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PubMed2004

An integrated epigenetic and genetic approach to common human disease.

Epigenetic information is heritable during cell division but is not contained within the DNA sequence itself. Despite increasing evidence for and interest in the role of epigenetics in human disease, particularly in cancer, virtually no epigenetic information is routinely or systematically measured at the genome level. The current population-based approach to common disease relates common DNA sequence variants to either disease status or incremental quantitative traits contributing to disease. Although this purely genetic approach is powerful and general, there is currently no conceptual framework to integrate epigenetic information. In this article, we propose an approach to common human disease that incorporates epigenetic variation into genetic studies. Epigenetic variation might also help to explain the late onset and progressive nature of most common diseases, the quantitative nature of complex traits and the role of environment in disease development, which a purely sequence-based approach might not.

Epigenesis, Genetic↗
PubMed1986

Complex segregation analysis of low levels of plasma high-density lipoprotein cholesterol in a sample of nuclear families in Jerusalem.

Low levels of high-density lipoprotein cholesterol (HDL-C) are associated with increased risk of coronary heart disease (CHD). Therefore, assessment of the mode of inheritance of HDL-C is of importance. HDL-C concentrations in 3,074 nuclear families in the multiethnic Jerusalem Lipid Research Center study population were analyzed for possible involvement of major genes in determination of low levels of this trait. Complex segregation analysis under the mixed model of inheritance (major gene and multifactorial components) was performed on transformed HDL-C concentrations after adjustment for age, sex, and environmental measures. Evidence for segregation of a recessive major gene for depressed HDL-C, with an allele frequency of q = 0.06, in addition to multifactorial transmission (H = 0.45) was found in these families. Estimates from the mixed model were homogeneous across the different ethnic groups. When the substantial multifactorial background was excluded from the model, we found evidence for an additive (codominant) Mendelian gene (d = 0.48), which demonstrates the necessity of using the mixed model. Our previous results were inconclusive with respect to the involvement of a major gene in determination of high levels of HDL-C. However, we tentatively postulate an uncommon recessive gene for low levels of HDL-C in the Israeli population in addition to polygenic and environmental determinants.

Adolescent↗
PubMed2003

Genetics of preeclampsia: what are the challenges?

Despite recent efforts to identify susceptibility genes of preeclampsia, the genetic determinants of the condition remain ill-defined, as is the situation for most disorders of complex inheritance patterns. The angiotensinogen, factor V, and methylenetetrahydrofolate reductase genes have been investigated in different populations, as have other genes involved in blood pressure, vascular volume control, thrombophilia, lipid metabolism, oxidative stress, and endothelial dysfunction. The study of the genetics of complex traits is faced with both methodological and genetic issues; these include adequate sample size to allow for the identification of modest genetic effects, of gene-gene and gene-environment interactions, the study of adequate quantitative traits and extreme phenotypes, haplotype analyses, statistical genetics, genome-wide (hypothesis-free) versus candidate-gene (hypothesis-driven) approaches, and the validation of positive associations. The use of genetically well-characterized populations showing a founder effect, such as the French-Canadian population of Quebec, in genetic association studies, may help to unravel the susceptibility genes of disorders showing complex inheritance, such as preeclampsia. It is necessary to better evaluate the role of the fetal genome in the resulting predisposition to preeclampsia and its complications. Eventually, we may be able to integrate genetic information to better identify the women at risk of developing preeclampsia, and to improve the management of those suffering from this condition.

Adult↗
PubMed2025

Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.

Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations. We investigated the potential of increasing prediction ability by combining genomic and transcriptomic datasets, adding whole-genome sequencing (WGS) SNP data, functional annotation-based filtering, and empirical quality filtering. Our RNA-Seq data were generated cost-efficiently using small-footprint plant cultivation, high-throughput RNA extraction, and Library preparation miniaturization. We also examined sequencing depth reduction as an additional cost-saving measure. We used fivefold cross-validation to evaluate the prediction ability of the gene expression dataset, the RNA-Seq SNP dataset, and the consensus SNP dataset between the RNA-Seq and parental WGS data, resulting in prediction abilities between 0.73 and 0.78. The consensus SNP dataset performed best, with five out of eight traits performing significantly better compared to a 50K SNP array, which served as a benchmark. The advantage of the consensus SNP dataset was most prominent in the inter-population predictions, in which the training and validation sets originated from different RIL sub-populations. We were therefore able to not only show that RNA-Seq data alone are able to predict various complex traits in barley using RILs, but also that the performance can be further increased with WGS data for which the public availability will steadily increase.

Hordeum↗
PubMed2006

Variance calculations for identity-by-descent estimation.

Nonparametric linkage strategies often involve estimation of identity by descent (IBD) with the use of affected sibling pairs. Methods for IBD estimation are well established and have been successful for mapping complex traits. However, the majority of linkage approaches involving IBD have focused on statistical testing, rather than on the effect estimates themselves. Through a bootstrap procedure developed for linkage-scan data sets, we provide standard errors for the estimated mean IBD that are broadly applicable. Applications that benefit from the availability of standard errors include effect-size estimates and confidence intervals; meta-analyses, including tests for heterogeneity; and discordant-sibling-pair evaluation. We demonstrate the use of estimated mean IBD and its standard errors in the National Institute of Mental Health Human Genetics Initiative linkage samples for bipolar disorder and Alzheimer disease. Mean IBD and its standard errors are valuable tools for the further assessment and evaluation of linkage-scan samples involving complex disease.

Alzheimer Disease↗
PubMed1999

The genetics of multiple sclerosis. A review.

Multiple sclerosis (MS) is characterized by chronic inflammation and demyelination in the central nervous system (CNS). Although the etiology of MS is unknown, both genetic and environmental contributions to the pathogenesis are inferred from epidemiologic studies. Geographic distributions and epidemics of MS and data from migration studies provide evidence for some, thus far unidentified, environmental effects. The co-occurrence of MS with high and low frequencies in ethnic groups often sharing an environment, the increased recurrence rate in families, and the high concordance rate among identical twins point to inheritable determinants of susceptibility. Based on the autoimmune hypothesis of demyelination, genetic studies sought associations between MS and polymorphic alleles of candidate genes which regulate either the immune response or myelin production. The most consistent finding in case-control studies was the association with the major histocompatibility complex (MHC) (also called human leukocyte antigen--HLA) class II, DR15, DQ6, Dw2 haplotype. Studies on other gene products encoded within or close to the MHC complex on chromosome 6p21.3 (e.g., HLA DP, complement components, transporter proteins, tumor necrosis factor, and myelin-oligodendrocyte glycoprotein) resulted in conflicting observations in different patient populations. The potential contribution of polymorphic alleles within the genes of the T-cell receptor alpha beta chains, immunoglobulins, cytokines, and oligodendrocyte growth factors or their receptors to MS susceptibility either remains equivocal or is rejected. Studies on families with multiple affected members have revealed that MS is a complex trait, that the contribution of individual genes to susceptibility is probably small, and that differences are possible between familial and sporadic forms. The development of molecular and computer technologies have facilitated the performance of comprehensive genomic scans in multiplex families, which have confirmed the possible linkage of multiple loci to susceptibility, each with a minor contribution. Several provisional sites were reported, but only 6p21 (MHC complex), 5p14, and 17q22 were positive in more than one study. The British update demonstrated segregation among regions of interest depending on DR15 sharing, and excluded a gene of major effect from 95%, and one with a moderate effect from 65% of the genome. The extended study by the US collaboration group revealed that the MHC linkage was limited to families segregating HLA DR2 alleles, which suggested that linkage to the MHC is related to the HLA DR2 association, and that sporadic and familial MS share at least one common susceptibility marker. Further identification of MS susceptibility loci may involve additional family sets, more polymorphic markers, and the exploration of telomeric chromosomal regions. Data from these studies may further elucidate pathogenic mechanisms of MS.

Chromosomes, Human, Pair 6↗
PubMed2001

Statistics for nonparametric linkage analysis of X-linked traits in general pedigrees.

We have compared the power of several allele-sharing statistics for "nonparametric" linkage analysis of X-linked traits in nuclear families and extended pedigrees. Our rationale was that, although several of these statistics have been implemented in popular software packages, there has been no formal evaluation of their relative power. Here, we evaluate the relative performance of five test statistics, including two new test statistics. We considered sibships of sizes two through four, four different extended pedigrees, 15 different genetic models (12 single-locus models and 3 two-locus models), and varying recombination fractions between the marker and the trait locus. We analytically estimated the sample sizes required for 80% power at a significance level of.001 and also used simulation methods to estimate power for a sample size of 10 families. We tried to identify statistics whose power was robust over a wide variety of models, with the idea that such statistics would be particularly useful for detection of X-linked loci associated with complex traits. We found that a commonly used statistic, S(all), generally performed well under various conditions and had close to the optimal sample sizes in most cases but that there were certain cases in which it performed quite poorly. Our two new statistics did not perform any better than those already in the literature. We also note that, under dominant and additive models, regardless of the statistic used, pedigrees with all-female siblings have very little power to detect X-linked loci.

Alleles↗
PubMed1999

Linkage of low-density lipoprotein size to the lipoprotein lipase gene in heterozygous lipoprotein lipase deficiency.

Small low-density lipoprotein (LDL) particles are a genetically influenced coronary disease risk factor. Lipoprotein lipase (LpL) is a rate-limiting enzyme in the formation of LDL particles. The current study examined genetic linkage of LDL particle size to the LpL gene in five families with structural mutations in the LpL gene. LDL particle size was smaller among the heterozygous subjects, compared with controls. Among heterozygous subjects, 44% were classified as affected by LDL subclass phenotype B, compared with 8% of normal family members. Plasma triglyceride levels were significantly higher, and high-density lipoprotein cholesterol (HDL-C) levels were lower, in heterozygous subjects, compared with normal subjects, after age and sex adjustment. A highly significant LOD score of 6.24 at straight theta=0 was obtained for linkage of LDL particle size to the LpL gene, after adjustment of LDL particle size for within-genotype variance resulting from triglyceride and HDL-C. Failure to adjust for this variance led to only a modest positive LOD score of 1.54 at straight theta=0. Classifying small LDL particles as a qualitative trait (LDL subclass phenotype B) provided only suggestive evidence for linkage to the LpL gene (LOD=1. 65 at straight theta=0). Thus, use of the quantitative trait adjusted for within-genotype variance, resulting from physiologic covariates, was crucial for detection of significant evidence of linkage in this study. These results indicate that heterozygous LpL deficiency may be one cause of small LDL particles and may provide a potential mechanism for the increase in coronary disease seen in heterozygous LpL deficiency. This study also demonstrates a successful strategy of genotypic specific adjustment of complex traits in mapping a quantitative trait locus.

Adolescent↗
PubMed2005

Gene expression differences in mice divergently selected for methamphetamine sensitivity.

In an effort to identify genes that may be important for drug-abuse liability, we mapped behavioral quantitative trait loci (bQTL) for sensitivity to the locomotor stimulant effect of methamphetamine (MA) using two mouse lines that were selectively bred for high MA-induced activity (HMACT) or low MA-induced activity (LMACT). We then examined gene expression differences between these lines in the nucleus accumbens, using 20 U74Av2 Affymetrix microarrays and quantitative polymerase chain reaction (qPCR). Expression differences were detected for several genes, including Casein Kinase 1 Epsilon (Csnkle), glutamate receptor, ionotropic, AMPA1 (GluR1), GABA B1 receptor (Gabbr1), and dopamine- and cAMP-regulated phosphoprotein of 32 kDa (Darpp-32). We used the www.WebQTL.org database to identify QTL that regulate the expression of the genes identified by the microarrays (expression QTL; eQTL). This approach identified an eQTL for Csnkle on Chromosome 15 (LOD = 3.8) that comapped with a bQTL for the MA stimulation phenotype (LOD = 4.5), suggesting that a single allele may cause both traits. The chromosomal region containing this QTL has previously been associated with sensitivity to the stimulant effects of cocaine. These results suggest that selection was associated with (and likely caused) altered gene expression that is partially attributable to different frequencies of gene expression polymorphisms. Combining classical genetics with analysis of whole-genome gene expression and bioinformatic resources provides a powerful method for provisionally identifying genes that influence complex traits. The identified genes provide excellent candidates for future hypothesis-driven studies, translational genetic studies, and pharmacological interventions.

Animals↗
PubMed2004

Methylenetetrahydrofolate reductase polymorphism interacts with riboflavin intake to influence bone mineral density.

Bone mineral density is a complex trait regulated by an interaction between genetic and environmental factors. Recent studies have identified a functional polymorphism affecting codon 677 of the methylenetetrahydrofolate reductase (MTHFR) gene that is associated with reduced bone mineral density (BMD) in Japanese and Danish postmenopausal women and increased risk of fracture in elderly Danish women. Since dietary B vitamins can influence circulating homocysteine (tHcy) levels, we examined the relationship among MTHFR genotype, B complex vitamins (folate, vitamin B12, vitamin B6 and riboflavin), BMD, and rate of change in BMD in a longitudinal study of 1241 Scottish women aged 45-54 years, at the time of initial study, who were followed up for a mean (SD) of 6.6 (0.7) years. There was no significant association between BMD and either MTHFR genotype or B complex vitamins when examined separately. However, we detected a significant interaction among quartile of energy-adjusted riboflavin intake, MTHFR 'TT' genotype, and BMD (P = 0.01 for baseline FN BMD, P = 0.02 for follow-up FN BMD). Increasing dietary riboflavin intake correlated with LS BMD and FN BMD in homozygotes for the MTHFR 'T' allele, which remained significant for FN after adjustment for confounders (r = 0.192, P = 0.036 for baseline; r = 0.186, P = 0.043 at follow-up) but not in the other genotypes. This raises the possibility that riboflavin intake and MTHFR genotype might interact to regulate BMD. Further work is required to determine if this association holds true for other populations and ethnic groups.

Biomarkers↗
PubMed2003

A new paradigm for drug discovery: integrating clinical, genetic, genomic and molecular phenotype data to identify drug targets.

Application of statistical genetics approaches to variations in mRNA transcript abundances in segregating populations can be used to identify genes and pathways associated with common human diseases. The combination of this genetic information with gene expression and clinical trait data can also be used to identify subtypes of a disease and the genetic loci specific to each subtype. Here we highlight results from some of our recent work in this area and further explore the many possibilities that exist in employing a more comprehensive genetics and functional genomics approach to the functional annotation of genomes, and in applying such methods to the validation of targets for complex traits in the drug discovery process.

Animals↗
PubMed1995

How can maximum likelihood methods reveal candidate gene effects on a quantitative trait?

Different maximum likelihood approaches were used to explore the role of candidate genes in the variability of quantitative trait Q1 while accounting for the effects of age, Q2, and Q3. Segregation analysis, under the class D regressive model, provides evidence for a Mendelian gene effect on the adjusted trait Q1. Results of gene mapping through lod-score analyses remain puzzling. Pairwise lod scores indicate a possible linkage with the candidate gene C5 which is excluded when using tightly linked informative marker loci. Finally, our combined segregation and linkage analysis clearly shows that a C5 linked gene is involved in Q1 variability. However, given the lod-score results within the C5 region, we postulate a more complex mechanism for Q1 than a single di-allelic C5 linked gene. The knowledge of the true model (C5 is MG1 and has three alleles) permits a partial explanation of our results. This study demonstrates the advantages of using complementary approaches to reveal the role of candidate genes in complex traits, and the value of simultaneous estimation of linkage and segregation parameters.

Alleles↗
PubMed1994

Variability and stability in cognitive abilities are largely genetic later in life.

The powerful quantitative genetic design of identical and fraternal twins reared apart (112 pairs) and matched twins reared together (111 pairs) was employed to assess the extent of genetic influence on individual differences in cognitive abilities during the last half of the life span. General cognitive ability yielded a heritability estimate of about .80 in two assessments 3 years apart as part of the Swedish Adoption/Twin Study of Aging. This is one of the highest heritabilities reported for a behavioral trait. Across the two ages, average heritabilities are about .60 for verbal tests, .50 for spatial and speed-of-processing tests, and .40 for memory tests. For general cognitive ability, the phenotypic stability across the 3 years is .92 and stable genetic factors account for nearly 90% this stability. These findings suggest that general cognitive ability is a reasonable target for research that aims to identify specific genes for complex traits.

Aging↗
PubMed2006

The idd4 locus displays sex-specific epistatic effects on type 1 diabetes susceptibility in nonobese diabetic mice.

The nonobese diabetic (NOD) mouse recapitulates many aspects of the pathogenesis of type 1 diabetes in humans, including inheritance as a complex trait. More than 20 Idd loci have been linked to type 1 diabetes susceptibility in NOD mice. Previously, we used linkage analysis of NOD crossed to the nonobese diabetes-resistant (NOR) strain and NOD congenic strains to map susceptibility to both spontaneous and cyclophosphamide-accelerated type 1 diabetes to the Idd4 locus on chromosome 11 that displayed a sex-specific effect on diabetes susceptibility. Here, we elucidate the complex genetic architecture of Idd4 by analysis of congenic strains on the NOD and NOR backgrounds. We previously refined Idd4.1 to 1.4 Mb and demonstrated an impact of this interval on type 1 interferon pathways in antigen-presenting cells. Here, we identify a second subregion, the 0.92 Mb Idd4.2 locus located telomeric to Idd4.1. Strikingly, Idd4.2 displayed a sex-specific, epistatic interaction with Idd4.1 in NOR.NOD congenic females that was not observed in syngenic males. Idd4.2 contains 29 genes, and promising candidates for the Idd4.2 effect on type 1 diabetes are described. These data demonstrate sex-dependent interaction effects on type 1 diabetes susceptibility and provide a framework for functional analysis of Idd4.2 candidate genes.

Animals↗
PubMed1994

Genetics and multiple sclerosis: an overview.

There is evidence to support the view that multiple sclerosis is a complex trait determined by both genetic and environmental factors. The genetic component is reflected in the higher rate of concordance in monozygotic versus dizygotic twins and in familial recurrence risk data. These data fit best with oligogenic hypotheses encompassing epistatic interactions. However, confirmation will require comprehensive linkage studies using techniques that can rapidly screen the entire genome. The number of families required to demonstrate the effects of a locus such as the major histocompatibility complex is very large.

Adult↗
PubMed2006

Personality traits in Sardinia: testing founder population effects on trait means and variances.

Potential founder population effects on personality trait means and variances were examined in a large, genetically homogeneous sample (N=5,669) from the Ogliastra, an isolated region within Sardinia, Italy. The Italian version of the Revised NEO Personality Inventory showed good psychometric properties: Internal consistency reliabilities ranged from 0.80 to 0.87; the factor structure replicated the American normative structure; and associations with education and gender replicated cross-cultural patterns. The hypothesis that mean trait levels in the Sardinian founder population would differ from mainland Italian values was not supported. Phenotypic variation in this founder population was within the range found in other cultures. However, the hypothesis of restricted phenotypic variation was supported for all five factors and 28 of the 30 facets when a Sardinian subsample matched on age, sex, and education was compared to a mainland Italian sample. The genetic homogeneity effect on the phenotypic expression of complex traits merits further exploration.

Analysis of Variance↗
PubMed2001

Genomics and atherosclerosis.

Recent progress in the human genome project allows us to study the genetic basis of complex traits such as atherosclerosis and diabetes. Among various approaches, a genetic approach such as affected sib-paired analysis and case-control study has successfully identified genes for susceptibility to Alzheimer's disease and diabetes. Several points to be considered are discussed for their successful application to athroscelorosis. In addition, functional genomic approaches based on powerful technology such as cDNA microarray and knockout mice allow us to identify genes and proteins involved in the complex biological (disease) process. As a successful example, a transgenic mice study of circadian rythm in transgenic mice is described.

Animals↗
PubMed2006

Model for mapping imprinted quantitative trait loci in an inbred F2 design.

The role of imprinting in shaping development has been ubiquitously observed in plants, animals, and humans. However, a statistical method that can detect and estimate the effects of imprinted quantitative trait loci (iQTL) over the genome has not been extensively developed. In this article, we propose a maximum likelihood approach for testing and estimating the imprinted effects of iQTL that contribute to variation in a quantitative trait. This approach, implemented with the EM algorithm, allows for a genome-wide scan for the existence of iQTL. This approach was used to reanalyze published data in an F(2) family derived from the LG/S and SM/S mouse strains. Several iQTL that regulate the growth of body weight by expressing paternally inherited alleles were identified. Our approach provides a standard procedure for testing the statistical significance of iQTL involved in the genetic control of complex traits.

Algorithms↗