Published familial relative risk (RR) estimates for Alzheimer's Disease (AD) typically focus on summary data from close relatives, rather than on complete family history for an individual. The risk estimates presented avoid common recall, recruitment, and ascertainment biases, and provide more individualized risk estimates based on a specific family history of AD. We use a population-based genealogy resource to estimate the risk for death from AD based on complete family history of death from AD. The Utah Population Data Base (UPDB), a computerized genealogical resource linked to state death certificates from 1904, was analyzed. Over 1 million individuals with at least 12 of their 14 immediate ancestors were analyzed. All individuals with specific family histories of AD were identified in the UPDB (probands) and the observed number of AD deaths among these probands was compared to the expected number of AD deaths using internal cohort-specific rates from Utah death certificates to obtain a RR estimate. We considered family history from first- to third-degree relatives, number of relatives affected, paternal versus maternal family history, and age at diagnosis. Significantly elevated RRs for AD mortality were observed based on the presence of any number of affected first-degree relatives; any number of affected second-degree relatives in the presence of at least 1 first-degree relative; and in the presence of at least 2 third-degree relatives, even in the absence of affected first- and second-degree relatives. There is evidence for increased risk via maternal versus paternal inheritance, and for higher risks for males than females given equivalent family history. This study provides unbiased, population-based estimates of AD risk based on an individual's family history for AD death. AD risk estimates derived from specific family history are as informative (or more so) and more economical than those estimated based on genotypes. Multiple family histories conferring 2-3 times increased risk for dying from AD are identified. Using detailed AD family history in the planning of screening, treatment, and monitoring opens additional avenues for implementation of more sound translational medicine practices, and decreasing morbidity and mortality in patients and their families.
Alzheimer's disease (AD) is the most common cause of dementia and AD risk clusters within families. Part of the familial aggregation of AD is accounted for by excess maternal vs. paternal inheritance, a pattern consistent with mitochondrial inheritance. The role of specific mitochondrial DNA (mtDNA) variants and haplogroups in AD risk is uncertain.We determined the complete mitochondrial genome sequence of 1007 participants in the Cache County Study on Memory in Aging, a population-based prospective cohort study of dementia in northern Utah. AD diagnoses were made with a multi-stage protocol that included clinical examination and review by a panel of clinical experts. We used TreeScanning, a statistically robust approach based on haplotype networks, to analyze the mtDNA sequence data. Participants with major mitochondrial haplotypes H6A1A and H6A1B showed a reduced risk of AD (p=0.017, corrected for multiple comparisons). The protective haplotypes were defined by three variants: m.3915G>A, m.4727A>G, and m.9380G>A. These three variants characterize two different major haplogroups. Together m.4727A>G and m.9380G>A define H6A1, and it has been suggested m.3915G>A defines H6A. Additional variants differentiate H6A1A and H6A1B; however, none of these variants had a significant relationship with AD case-control status.Our findings provide evidence of a reduced risk of AD for individuals with mtDNA haplotypes H6A1A and H6A1B. These findings are the results of the largest study to date with complete mtDNA genome sequence data, yet the functional significance of the associated haplotypes remains unknown and replication in others studies is necessary.
SNPs located in the gene encoding the regulatory subunit of the protein phosphatase 2B (PPP3R1, rs1868402), and the microtubule-associated protein tau (MAPT, rs3785883) gene, were recently reported to show association with CSF tau levels. Cruchaga et al 2010 also reported that rs1868402 and rs3785883 were associated with an increased rate of progression of Alzheimer's disease (AD) as measured by the Clinical Dementia Rating sum of boxes scores (CDR-sb). We attempted to validate these associations in an independent, population-based sample of incident AD cases from the Cache County Memory Study and tested them for association with the rate of progression of AD. 68 AD cases met criteria for inclusion: a global CDR-sb of less than 1 (mild) at their initial clinical assessment and CDR-sb data for at least two time points. We genotyped rs1868402 and rs3785883 using custom Taqman Assays (Applied Biosystems), utilizing the ABI ViiA 7 Instrument and the ABI Genotyper software. Subjects had an average of 5 assessments and average time from first to final assessment was 3.17 years. We used linear mixed models to identify associations between these SNPs and the trajectory of CDR-sb. Analyses were performed using Proc Mixed in SAS. We found a significant association between rs3785883 and the rate of progression of AD (p = 0.015), but failed to detect an association for rs1868402 (p = 0.30). Our analyses support the evidence that rs3785883 is associated with the rate of progression of AD. Although our results with rs1868402 were not statistically significant, the direction and magnitude of the effect observed in our data is consistent with the previous findings. We are currently genotyping additional samples and performing a combined analysis of these samples and the data from the original report. The data reported here and the additional genotyping and analyses to be presented at the meeting will provide a better understanding of the genetic variability that influences the rate of progression of Alzheimer's disease and could provide novel insights into possible preventative and therapeutic strategies.
Family-based association tests are important tools for investigating genetic risk factors of complex diseases. These tests are especially valuable for being robust to population structure. We introduce a tool, EFBAT, which performs exact family-based tests of association for X-chromosome and autosomal biallelic markers. The program EFBAT extends a network algorithm previously applied to autosomal markers to include the X-chromosome and to perform tests of association under the null hypotheses "no association, no linkage" and "no association in the presence of linkage" under additive, dominant and recessive genetic models. These tests are valid regardless of patterns of missing familial data. The general framework for performing exact family-based association tests has been usefully extended to the X-chromosome, particularly for the hypothesis of "no association in the presence of linkage" and for different genetic models.
Background Associations between selenium and cancer have directed attention to role of selenoproteins in the carcinogenic process. Methods We used data from two population-based case-control studies of colon (n = 1555 cases, 1956 controls) and rectal (n = 754 cases, 959 controls) cancer. We evaluated the association between genetic variation in TXNRD1, TXNRD2, TXNRD3, C11orf31 (SelH), SelW, SelN1, SelS, SepX, and SeP15 with colorectal cancer risk. Results After adjustment for multiple comparisons, several associations were observed. Two SNPs in TXNRD3 were associated with rectal cancer (rs11718498 dominant OR 1.42 95% CI 1.16,1.74 pACT 0.0036 and rs9637365 recessive 0.70 95% CI 0.55,0.90 pACT 0.0208). Four SNPs in SepN1 were associated with rectal cancer (rs11247735 recessive OR 1.30 95% CI 1.04,1.63 pACT 0.0410; rs2072749 GGvsAA OR 0.53 95% CI 0.36,0.80 pACT 0.0159; rs4659382 recessive OR 0.58 95% CI 0.39,0.86 pACT 0.0247; rs718391 dominant OR 0.76 95% CI 0.62,0.94 pACT 0.0300). Interaction between these genes and exposures that could influence these genes showed numerous significant associations after adjustment for multiple comparisons. Two SNPs in TXNRD1 and four SNPs in TXNRD2 interacted with aspirin/NSAID to influence colon cancer; one SNP in TXNRD1, two SNPs in TXNRD2, and one SNP in TXNRD3 interacted with aspirin/NSAIDs to influence rectal cancer. Five SNPs in TXNRD2 and one in SelS, SeP15, and SelW1 interacted with estrogen to modify colon cancer risk; one SNP in SelW1 interacted with estrogen to alter rectal cancer risk. Several SNPs in this candidate pathway influenced survival after diagnosis with colon cancer (SeP15 and SepX1 increased HRR) and rectal cancer (SepX1 increased HRR). Conclusions Findings support an association between selenoprotein genes and colon and rectal cancer development and survival after diagnosis. Given the interactions observed, it is likely that the impact of cancer susceptibility from genotype is modified by lifestyle.
