V. Shane Pankratz

Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease.

We undertook a two-stage genome-wide association study (GWAS) of Alzheimers disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 × 10−157) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 × 10−9) and 5′ to the PICALM gene (rs3851179, P = 1.9 × 10−8). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimers disease in the combined dataset (rs11136000, P = 8.5 × 10−10, odds ratio = 0.86; rs3851179, P = 1.3 × 10−9, odds ratio = 0.86).

Letter abstract - Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's Disease

We undertook a two-stage genome-wide association study (GWAS) of Alzheimers disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 × 10−157) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 × 10−9) and 5′ to the PICALM gene (rs3851179, P = 1.9 × 10−8). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimers disease in the combined dataset (rs11136000, P = 8.5 × 10−10, odds ratio = 0.86; rs3851179, P = 1.3 × 10−9, odds ratio = 0.86).

Genome-wide Analysis of Genetic Loci Associated With Alzheimer Disease

CONTEXT Genome-wide association studies (GWAS) have recently identified CLU, PICALM, and CR1 as novel genes for late-onset Alzheimer disease (AD). OBJECTIVES To identify and strengthen additional loci associated with AD and confirm these in an independent sample and to examine the contribution of recently identified genes to AD risk prediction in a 3-stage analysis of new and previously published GWAS on more than 35,000 persons (8371 AD cases). DESIGN, SETTING, AND PARTICIPANTS In stage 1, we identified strong genetic associations (P < 10(-3)) in a sample of 3006 AD cases and 14,642 controls by combining new data from the population-based Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (1367 AD cases [973 incident]) with previously reported results from the Translational Genomics Research Institute and the Mayo AD GWAS. We identified 2708 single-nucleotide polymorphisms (SNPs) with P < 10(-3). In stage 2, we pooled results for these SNPs with the European AD Initiative (2032 cases and 5328 controls) to identify 38 SNPs (10 loci) with P < 10(-5). In stage 3, we combined data for these 10 loci with data from the Genetic and Environmental Risk in AD consortium (3333 cases and 6995 controls) to identify 4 SNPs with P < 1.7x10(-8). These 4 SNPs were replicated in an independent Spanish sample (1140 AD cases and 1209 controls). Genome-wide association analyses were completed in 2007-2008 and the meta-analyses and replication in 2009. MAIN OUTCOME MEASURE Presence of Alzheimer disease. RESULTS Two loci were identified to have genome-wide significance for the first time: rs744373 near BIN1 (odds ratio [OR],1.13; 95% confidence interval [CI],1.06-1.21 per copy of the minor allele; P = 1.59x10(-11)) and rs597668 near EXOC3L2/BLOC1S3/MARK4 (OR, 1.18; 95% CI, 1.07-1.29; P = 6.45x10(-9)). Associations of these 2 loci plus the previously identified loci CLU and PICALM with AD were confirmed in the Spanish sample (P < .05). However, although CLU and PICALM were confirmed to be associated with AD in this independent sample, they did not improve the ability of a model that included age, sex, and APOE to predict incident AD (improvement in area under the receiver operating characteristic curve from 0.847 to 0.849 in the Rotterdam Study and 0.702 to 0.705 in the Cardiovascular Health Study). CONCLUSIONS Two genetic loci for AD were found for the first time to reach genome-wide statistical significance. These findings were replicated in an independent population. Two recently reported associations were also confirmed. These loci did not improve AD risk prediction. While not clinically useful, they may implicate biological pathways useful for future research.

Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

Background Late Onset Alzheimers disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimers disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches.

Penalized Survival Models and Frailty

Interest in the use of random effects in the survival analysis setting has been increasing. However, the computational complexity of such frailty models has limited their general use. Although fitting frailty models has traditionally been difficult, standard algorithms for fitting Cox semiparametric and parametric regression models can be readily extended to include penalized regression. We demonstrate that solutions for gamma shared frailty models can be obtained exactly via penalized estimation. Similarly, Gaussian frailty models are closely linked to penalized models. Fitting frailty models with penalized likelihoods can be made quite efficient by taking advantage of computational methods available for penalized models. We have implemented penalized regression for the coxph function of S-Plus and illustrate the algorithms with examples using the Cox model.

GENETIC VARIATION IN PCDH11X IS ASSOCIATED WITH SUSCEPTIBILITY TO LATE ONSET ALZHEIMER'S DISEASE

By analyzing late-onset Alzheimers disease (LOAD) in a genome-wide association study (313,504 SNPs, three series, 844 cases and 1,255 controls) and evaluating the 25 SNPs with the most significant allelic association in four additional series (1,547 cases and 1,209 controls), we identified a SNP (rs5984894) on Xq21.3 in PCDH11X that is strongly associated with LOAD in individuals of European descent from the United States. Analysis of rs5984894 by multivariable logistic regression adjusted for sex gave global P values of 5.7 × 10−5 in stage 1, 4.8 × 10−6 in stage 2 and 3.9 × 10−12 in the combined data. Odds ratios were 1.75 (95% CI = 1.42–2.16) for female homozygotes (P = 2.0 × 10−7) and 1.26 (95% CI = 1.05–1.51) for female heterozygotes (P = 0.01) compared to female noncarriers. For male hemizygotes (P = 0.07) compared to male noncarriers, the odds ratio was 1.18 (95% CI = 0.99–1.41).

Physical Exercise, Aging, and Mild Cognitive Impairment: A Population-Based Study

BACKGROUND Physical exercise is associated with decreased risk of dementia and Alzheimer disease. OBJECTIVE To investigate whether physical exercise is associated with decreased risk of mild cognitive impairment (MCI). DESIGN Population-based case-control study. SETTING The Mayo Clinic Study of Aging, an ongoing population-based cohort study in Olmsted County, Minnesota. PARTICIPANTS A total of 1324 subjects without dementia who completed a Physical Exercise Questionnaire. MAIN OUTCOME MEASURES An expert consensus panel classified each subject as having normal cognition or MCI based on published criteria. RESULTS We compared the frequency of physical exercise among 198 subjects with MCI with that among 1126 subjects with normal cognition and adjusted the analyses for age, sex, years of education, medical comorbidity, and depression. The odds ratios for any frequency of moderate exercise were 0.61 (95% confidence interval, 0.43-0.88; P = .008) for midlife (age range, 50-65 years) and 0.68 (95% confidence interval, 0.49-0.93; P = .02) for late life. The findings were consistent among men and women. Light exercise and vigorous exercise were not significantly associated with decreased risk of MCI. CONCLUSION In this population-based case-control study, any frequency of moderate exercise performed in midlife or late life was associated with a reduced odds of having MCI.

Inherited Mutations in 17 Breast Cancer Susceptibility Genes Among a Large Triple-Negative Breast Cancer Cohort Unselected for Family History of Breast Cancer

PURPOSE Recent advances in DNA sequencing have led to the development of breast cancer susceptibility gene panels for germline genetic testing of patients. We assessed the frequency of mutations in 17 predisposition genes, including BRCA1 and BRCA2, in a large cohort of patients with triple-negative breast cancer (TNBC) unselected for family history of breast or ovarian cancer to determine the utility of germline genetic testing for those with TNBC. PATIENTS AND METHODS Patients with TNBC (N = 1,824) unselected for family history of breast or ovarian cancer were recruited through 12 studies, and germline DNA was sequenced to identify mutations. RESULTS Deleterious mutations were identified in 14.6% of all patients. Of these, 11.2% had mutations in the BRCA1 (8.5%) and BRCA2 (2.7%) genes. Deleterious mutations in 15 other predisposition genes were detected in 3.7% of patients, with the majority observed in genes involved in homologous recombination, including PALB2 (1.2%) and BARD1, RAD51D, RAD51C, and BRIP1 (0.3% to 0.5%). Patients with TNBC with mutations were diagnosed at an earlier age (P < .001) and had higher-grade tumors (P = .01) than those without mutations. CONCLUSION Deleterious mutations in predisposition genes are present at high frequency in patients with TNBC unselected for family history of cancer. Mutation prevalence estimates suggest that patients with TNBC, regardless of age at diagnosis or family history of cancer, should be considered for germline genetic testing of BRCA1 and BRCA2. Although mutations in other predisposition genes are observed among patients with TNBC, better cancer risk estimates are needed before these mutations are used for clinical risk assessment in relatives.

Mammographic density, breast cancer risk and risk prediction

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individuals probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models.

Replication of CLU, CR1, and PICALM Associations With Alzheimer Disease

OBJECTIVE To test for replication of the association between variants in the CLU, CR1, and PICALM genes with Alzheimer disease. DESIGN Follow-up case-control association study. SETTING The Mayo Clinics at Jacksonville, Florida, and Rochester, Minnesota. PARTICIPANTS Community-based patients of European descent with late-onset Alzheimer disease (LOAD) and controls without dementia who were seen at the Mayo clinics, and autopsy-confirmed cases and controls whose pathology was evaluated at the Mayo Clinic in Jacksonville. Additional samples were obtained from the National Cell Repository for Alzheimer Disease (NCRAD). A total of 1829 LOAD cases and 2576 controls were analyzed. INTERVENTIONS The most significant single-nucleotide polymorphisms in CLU (rs11136000), CR1 (rs3818361), and PICALM (rs3851179) were tested for allelic association with LOAD. Main Outcome Measure Clinical or pathology-confirmed diagnosis of LOAD. RESULTS Odds ratios for CLU, CR1, and PICALM were 0.82, 1.15, and 0.80, respectively, comparable in direction and magnitude with those originally reported. P values were 8.6 x 10(-5), .014, and 1.3 x 10(-5), respectively; they remain significant even after Bonferroni correction for the 3 single-nucleotide polymorphisms tested. CONCLUSION These results show near-perfect replication and provide the first additional evidence that CLU, CR1, and PICALM are associated with the risk of LOAD.