, and 10−3, respectively. The area under the ROC curve (AUC) is 0.79, but assuming prevalences of 15%, 5.5%, and 1.5% (which are realistic for age groups 80 y, 65 y, and 40 y and older, respectively), only 30%, 12%, and 3% of the group classified as high risk are cases. Additionally, we present examples for four other diseases for which strongly associated variants have been discovered. In type 2 diabetes, our classification model of 12 SNPs has an AUC of only 0.64, and two SNPs achieve an AUC of only 0.56 for prostate cancer. Nine SNPs were not sufficient to improve the discrimination power over that of nongenetic predictors for risk of cardiovascular events. Finally, in Crohn's disease, a model of five SNPs, one with a quite low odds ratio of 0.26, has an AUC of only 0.66. Our analyses and examples show that strong association, although very valuable for establishing etiological hypotheses, does not guarantee effective discrimination between cases and controls. The scientific community should be cautious to avoid overstating the value of association findings in terms of personalized medicine before their time.

Background Preeclampsia is a pregnancy-specific disorder that remains a leading cause of maternal, fetal and neonatal morbidity and mortality, and is associated with risk for future cardiovascular disease. There are no reliable predictors, specific preventative measures or treatments other than delivery. A widely-held view is that the antecedents of preeclampsia lie with impaired placentation in early pregnancy. Accordingly, we hypothesized dysregulation of global gene expression in first trimester placentas of women who later manifested preeclampsia. Methods Surplus chorionic villus sampling (CVS) tissues were collected at 10–12 weeks gestation in 160 patients with singleton fetuses. Four patients developed preeclampsia, and their banked CVS specimens were matched to 8 control samples from patients with unaffected pregnancies. Affymetrix HG-U133 Plus 2.0 GeneChips were utilized for microarray analysis. Naïve Bayes prediction modeling and pathway analysis were conducted. qRT-PCR examined three of the dysregulated genes. Results Thirty-six differentially expressed genes were identified in the preeclampsia placentas. qRT-PCR verified the microarray analysis. Thirty-one genes were down-regulated. Many were related to inflammation/immunoregulation and cell motility. Decidual gene dysregulation was prominent. No evidence was found for alterations in hypoxia and oxidative stress regulated genes. Conclusions To our knowledge, this is the first study to show dysregulation of gene expression in the early placentas of women ~6 months before developing preeclampsia, thereby reinforcing a placental origin of the disorder. We hypothesize that placentation in preeclampsia is compromised in the first trimester by maternal and fetal immune dysregulation, abnormal decidualization, or both, thereby impairing trophoblast invasion. Several of the genes provide potential targets for the development of clinical biomarkers in maternal blood during the first trimester. Supplementary materials are available for this article via the publisher’s online edition.

Objective: The objective of this study was to provide insight into the molecular mechanisms of acute ischemic cerebrovascular syndrome (AICS) through gene expression profiling and pathway analysis. Methods:Peripheral whole blood samples were collected from 39 MRI-diagnosed patients with AICS and 25 nonstroke control subjects Ն18 years of age. Total RNA was extracted from whole blood stabilized in Paxgene RNA tubes, amplified, and hybridized to Illumina HumanRef-8v2 bead chips. Gene expression was compared in a univariate manner between stroke patients and control subjects using t test in GeneSpring. The significant genes were tested in a logistic regression model controlling for age, hypertension, and dyslipidemia. Inflation of type 1 error was corrected by Bonferroni and Ingenuity Systems Pathway analysis was performed. Validation was performed by QRT-PCR using Taqman gene expression assays.