Biomedical subjects

Elizabeth R Hauser

Publications and source records attributed to Elizabeth R Hauser.

At least 19 recordsLinked to original sources

PubMed2007

Interpretation of simultaneous linkage and family-based association tests in genome screens.

Linkage and association analyses have played important roles in identifying susceptibility genes for complex diseases. Linkage tests and family-based tests of association are often applied in the same data to help fine-map disease loci or validate results. This paradigm increases efficiency by making maximal use of family data sets. However, it is not intuitively clear under what conditions association and linkage tests performed in the same data set may be correlated. Understanding this relationship is important for interpreting the combined results of both tests. We used computer simulations and theoretical statements to estimate the correlation between linkage statistics (affected sib pair maximum LOD scores) and family-based association statistics (pedigree disequilibrium test (PDT) and association in the pressure of linkage (APL)) under various hypotheses. Different types of pedigrees were studied: nuclear families with affected sib pairs, extended pedigrees and incomplete pedigrees. Both simulation and theoretical results showed that when there is no linkage or no association, the linkage and association tests are not correlated. When there is linkage and association in the data, the two tests have a positive correlation. We concluded that when linkage and association tests are applied in the same data, the type I error rate of neither test will be affected and that power can be increased by applying tests conditionally.

Alleles↗

PubMed2007

Maternal serum cytokines in preterm premature rupture of membranes.

OBJECTIVE: To estimate whether maternal serum interleukin (IL)-6 or granulocyte colony-stimulating factor (G-CSF) obtained daily are elevated in women with preterm premature rupture of membranes who develop funisitis. METHODS: Daily blood samples were obtained from women with preterm premature rupture of membranes and analyzed for IL-6 and G-CSF by enzyme-linked immunosorbent assay. Funisitis was determined by placental examination. Observations were stratified based on the presence or absence of funisitis and analyzed. Proportional hazards models were used to evaluate time-to-delivery on the basis of diagnostic IL-6 and G-CSF levels, determined by receiver operating characteristic curve analysis. RESULTS: Of the 107 patients available for analysis, 54 (50%) had evidence of funisitis after delivery. Patients with funisitis were more likely to deliver at an earlier gestational age (28.5 weeks compared with 31.5 weeks, P<.001) and have Medicaid insurance (57% compared with 39%, P=.04). Serum IL-6 and G-CSF were elevated 24 to 48 hours before delivery in women with preterm premature rupture of membranes with funisitis compared with those without funisitis (IL-6, 7.5 compared with 2.8 pg/mL, P<.001; G-CSF, 121.7 compared with 56.9 pg/mL, P=.002). Using values identified by the receiver operating characteristic curve, elevated serum IL-6 in the interval 24-72 hours before delivery was significantly associated with funisitis (P<.03), even after controlling for gestational age and insurance status. CONCLUSION: Maternal serum IL-6 and G-CSF appear to be biomarkers in the identification of women with preterm premature rupture of membranes likely to develop funisitis. LEVEL OF EVIDENCE: II.

Adult↗

PubMed2006

The APL test: extension to general nuclear families and haplotypes and examination of its robustness.

OBJECTIVE: The Association in the Presence of Linkage test (APL) is a powerful statistical method that allows for missing parental genotypes in nuclear families. However, in its original form, the statistic does not easily extend to mixed nuclear family structures nor to multiple-marker haplotypes. Furthermore, the robustness of APL in practice has not been examined. Here we present a generalization of the APL model and examination of its robustness under a variety of non-standard scenarios. METHODS: The generalization is made possible by incorporating a bootstrap variance estimator instead of the original robust variance estimator. This allows for use of more than two affected siblings. Haplotype analysis was accomplished by combining estimation of haplotype phase into the EM algorithm. Computer simulation was used to examine robustness of the APL to departures from test assumptions. RESULTS: The extended APL tests both single-marker and multiple-marker haplotypes and shows more power than other association methods. Simulation results showed that the single-marker APL test is robust to the departure from HWE. For the haplotype test, violation of the HWE assumption can inflate type I error. We also evaluated general guidelines for the validity of APL with rare alleles and rare haplotypes. Software for the APL test is available from http://www.chg.duke.edu/research/apl.html.

Computer Simulation↗

PubMed2006

GATA2 is associated with familial early-onset coronary artery disease.

The transcription factor GATA2 plays an essential role in the establishment and maintenance of adult hematopoiesis. It is expressed in hematopoietic stem cells, as well as the cells that make up the aortic vasculature, namely aortic endothelial cells and smooth muscle cells. We have shown that GATA2 expression is predictive of location within the thoracic aorta; location is suggested to be a surrogate for disease susceptibility. The GATA2 gene maps beneath the Chromosome 3q linkage peak from our family-based sample set (GENECARD) study of early-onset coronary artery disease. Given these observations, we investigated the relationship of several known and novel polymorphisms within GATA2 to coronary artery disease. We identified five single nucleotide polymorphisms that were significantly associated with early-onset coronary artery disease in GENECARD. These results were validated by identifying significant association of two of these single nucleotide polymorphisms in an independent case-control sample set that was phenotypically similar to the GENECARD families. These observations identify GATA2 as a novel susceptibility gene for coronary artery disease and suggest that the study of this transcription factor and its downstream targets may uncover a regulatory network important for coronary artery disease inheritance.

Adult↗

PubMed2006

Linkage analysis with gene-environment interaction: model illustration and performance of ordered subset analysis.

The ordered subset analysis (OSA) method allows for the incorporation of covariates into the linkage analysis of a dichotomous disease phenotype in order to reduce genetic heterogeneity. Complex human diseases may involve gene-environment (G x E) interactions, which represent a special form of heterogeneity. Here, we present results of a simulation study to evaluate the performance of OSA when the disease-generating mechanism includes G x E interaction, in the absence of main effects of gene and environment. First, the complex simulation models are illustrated graphically. Second, we show that OSA is underpowered to detect small to moderate interaction effects, consistent with previous evaluations of other linkage analysis methods. When interaction effects are large enough to produce substantial marginal effects, standard linkage methods have sufficient power to detect significant baseline linkage evidence in the entire dataset. The power of OSA to improve upon a high baseline lod score is then strongly dependent on the underlying genetic model, especially the susceptibility allele frequency. If significant, OSA identifies family subsets that are more efficient for follow-up analysis than the entire dataset, in terms of the proportion of susceptible genotypes among generated marker genotypes. For example, when strong G x E interaction with RR(G x E) = 10 is operating in at least 70% of families in the dataset, OSA has at least 70% power to detect a subset of families with significantly greater linkage evidence, the majority of linked families are captured in the OSA subset, and the per-genotype efficiency in the subset is 20-30% greater than in the entire dataset.

Chromosome Mapping↗

PubMed2006

Association of maternal IL-1 receptor antagonist intron 2 gene polymorphism and preterm birth.

OBJECTIVE: This study was undertaken to determine whether the interleukin-1 receptor antagonist (IL-1RN) variable number tandem repeat polymorphism is associated with preterm birth. STUDY DESIGN: A case-control study was performed. Cases (n = 95) delivered before 37 weeks after preterm labor (PTL) or preterm premature rupture of membranes (PPROM) and controls (n = 105) delivered after 37 weeks. Maternal DNA was genotyped by polymerase chain reaction for a length polymorphism in intron 2 of the IL-1RN gene. RESULTS: There was no significant difference in maternal age, ethnicity, insurance status, or parity between groups. Allele and genotype frequencies did not differ significantly from that expected under Hardy-Weinberg equilibrium (P = .59) in the total group as well as study groups. Of the 95 cases, 26.8% had at least 1 copy of allele 2 present compared with 12.4% in the control group (P < .0004). CONCLUSION: Maternal carriage of at least 1 copy of the IL-1RN allele 2 appears to be associated with increased risk of preterm birth.

Adult↗

PubMed2005

Searching for epistatic interactions in nuclear families using conditional linkage analysis.

BACKGROUND: Genomic screens generally employ a single-locus strategy for linkage analysis, but this may have low power in the presence of epistasis. Ordered subsets analysis (OSA) is a method for conditional linkage analysis using continuous covariates. METHODS: We used OSA to evaluate two-locus interactions in the simulated Genetic Analysis Workshop 14 dataset. We used all nuclear families ascertained by Aipotu, Karangar, and Danacaa. Using the single-nucleotide polymorphism map, multipoint affected-sibling-pair (ASP) linkage analysis was performed on all 100 replicates for each chromosome using SIBLINK. OSA was used to examine linkage on each chromosome using LOD scores at each 3-cM location on every other chromosome as covariates. Two methods were used to identify positive results: one searching across the entire covariate chromosome, the other conditioning on location of known disease loci. RESULTS: Single-locus linkage analysis revealed very high LOD scores for disease loci D1 through D4, with mean LOD scores over 100 replicates ranging from 4.0 to 7.8. Although OSA did not obscure this linkage evidence, it did not detect the simulated interactions between any of the locus pairs. We found inflated type I error rates using the first OSA method, highlighting the need to correct for multiple comparisons. Therefore, using "null chromosome pairs" without simulated disease loci, we calculated a corrected alpha-level. CONCLUSION: We were unable to detect two-locus interactions using OSA. This may have been due to lack of incorporation of phenotypic subgroups, or because linkage evidence as summarized by LOD scores performs poorly as an OSA covariate. We found inflated type I error rates, but were able to calculate a corrected alpha-level for future analyses employing this strategy to search for two-locus interactions.

Chromosome Mapping↗

PubMed2005

SNPselector: a web tool for selecting SNPs for genetic association studies.

SUMMARY: Single nucleotide polymorphisms (SNPs) are commonly used for association studies to find genes responsible for complex genetic diseases. With the recent advance of SNP technology, researchers are able to assay thousands of SNPs in a single experiment. But the process of manually choosing thousands of genotyping SNPs for tens or hundreds of genes is time consuming. We have developed a web-based program, SNPselector, to automate the process. SNPselector takes a list of gene names or a list of genomic regions as input and searches the Ensembl genes or genomic regions for available SNPs. It prioritizes these SNPs on their tagging for linkage disequilibrium, SNP allele frequencies and source, function, regulatory potential and repeat status. SNPselector outputs result in compressed Excel spreadsheet files for review by the user. AVAILABILITY: SNPselector is freely available at http://primer.duhs.duke.edu/

Algorithms↗

PubMed2005

Linkage disequilibrium inflates type I error rates in multipoint linkage analysis when parental genotypes are missing.

OBJECTIVES: Describe the inflation in nonparametric multipoint LOD scores due to inter-marker linkage disequilibrium (LD) across many markers with varied allele frequencies. METHOD: Using simulated two-generation families with and without parents, we conducted nonparametric multipoint linkage analysis with 2 to 10 markers with minor allele frequencies (MAF) of 0.5 and 0.1. RESULTS: Misspecification of population haplotype frequencies by assuming linkage equilibrium caused inflated multipoint LOD scores due to inter-marker LD when parental genotypes were not included. Inflation increased as more markers in LD were included and decreased as markers in equilibrium were added. When marker allele frequencies were unequal, the r2 measure of LD was a better predictor of inflation than D'. CONCLUSION: This observation strongly supports the evaluation of LD in multipoint linkage analyses, and further suggests that unaccounted for LD may be suspected when two-point and multipoint linkage analyses show a marked disparity in regions with elevated r2 measures of LD. Given the increasing popularity of high-density genome-wide SNP screens, inter-marker LD should be a concern in future linkage studies.

Computer Simulation↗

PubMed2005

Extension of the SIMLA package for generating pedigrees with complex inheritance patterns: environmental covariates, gene-gene and gene-environment interaction.

We have previously distributed a software package, SIMLA (SIMulation of Linkage and Association), which can be used to generate disease phenotype and marker genotype data in three-generational pedigrees of user-specified structure. To our knowledge, SIMLA is the only publicly available program that can simulate variable levels of both linkage (recombination) and linkage disequilibrium (LD) between marker and disease loci in general pedigrees. While the previous SIMLA version provided flexibility in choosing many parameters relevant for linkage and association mapping of complex human diseases, it did not allow for the segregation of more than one disease locus in a given pedigree and did not incorporate environmental covariates possibly interacting with disease susceptibility genes. Here, we present an extension of the simulation algorithm characterized by a much more general penetrance function, which allows for the joint action of up to two genes and up to two environmental covariates in the simulated pedigrees, with all possible multiplicative interaction effects between them. This makes the program even more useful for comparing the performance of different linkage and association analysis methods applied to complex human phenotypes. SIMLA can assist investigators in planning and designing a variety of linkage and association studies, and can help interpret results of real data analyses by comparing them to results obtained under a user-controlled data generation mechanism.A free download of the SIMLA package is available at http://wwwchg.duhs.duke.edu/software.

Journal Article↗

PubMed2005

Statistical Viewer: a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser.

BACKGROUND: To facilitate efficient selection and the prioritization of candidate complex disease susceptibility genes for association analysis, increasingly comprehensive annotation tools are essential to integrate, visualize and analyze vast quantities of disparate data generated by genomic screens, public human genome sequence annotation and ancillary biological databases. We have developed a plug-in package for Ensembl called "Statistical Viewer" that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis. RESULTS: Statistical Viewer is an add-on package to the open-source Ensembl Genome Browser and Annotation System that displays disease study-specific linkage and/or association data as 2 dimensional plots in new panels in the context of Ensembl's Contig View and Cyto View pages. An enhanced upload server facilitates the upload of statistical data, as well as additional feature annotation to be displayed in DAS tracts, in the form of Excel Files. The Statistical View panel, drawn directly under the ideogram, illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs. A module called "Get Map" easily converts the genetic locations of markers to genomic coordinates. The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl's Contig- and Cyto- View pages to choose the region to be displayed in Ensembl's "Overview" and "Detailed View" panels. To resolve Association and Fine mapping data plots, a "Detailed Statistic View" plot corresponding to the "Detailed View" may be displayed underneath. CONCLUSION: Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System (DAS) to display supplemental laboratory information such as differentially expressed disease genes in private data tracks. Statistic View is a novel and powerful visual feature that enhances Ensembl's utility as valuable resource for integrative genomic-based approaches to the identification of candidate disease susceptibility genes. At present there are no other tools that provide for the visualization of 2-dimensional plots of quantitative data scores against genomic coordinates in the context of a primary public genome annotation browser.

Chromosome Mapping↗

PubMed2005

Early adult-onset POAG linked to 15q11-13 using ordered subset analysis.

PURPOSE: Primary open-angle glaucoma (POAG) is a complex inherited disorder. It has been demonstrated in other complex disorders that phenotypic heterogeneity may be the result of genetic heterogeneity and that stratification analysis can be used to increase the power of detection. Ordered subset analysis (OSA) is a recently described method that utilizes the variability of phenotypic traits to determine underlying genetic heterogeneity. METHODS: Eighty-six multiplex families with POAG were clinically ascertained for genetic analysis. Age at diagnosis (AAD) was used as a surrogate for age of onset in affected family members. Nine genetic markers within the 15q11-13 interval on chromosome 15 were used for OSA analysis. RESULTS: An 11-cM linkage interval with a peak LOD score of 3.24 centered at the GABRB3 locus (P = 0.013 by permutation test) was identified in a subset of 15 families, which represents 17% of the total dataset (15/86 families). The mean AAD for the affected OSA families was 44.1 +/- 9.1 years (SD). The mean AAD for the complementary group was 61.3 +/- 10.4 years. African-American and white families were well represented in the OSA subset. CONCLUSIONS: Linkage was identified for POAG to an 11-cM region on chromosome 15, designated GLC1I. This result provides further evidence that AAD and other phenotypic traits can be used as stratification variables to identify genes in complex disorders such as POAG and suggests that the 15q11-13 locus is one of the largest genetic contributors to POAG identified to date.

Adult↗

PubMed2004

A genomewide scan for early-onset coronary artery disease in 438 families: the GENECARD Study.

A family history of coronary artery disease (CAD), especially when the disease occurs at a young age, is a potent risk factor for CAD. DNA collection in families in which two or more siblings are affected at an early age allows identification of genetic factors for CAD by linkage analysis. We performed a genomewide scan in 1,168 individuals from 438 families, including 493 affected sibling pairs with documented onset of CAD before 51 years of age in men and before 56 years of age in women. We prospectively defined three phenotypic subsets of families: (1) acute coronary syndrome in two or more siblings; (2) absence of type 2 diabetes in all affected siblings; and (3) atherogenic dyslipidemia in any one sibling. Genotypes were analyzed for 395 microsatellite markers. Regions were defined as providing evidence for linkage if they provided parametric two-point LOD scores >1.5, together with nonparametric multipoint LOD scores >1.0. Regions on chromosomes 3q13 (multipoint LOD = 3.3; empirical P value <.001) and 5q31 (multipoint LOD = 1.4; empirical P value <.081) met these criteria in the entire data set, and regions on chromosomes 1q25, 3q13, 7p14, and 19p13 met these criteria in one or more of the subsets. Two regions, 3q13 and 1q25, met the criteria for genomewide significance. We have identified a region on chromosome 3q13 that is linked to early-onset CAD, as well as additional regions of interest that will require further analysis. These data provide initial areas of the human genome where further investigation may reveal susceptibility genes for early-onset CAD.

Adult↗

PubMed2004

Ordered subset linkage analysis supports a susceptibility locus for age-related macular degeneration on chromosome 16p12.

BACKGROUND: Age-related macular degeneration (AMD) is a complex disorder that is responsible for the majority of central vision loss in older adults living in developed countries. Phenotypic and genetic heterogeneity complicate the analysis of genome-wide scans for AMD susceptibility loci. The ordered subset analysis (OSA) method is an approach for reducing heterogeneity, increasing statistical power for detecting linkage, and helping to define the most informative data set for follow-up analysis. OSA assesses the linkage evidence in subsets of potentially more homogeneous families by rank-ordering family-specific lod scores with respect to trait-associated covariates or phenotypic features. Here, we present results of incorporating five continuous covariates into our genome-wide linkage analysis of 389 microsatellite markers in 62 multiplex families: Body mass index (BMI), systolic (SBP) and diastolic (DBP) blood pressure, intraocular pressure (IOP), and pack-years of cigarette smoking. Chromosome-wide significance of increases in nonparametric multipoint lod scores in covariate-defined subsets relative to the overall sample was assessed by permutation. RESULTS: Using a correction for testing multiple covariates, statistically significant lod score increases were observed for two chromosomal regions: 14q13 with a lod score of 3.2 in 28 families with average IOP </= 15.5 (p = 0.002), and 6q14 with a lod score of 1.6 in eight families with average BMI >/= 30.1 (p = 0.0004). On chromosome 16p12, nominally significant lod score increases (p </= 0.05), up to a lod score of 2.9 in 32 families, were observed with several covariate orderings. While less significant, this was the only region where linkage evidence was associated with multiple clinically meaningful covariates and the only nominally significant finding when analysis was restricted to advanced forms of AMD. Families with linkage to 16p12 had higher averages of SBP, IOP and BMI and were primarily affected with neovascular AMD. For all three regions, linkage signals at or very near the peak marker have previously been reported. CONCLUSION: Our results suggest that a susceptibility gene on chromosome 16p12 may predispose to AMD, particularly to the neovascular form, and that further research into the previously suggested association of neovascular AMD and systemic hypertension is warranted.

Aged↗

PubMed2004

Ordered subset analysis in genetic linkage mapping of complex traits.

Etiologic heterogeneity is a fundamental feature of complex disease etiology; genetic linkage analysis methods to map genes for complex traits that acknowledge the presence of genetic heterogeneity are likely to have greater power to identify subtle changes in complex biologic systems. We investigate the use of trait-related covariates to examine evidence for linkage in the presence of heterogeneity. Ordered-subset analysis (OSA) identifies subsets of families defined by the level of a trait-related covariate that provide maximal evidence for linkage, without requiring a priori specification of the subset. We propose that examining evidence for linkage in the subset directly may result in a more etiologically homogeneous sample. In turn, the reduced impact of heterogeneity will result in increased overall evidence for linkage to a specific region and a more distinct lod score peak. In addition, identification of a subset defined by a specific trait-related covariate showing increased evidence for linkage may help refine the list of candidate genes in a given region and suggest a useful sample in which to begin searching for trait-associated polymorphisms. This method provides a means to begin to bridge the gap between initial identification of linkage and identification of the disease predisposing variant(s) within a region when mapping genes for complex diseases. We illustrate this method by analyzing data on breast cancer age of onset and chromosome 17q [Hall et al., 1990, Science 250:1684-1689]. We evaluate OSA using simulation studies under a variety of genetic models.

Breast Neoplasms↗

PubMed2004

A large set of Finnish affected sibling pair families with type 2 diabetes suggests susceptibility loci on chromosomes 6, 11, and 14.

The aim of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genes that predispose to type 2 diabetes or are responsible for variability in diabetes-related traits via a positional cloning and positional candidate gene approach. In a previously published genome-wide scan of 478 Finnish affected sibling pair (ASP) families (FUSION 1), the strongest linkage results were on chromosomes 20 and 11. We now report a second genome-wide scan using an independent set of 242 Finnish ASP families (FUSION 2), a detailed analysis of the combined set of 737 FUSION 1 + 2 families (495 updated FUSION 1 families), and fine mapping of the regions of chromosomes 11 and 20. The strongest FUSION 2 linkage results were on chromosomes 6 (maximum logarithm of odds score [MLS] = 2.30 at 95 cM) and 14 (MLS = 1.80 at 57 cM). For the combined FUSION 1 + 2 families, three results were particularly notable: chromosome 11 (MLS = 2.98 at 82 cM), chromosome 14 (MLS = 2.74 at 58 cM), and chromosome 6 (MLS = 2.66 at 96 cM). We obtained smaller FUSION 1 + 2 MLSs on chromosomes X (MLS = 1.27 at 152 cM) and 20p (MLS = 1.21 at 20 cM). Among the 10 regions that showed nominally significant evidence for linkage in FUSION 1, four (on chromosomes 6, 11, 14, and X) also showed evidence for linkage in FUSION 2 and stronger evidence for linkage in the combined FUSION 1 + 2 sample.

Age of Onset↗

PubMed2003

Adjusting for covariates on a slippery slope: linkage analysis of change over time.

BACKGROUND: We analyzed the Genetic Analysis Workshop 13 (GAW13) simulated data to contrast and compare different methods for the genetic linkage analysis of hypertension and change in blood pressure over time. We also examined methods for incorporating covariates into the linkage analysis. We used methods for quantitative trait loci (QTL) linkage analysis with and without covariates and affected sib-pair (ASP) analysis of hypertension followed by ordered subset analysis (OSA), using variables associated with change in blood pressure over time. RESULTS: Four of the five baseline genes and one of the three slope genes were not detected by any method using conventional criteria. OSA detected baseline gene b35 on chromosome 13 when using the slope in blood pressure to adjust for change over time. Slope gene s10 was detected by the ASP analysis and slope gene s11 was detected by QTL linkage analysis as well as by OSA analysis. Analysis of null chromosomes, i.e., chromosomes without genes, did not reveal significant increases in type I error. However, there were a number of genes indirectly related to blood pressure detected by a variety of methods. CONCLUSIONS: We noted that there is no obvious first choice of analysis software for analyzing a complicated model, such as the one underlying the GAW13 simulated data. Inclusion of covariates and longitudinal data can improve localization of genes for complex traits but it is not always clear how best to do this. It remains a worthwhile task to apply several different approaches since one method is not always the best.

Blood Pressure↗

PubMed2003

Ordered-subsets linkage analysis detects novel Alzheimer disease loci on chromosomes 2q34 and 15q22.

Alzheimer disease (AD) is a complex disorder characterized by a wide range, within and between families, of ages at onset of symptoms. Consideration of age at onset as a covariate in genetic-linkage studies may reduce genetic heterogeneity and increase statistical power. Ordered-subsets analysis includes continuous covariates in linkage analysis by rank ordering families by a covariate and summing LOD scores to find a subset giving a significantly increased LOD score relative to the overall sample. We have analyzed data from 336 markers in 437 multiplex (>/=2 sampled individuals with AD) families included in a recent genomic screen for AD loci. To identify genetic heterogeneity by age at onset, families were ordered by increasing and decreasing mean and minimum ages at onset. Chromosomewide significance of increases in the LOD score in subsets relative to the overall sample was assessed by permutation. A statistically significant increase in the nonparametric multipoint LOD score was observed on chromosome 2q34, with a peak LOD score of 3.2 at D2S2944 (P=.008) in 31 families with a minimum age at onset between 50 and 60 years. The LOD score in the chromosome 9p region previously linked to AD increased to 4.6 at D9S741 (P=.01) in 334 families with minimum age at onset between 60 and 75 years. LOD scores were also significantly increased on chromosome 15q22: a peak LOD score of 2.8 (P=.0004) was detected at D15S1507 (60 cM) in 38 families with minimum age at onset >/=79 years, and a peak LOD score of 3.1 (P=.0006) was obtained at D15S153 (62 cM) in 43 families with mean age at onset >80 years. Thirty-one families were contained in both 15q22 subsets, indicating that these results are likely detecting the same locus. There is little overlap in these subsets, underscoring the utility of age at onset as a marker of genetic heterogeneity. These results indicate that linkage to chromosome 9p is strongest in late-onset AD and that regions on chromosome 2q34 and 15q22 are linked to early-onset AD and very-late-onset AD, respectively.

Age of Onset↗