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Janet S Sinsheimer

Publications and source records attributed to Janet S Sinsheimer.

At least 19 recordsLinked to original sources
PubMed2006

Allowing for missing data at highly polymorphic genes when testing for maternal, offspring and maternal-fetal genotype incompatibility effects.

Genes can be associated with disease through an individual's inherited genotype, the maternal genotype or the interaction between these two. When the gene is highly polymorphic, it is more difficult to identify the gene's functional role than for less polymorphic loci, because different alleles at the locus may be associated with the disease through separate and joint effects from maternal and offspring genotypes. Family-based studies are used to test genetic associations because of their robustness to population stratification. However, parental genotype data are often missing, and omitting incompletely genotyped families is inefficient. Methods have been proposed to accommodate incomplete families in family-based association studies. They are not easily generalized to allow simultaneous examination of offspring allelic, maternal allelic and maternal-fetal genotype (MFG) incompatibility effects. Since many MFG incompatibility effects occur through matching between maternal and offspring's genotypes, we present an identity-by-state (IBS) framework to incorporate incomplete families in the MFG test when modeling genetic effects produced by a polymorphic gene. Using simulations, we examine the MFG test's performance with incomplete parental genotype data and an IBS framework. The MFG test using the IBS framework is immune to population stratification and efficiently uses information from incomplete families.

Algorithms↗
PubMed2006

A high-throughput method for cloning and sequencing human immunodeficiency virus type 1 integration sites.

Integration of retroviral DNA is nonspecific and can occur at many sites throughout chromosomes. However, the process is not uniformly distributed, and both hot and cold spots for integration exist. The mechanism that determines target site specificity is not well understood. Because of the nonspecific and widespread nature of integration, studies analyzing the mechanism and factors that control target site selection require the collection and analysis of a large library of human immunodeficiency virus type 1 (HIV-1) proviral clones. Such analyses are time-consuming and labor-intensive using conventional means. We have developed an efficient and high-throughput method of sequencing and mapping a large number of independent integration sites in the absence of any selection or bias. The new assay involves the use of a modified HIV-1 (NL-Mme) containing a type IIS restriction site, MmeI, at the right end of viral DNA. Digestion of genomic DNA from NL-Mme-infected cells generated viral DNA-containing fragments of a discrete size. Subsequent ligation-mediated PCR yielded short integration site fragments termed Int-tags, which were concatemerized for determining multiple integration sites in a single sequencing reaction. Analysis of chromosomal features and sequence preference associated with integration events confirmed the validity of the new high-throughput assay. The assay will aid the effort in understanding the mechanisms of target site selection during HIV-1 DNA integration, and the described methodology can be adapted easily to integration site studies involving other retroviruses and transposons.

Cell Line↗
PubMed2006

HLA-B maternal-fetal genotype matching increases risk of schizophrenia.

Schizophrenia and human leukocyte antigen (HLA) matching between couples or between mothers and offspring have independently been associated with prenatal/obstetric complications, including preeclampsia and low birth weight. Here, we report the results of a family-based candidate-gene study that brings together these two disparate lines of research by assessing maternal-fetal genotype matching at HLA-A, -B, and -DRB1 as a risk factor of schizophrenia. We used a conditional-likelihood modeling approach with a sample of 274 families that had at least one offspring with schizophrenia or a related spectrum disorder. A statistically significant HLA-B maternal-fetal genotype-matching effect on schizophrenia was demonstrated for female offspring (P=.01; parameter estimate 1.7 [95% confidence interval 1.22-2.49]). Because the matching effect could be associated with pregnancy complications rather than with schizophrenia per se, these findings are consistent with the neurodevelopmental hypothesis of schizophrenia and with accumulating evidence that the prenatal period is involved in the origins of this disease. Our approach demonstrates how genetic markers can be used to characterize the biology of prenatal risk factors of schizophrenia.

Female↗
PubMed2006

The v-MFG test: investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability.

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

Alleles↗
PubMed2005

Investigating the aspartic acid (D) repeat of asporin as a risk factor for osteoarthritis in a UK Caucasian population.

OBJECTIVE: A compelling genetic association with osteoarthritis (OA) of 2 functional alleles in the aspartic acid (D) repeat of the asporin gene was recently reported in a Japanese population. Allele D13 of the repeat encoded OA protection, whereas allele D14 encoded OA susceptibility. The 2 alleles mediate differences in the capacity of asporin to inhibit the cartilage growth factor transforming growth factor beta, with the D14 allele being a particularly potent inhibitor. Our objective was to assess whether the D repeat is associated with OA in UK Caucasians. METHODS: The repeat was genotyped in 1,247 patients who had undergone elective joint replacement of the hip or the knee due to end-stage primary OA and in 748 age-matched controls. RESULTS: The D13 allele was more common in controls, and the D14 allele was more common in patients. However, this trend was significant only for men who had undergone hip replacement (P = 0.016, odds ratio 1.48, 95% confidence interval 1.09-2.01). CONCLUSION: Our data suggest that the asporin polymorphism is not a major influence on OA etiology in Caucasians. The results of our study do not question the veracity of the Japanese report. Instead, our study highlights the complex, heterogeneous nature of OA genetic susceptibility.

Aged↗
PubMed2005

An exact maternal-fetal genotype incompatibility (MFG) test.

The maternal-fetal genotype incompatibility (MFG) test can be used for a variety of genetic applications concerning disease risk in offspring including testing for the presence of alleles that act directly through offspring genotypes (child allelic effects), alleles that act through maternal genotypes (maternal allelic effects), or maternal-fetal genotype incompatibilities. The log-linear version of the MFG model divides the genotype data into many cells, where each cell represents one of the possible mother, father, and child genotype combinations. Currently, tests of hypotheses about different allelic effects are accomplished by an asymptotic MFG test, but it is unknown if this is appropriate under conditions that produce small cell counts. In this report, we develop an exact MFG test that is based on the permutation distribution of cell counts. We determine by simulation the type I error and power of both the exact MFG test and the asymptotic MFG test for four different biologically relevant scenarios: a test of child allelic effects in the presence of maternal allelic effects, a test of maternal allelic effects in the presence of child allelic effects, and tests of maternal-fetal genotype incompatibility with and without child allelic effects. These simulations show that, in general, the exact test is slightly conservative whereas the asymptotic test is slightly anti-conservative. However, the asymptotic MFG test produces significantly inflated type I error rates under conditions with extreme null allele frequencies and sample sizes of 75, 100, and 150. Under these conditions, the exact test is clearly preferred over the asymptotic test. Under all other conditions that we tested, the user can safely choose either the exact test or the asymptotic test.

Adult↗
PubMed2005

Association testing with Mendel.

This report presents an overview of association testing strategies from a user's perspective, with particular attention to the capabilities of the computer program Mendel. Association testing is driven by the nature of the study sample, the nature of the disease trait, and the kind of markers employed. The practicing statistician must also choose whether to conduct parametric or nonparametric tests. Because of the complexities involved, Mendel offers users several analysis options. The different options are tied together by shared input and output conventions and a shared language for defining models. Mendel also features new statistics and theory found in no other genetics software. The most important innovations include: association testing by penetrance estimation, expansion of matched-pair designs to permutation unit designs, and a rigorous implementation of the measured genotype approach for quantitative trait loci. This report explains how Mendel imputes allele counts and conducts both asymptotic and permutation tests in the measured genotype framework.

Analysis of Variance↗
PubMed2005

Models for estimating bayes factors with applications to phylogeny and tests of monophyly.

Bayes factors comparing two or more competing hypotheses are often estimated by constructing a Markov chain Monte Carlo (MCMC) sampler to explore the joint space of the hypotheses. To obtain efficient Bayes factor estimates, Carlin and Chib (1995, Journal of the Royal Statistical Society, Series B57, 473-484) suggest adjusting the prior odds of the competing hypotheses so that the posterior odds are approximately one, then estimating the Bayes factor by simple division. A byproduct is that one often produces several independent MCMC chains, only one of which is actually used for estimation. We extend this approach to incorporate output from multiple chains by proposing three statistical models. The first assumes independent sampler draws and models the hypothesis indicator function using logistic regression for various choices of the prior odds. The two more complex models relax the independence assumption by allowing for higher-lag dependence within the MCMC output. These models allow us to estimate the uncertainty in our Bayes factor calculation and to fully use several different MCMC chains even when the prior odds of the hypotheses vary from chain to chain. We apply these methods to calculate Bayes factors for tests of monophyly in two phylogenetic examples. The first example explores the relationship of an unknown pathogen to a set of known pathogens. Identification of the unknown's monophyletic relationship may affect antibiotic choice in a clinical setting. The second example focuses on HIV recombination detection. For potential clinical application, these types of analyses must be completed as efficiently as possible.

Bayes Theorem↗
PubMed2004

Long-term survivors in Nairobi: complete HIV-1 RNA sequences and immunogenetic associations.

To investigate African long-term survivors (LTSs) infected with non-subtype B human immunodeficiency virus type 1 (HIV-1), we obtained full-length HIV-1 RNA sequences and immunogenetic profiles from 6 untreated women enrolled in the Pumwani Sex Worker Cohort in Nairobi, Kenya. There were no discernible sequence changes likely to cause attenuation. CCR2-V64I, an immunogenetic polymorphism linked to LTSs, was detected in 4 women, all of whom carried the HLA B58 allele. Further investigation of 99 HIV-1-infected Nairobi women found an association between CCR2-V64I and HLA B58 (P=.0048). Studying the interaction among immunogenetics, immune responses, and viral sequences from all HIV-1 subtypes may increase our understanding of slow HIV-1 disease progression.

Adult↗
PubMed2004

Association of the APOLIPOPROTEIN A1/C3/A4/A5 gene cluster with triglyceride levels and LDL particle size in familial combined hyperlipidemia.

The APOLIPOPROTEIN (APO)A1/C3/A4/A5 gene cluster on chromosome 11 has been hypothesized to be a modifier of plasma triglycerides in FCH. In the present study, we extended previous association analyses of the gene cluster to include APOA5, a newly discovered member of the cluster. Eight SNPs across the APOA1/C3/A4/A5 gene region were analyzed in 78 FCH probands and their normolipidemic spouses as well as in 27 Dutch FCH families. Of the individual SNPs tested in the case-control panel, the strongest evidence of association was obtained with SNPs in APOA1 (P=0.001) and APOA5 (P=0.001). A single haplotype defined by a missense mutation in APOA5 was enriched 3-fold in FCH probands when compared with the normolipidemic spouses (P=0.001) and a second haplotype was significantly enriched in the spouses (P=0.001). Family-based tests also indicated significant association of triglyceride levels and LDL particle size with the investigated SNPs of APOC3 and APOA5. These findings suggest that genetic variation in the APOA1/C3/A4/A5 gene cluster acts as a modifier of plasma triglyceride levels and LDL particle size within FCH families and furthermore indicate that a number of haplotypes may contribute to FCH.

Adult↗
PubMed2004

Familial combined hyperlipidemia is associated with upstream transcription factor 1 (USF1).

Familial combined hyperlipidemia (FCHL), characterized by elevated levels of serum total cholesterol, triglycerides or both, is observed in about 20% of individuals with premature coronary heart disease. We previously identified a locus linked to FCHL on 1q21-q23 in Finnish families with the disease. This region has also been linked to FCHL in families from other populations as well as to type 2 diabetes mellitus. These clinical entities have several overlapping phenotypic features, raising the possibility that the same gene may underlie the obtained linkage results. Here, we show that the human gene encoding thioredoxin interacting protein (TXNIP) on 1q, which underlies combined hyperlipidemia in mice, is not associated with FCHL. We show that FCHL is linked and associated with the gene encoding upstream transcription factor 1 (USF1) in 60 extended families with FCHL, including 721 genotyped individuals (P = 0.00002), especially in males with high triglycerides (P = 0.0000009). Expression profiles in fat biopsy samples from individuals with FCHL seemed to differ depending on their carrier status for the associated USF1 haplotype. USF1 encodes a transcription factor known to regulate several genes of glucose and lipid metabolism.

Animals↗
PubMed2004

RHD maternal-fetal genotype incompatibility and schizophrenia: extending the MFG test to include multiple siblings and birth order.

Rh incompatibility disease (ie Rh hemolytic disease of the fetus and newborn) has been implicated as a risk factor for schizophrenia. Here, we extend the maternal-fetal genotype incompatibility (MFG) test used in an earlier case-parent trio study that found significant evidence for an increased risk of schizophrenia in RHD MFG-incompatible children. We modify the MFG test for case-parent trios to include any number of siblings. This modified test enables us to use more of the available data from the earlier study. The increased sample size not only gives us greater power to test for MFG incompatibility but it also enables us to model the impact of previous RHD MFG-incompatible pregnancies on the relative risk of RHD MFG incompatibility in later-born siblings. This modeling is important, because RHD MFG incompatibility is a proxy for Rh incompatibility disease, and the risk of Rh incompatibility disease increases with the number of previous RHD MFG-incompatible pregnancies. The best-fitting models are consistent with the hypothesized effect that previous incompatible pregnancies increase the risk of schizophrenia due to RHD MFG incompatibility. There was significant evidence that the relative risk of schizophrenia in the second- and later-born RHD MFG-incompatible children is 1.7, consistent with earlier estimates. Our extension of the MFG test has general application to family-based studies of maternal-genotype and MFG interaction effects.

Birth Order↗
PubMed2004

The pedigree trimming problem.

This report mathematically validates a fast algorithm for trimming irrelevant members from a pedigree. These individuals are typically dead or otherwise unavailable for study. Left in the pedigree, they slow likelihood evaluation. Of course, each pedigree of interest will have some core people who must be retained. The described algorithm retains just enough of the pedigree to maintain the proper relationships among the core people.

Algorithms↗
PubMed2003

Detecting genotype combinations that increase risk for disease: maternal-fetal genotype incompatibility test.

Biological mechanisms that involve gene-by-environment interactions have been hypothesized to explain susceptibility to complex familial disorders. Current research provides compelling evidence that one environmental factor, which acts prenatally to increase susceptibility, arises from a maternal-fetal genotype incompatibility. Because it is genetic in origin, a maternal-fetal incompatibility is one possible source of an adverse environment that can be detected in genetic analyses and precisely studied, even years after the adverse environment was present. Existing statistical models and tests for gene detection are not optimal or even appropriate for identifying maternal-fetal genotype incompatibility loci that may increase the risk for complex disorders. We describe a new test, the maternal-fetal genotype incompatibility (MFG) test, that can be used with case-parent triad data (affected individuals and their parents) to identify loci for which a maternal-fetal genotype incompatibility increases the risk for disease. The MFG test adapts a log-linear approach for case-parent triads in order to detect maternal-fetal genotype incompatibility at a candidate locus, and allows the incompatibility effects to be estimated separately from direct effects of either the maternal or the child's genotype. Through simulations of two biologically plausible maternal-fetal genotype incompatibility scenarios, we show that the type-I error rate of the MFG test is appropriate, that the estimated parameters are accurate, and that the test is powerful enough to detect a maternal-fetal genotype incompatibility of moderate effect size.

Bias↗
PubMed2003

Testing a molecular clock without an outgroup: derivations of induced priors on branch-length restrictions in a Bayesian framework.

We propose a Bayesian method for testing molecular clock hypotheses for use with aligned sequence data from multiple taxa. Our method utilizes a nonreversible nucleotide substitution model to avoid the necessity of specifying either a known tree relating the taxa or an outgroup for rooting the tree. We employ reversible jump Markov chain Monte Carlo to sample from the posterior distribution of the phylogenetic model parameters and conduct hypothesis testing using Bayes factors, the ratio of the posterior to prior odds of competing models. Here, the Bayes factors reflect the relative support of the sequence data for equal rates of evolutionary change between taxa versus unequal rates, averaged over all possible phylogenetic parameters, including the tree and root position. As the molecular clock model is a restriction of the more general unequal rates model, we use the Savage-Dickey ratio to estimate the Bayes factors. The Savage-Dickey ratio provides a convenient approach to calculating Bayes factors in favor of sharp hypotheses. Critical to calculating the Savage-Dickey ratio is a determination of the prior induced on the modeling restrictions. We demonstrate our method on a well-studied mtDNA sequence data set consisting of nine primates. We find strong support against a global molecular clock, but do find support for a local clock among the anthropoids. We provide mathematical derivations of the induced priors on branch length restrictions assuming equally likely trees. These derivations also have more general applicability to the examination of prior assumptions in Bayesian phylogenetics.

Animals↗
PubMed2003

Hierarchical phylogenetic models for analyzing multipartite sequence data.

Debate exists over how to incorporate information from multipartite sequence data in phylogenetic analyses. Strict combined-data approaches argue for concatenation of all partitions and estimation of one evolutionary history, maximizing the explanatory power of the data. Consensus/independence approaches endorse a two-step procedure where partitions are analyzed independently and then a consensus is determined from the multiple results. Mixtures across the model space of a strict combined-data approach and a priori independent parameters are popular methods to integrate these methods. We propose an alternative middle ground by constructing a Bayesian hierarchical phylogenetic model. Our hierarchical framework enables researchers to pool information across data partitions to improve estimate precision in individual partitions while permitting estimation and testing of tendencies in across-partition quantities. Such across-partition quantities include the distribution from which individual topologies relating the sequences within a partition are drawn. We propose standard hierarchical priors on continuous evolutionary parameters across partitions, while the structure on topologies varies depending on the research problem. We illustrate our model with three examples. We first explore the evolutionary history of the guinea pig (Cavia porcellus) using alignments of 13 mitochondrial genes. The hierarchical model returns substantially more precise continuous parameter estimates than an independent parameter approach without losing the salient features of the data. Second, we analyze the frequency of horizontal gene transfer using 50 prokaryotic genes. We assume an unknown species-level topology and allow individual gene topologies to differ from this with a small estimable probability. Simultaneously inferring the species and individual gene topologies returns a transfer frequency of 17%. We also examine HIV sequences longitudinally sampled from HIV+ patients. We ask whether posttreatment development of CCR5 coreceptor virus represents concerted evolution from middisease CXCR4 virus or reemergence of initial infecting CCR5 virus. The hierarchical model pools partitions from multiple unrelated patients by assuming that the topology for each patient is drawn from a multinomial distribution with unknown probabilities. Preliminary results suggest evolution and not reemergence.

Animals↗
PubMed2003

Site and gender specificity of inheritance of bone mineral density.

UNLABELLED: Differences in genetic control of BMD by skeletal sites and genders were examined by complex segregation analysis in 816 members of 147 families with probands with extreme low BMD. Spine BMD correlated more strongly in male-male comparisons and hip BMD in female-female comparisons, consistent with gender- and site-specificity of BMD heritability. INTRODUCTION: Evidence from studies in animals and humans suggests that the genetic control of bone mineral density (BMD) may differ at different skeletal sites and between genders. This question has important implications for the design and interpretation of genetic studies of osteoporosis. METHODS: We examined the genetic profile of 147 families with 816 individuals recruited through probands with extreme low BMD (T-score < -2.5, Z-score < -2.0). Complex segregation analysis was performed using the Pedigree Analysis Package. BMD was measured by DXA at both lumbar spine (L1-L4) and femoral neck. RESULTS: Complex segregation analysis excluded purely monogenic and environmental models of segregation of lumbar spine and femoral neck BMD in these families. Pure polygenic models were excluded at the lumbar spine when menopausal status was considered as a covariate, but not at the femoral neck. Mendelian models with a residual polygenic component were not excluded. These models were consistent with the presence of a rare Mendelian genotype of prevalence 3-19%, causing high BMD at the hip and spine in these families, with additional polygenic effects. Total heritability range at the lumbar spine was 61-67% and at the femoral neck was 44-67%. Significant differences in correlation of femoral neck and lumbar spine BMD were observed between male and female relative pairs, with male-male comparisons exhibiting stronger lumbar spine BMD correlation than femoral neck, and female-female comparisons having greater femoral neck BMD correlation than lumbar spine. These findings remained true for parent-offspring correlations when menopausal status was taken into account. The recurrence risk ratio for siblings of probands of a Z-score < -2.0 was 5.4 at the lumbar spine and 5.9 at the femoral neck. CONCLUSIONS: These findings support gender- and site-specificity of the inheritance of BMD. These results should be considered in the design and interpretation of genetic studies of osteoporosis.

Bone Density↗