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Genomic Search for Susceptibility to Alzheimer Disease

National Institute on Aging (NIA)
During the last twenty years genetic studies of familial early onset Alzheimer’s Disease (AD) have demonstrated that mutations in three genes cause AD via a common biochemical pathway involving Aβ metabolism. Studies of late onset AD (LOAD) have implicated genotype at the apolipoprotein E (APOE) locus as a major risk factor that also acts via an Aβ-dependent mechanism. However, only 50% of LOAD cases carry a risk allele at the APOE locus. The goal of this study is to combine quantitative trait locus (QTL) studies of biochemical measures in cerebrospinal fluid and case control data to identify and validate novel genetic risk factors for LOAD.  We use publicly available existing genome-wide associate study (GWAS) data in case control datasets and newly acquired GWAS data (through the AD Genetics Consortium (ADGC)) in samples with biomarker measurements to identify SNPs/genes that influence risk for LOAD via an Aβ-dependent mechanism. GWAS data in the Washington University/University of Washington (WU/UW) biomarker datasets are generated as part of the first phase of genotyping by the ADGC. GWAS data for the AD Neuroimaging Initiative (ADNI) series and from several case control datasets are in hand (approx. 3000 cases and 3000 controls).  The aims of this study are 1) test in the WU/UW CSF series for genetic factors on chromosome 10 and elsewhere in the genome that influence CSF Aβ-levels; 2) try to replicate these findings in an independent series with CSF biomarker measurements, collected by the ADNI consortium; and 3) compare our findings in the CSF series with the results of a combined GWAS dataset in AD cases and controls. This will allow us to identify the putative AD genes that influence risk by an Aβ-dependent mechanism, facilitating follow-up mechanistic studies to confirm the functional effects of these genes on Ass metabolism and AD risk. The use of case-control and endophenotype measures in CSF provides a powerful and novel approach to the genetics of LOAD.

Identification of Functional Alleles that Influence Cerebrospinal Fluid Levels of A-beta and Risk for Alzheimer’s Disease

American Health Assistance Foundation
With the exception of the apolipoprotein E ε4 allele (APOE ε4), no consistently replicated genetic risk factors for late-onset Alzheimer’s disease (LOAD) have been successfully identified. This lack of success is likely due in part to insufficient sample sizes and heterogeneity in case-control samples. We have developed an alternative approach, which uses CSF amyloid beta (Aβ) levels as endophenotypes for genetic studies of Alzheimer’s disease (AD). Aβ fragments are normal products of amyloid precursor protein (APP) processing and can be detected in the cerebrospinal fluid (CSF). It has been hypothesized that the aggregation of Aβ into insoluble plaques in the brain is a central feature of AD pathogenesis (Hardy and Selkoe 2002). CSF Aβ levels have also been shown to correlate with disease status and severity and are promising biomarkers for AD (Sunderland et al. 2006). This novel approach overcomes the problem of heterogeneity and allows for the use of quantitative statistical methods, increasing power to detect genetic association. Using this approach we have identified single nucleotide polymorphisms (SNPs) in LOAD candidate genes which are associated with CSF Aβ levels. We hypothesize that some of these SNPs will exhibit replicable association, thus elucidating pathways which regulate CSF Aβ levels and identifying novel genetic risk factors for AD. Our goal is to identify SNPs from our preliminary data that show replicable association in additional, independent CSF and case-control series and characterize the functional variants that drive this association.

Alzheimer’s Disease Research Center (ADRC) – Genetics Core

National Institute on Aging (NIA)
The Genetics Core will screen all participants in the ADRC Clinical Core for the known genetics causes and risk factors for dementia.

Read more on ADRC website

Healthy Aging & Senile Dementia

National Institute on Aging (NIA)
The program project, Healthy Aging and Senile Dementia (HASD), focuses on the clinical, psychometric, and neuropathologic correlates of dementia of the Alzheimer type (DAT) in comparison with healthy aging with a thrust addressing preclinical Alzheimer’s disease. The project in our lab, “Sequence variation in genes for biomarker proteins and age at onset of Alzheimer’s Disease” uses CSF proteins as intermediate traits, or endophenotypes, to identify novel genetic risk factors for late onset DAT.

Genetics Consortium for Late Onset Alzheimer’s Disease

National Institute on Aging (NIA)
Genetic factors contribute to the risk for Alzheimer’s disease (AD) with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer’s disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer’s disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer’s Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer’s disease.

Read more on NIH website

Dominantly Inherited Alzheimer Network

National Institute on Aging (NIA)
This project studies dominantly inherited Alzheimer’s disease (AD), which represents less than 1% of all cases of AD and is an attractive model for study because the responsible mutations have known biochemical consequences that are believed to underlie the pathological basis of the disorder.

Read more on DIAN website

Collaborative Study on the Genetics of Alcoholism (COGA)

National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Since 1989, pedigrees densely affected with alcoholism (DSM-III-R) have been ascertained at six sites (SUNY Downstate Health Sciences Center, University of Connecticut, Indiana University, Washington University, University of Iowa, and The University of California at San Diego). Diagnoses of alcohol dependence according to several diagnostic systems (e.g., DSM-III-R, Feighner, ICD-10) are made based on examination of medical records and direct assessment using the Semi-Structured Assessment for Genetics of Alcoholism (SSAGA). Nuclear and extended pedigrees containing at least two alcohol-dependent first-degree relatives in addition to an alcohol dependent proband (with all affected individuals meeting both DSM-IIIR and Feighner criteria) have been ascertained.   “Clinical data,” designating anonymous data on family structure, age, sex, vital status, psychopathology, diagnosis, other clinically relevant information, are stored, maintained, and distributed by Washington University. “Research data,” consist of data on blood biochemistry and psychological test performance, which are stored, maintained, and distributed by Washington University, and brain electrophysiological data, which are stored, maintained, and distributed by SUNY. “Genetic analysis data,” consisting of marker genotypes, along with results of previous genetic analyses of COGA data, are stored, maintained, and distributed by Washington University. “Biomaterials,” consisting of lymphoblastoid cell lines and DNA from participating subjects are stored, maintained, and distributed by Rutgers University.

Read more on NIAAA website

The Genetics of Vulnerability to Nicotine Addictions

National Institute on Drug Abuse (NIDA)
Our genetic epidemiologic collaboration seeks to identify genes that influence risks for heavy smoking and nicotine dependence. QTL linkage analyses using 10cM microsatellite marker genome scan data have identified a strong linkage signal in both Australian and Finnish sibships, for our primary heaviness-of-smoking (HoS) phenotype, on Chr 22q12 (in updated analyses, multi-point LODs of 3.05 and 3.21 respectively). Genotyping of two additional microsatellite markers flanking the linkage peaks, in both Finnish and Australian genome-scan samples, yielded a combined multipoint LOD of 5.21 (genome-wide significance p=.006) at 25cM. This project seeks to identify the gene or genes at 22q12 which are contributing to HoS using the efficiency of existing data and DNAs and large informative samples, with complementary strengths, that were drawn from the same populations in which the original linkage signal was obtained. This goal will be achieved by (i) conducting a genetic association study, with high-throughput genotyping of 1436 SNPs across a 1-LOD support interval within our primary linkage region in 1000 unrelated Finnish male heavy smokers (ATBC chemoprevention trial participants who smoked 40+ cigarettes per day) and 1000 Finnish male population controls (Health2000 participants) (Aim 1: ‘Finnish series I’; ‘stage 1 genotyping’); (ii) conducting follow-up genotyping of SNPs found nominally significant at stage 1 in two separate series: (a) an additional 2000 unrelated heavy smokers (who smoked 30+ cigarettes per day) and 2000 population controls (‘Finnish series II’); and (b) a family-based series of 4429 siblings who are smokers (55 percent female) from a community-based series of Australian large sibships (‘BIGSIB’ sample) ascertained solely on the basis of large sibship size from the Australian twin panel, from the same cohorts as the Australian linkage families. Combining Finnish series I and II will ensure adequate power to detect quite modest QTL effect sizes; confirmation of nominal stage 1 associations in the Australian series will ensure that we are able to detect genetic effects that may be only modest in male long-term smokers, but more potent in female smokers. For genes with SNPs confirmed to be associated with HoS, we will conduct DNA sequencing in individuals with high-risk and low-risk haplotypes, selected from the original Finnish and Australian linkage families, to attempt to identify variants that might be functional, and will characterize using family-based association approaches the effects of genetic variants (or haplotypes) thus identified on cigarette-smoking and related behaviors (including correlated substance use and other psychiatric disorders), using the original Finnish NAG families and the Australian BIGSIB sample. The importance of genetic influences on risk of becoming a long-term heavy smoker has been known for many years. Understanding the genetic mechanisms by which some individuals are at increased risk should ultimately lead to improved therapies to assist smoking cessation.

The Collaborative Genetic Study of Nicotine Dependence (COGEND)

National Cancer Institute (NCI)
COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies.

Read more on NCBI website