Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “complex trait”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67Linked to original sources
PubMed1999

Why FRET over genomics?

Genetic information is being uncovered quickly and in vast amounts through the largely automated sequencing of genomes from all kinds of organisms. As this information becomes available, enormous challenges are emerging on three levels: first, functions will have to be assigned to individual gene products; second, factors that influence the expression level of these gene products will have to be identified; and third, allelic variants that act alone or in combination to give rise to complex traits will have to be characterized. Because of the sheer size of genomes, methods that can streamline or automate these processes are highly desirable. Fluorescence is an attractive readout for such high-throughput tasks because of the availability of equipment designed to detect light-emitting compounds with great speed and high capacity. The following is an overview of the achievements and potential of fluorescence resonance energy transfer (FRET) as applied in three areas of genomics: the identification of single-nucleotide polymorphisms, the detection of protein-protein interactions, and the genomewide analysis of regulatory sequences.

Animals↗
PubMed2001

Candidate genes and single nucleotide polymorphisms (SNPs) in the study of human disease.

The genomic revolution has generated an extraordinary resource, the catalog of variation within the human genome, for investigating biological, evolutionary and medical questions. Together with new, more efficient platforms for high-throughput genotyping, it is possible to begin to dissect genetic contributions to complex trait diseases, specifically examining common variants, such as the single nucleotide polymorphism (SNP). At the same time, these tools will make it possible to identify determinants of disease with the expectation of eventually, tailoring therapies based upon specific profiles. However, a number of methodological, practical and ethical issues must be addressed before the analysis of genetic variation becomes a standard of clinical medicine. The currents of variation in human biology are reviewed here, with a specific emphasis on future challenges and directions.

Base Sequence↗
PubMed2004

Genetic dissection of learning and memory in mice.

In this minireview, we discuss different strategies to dissect genetically the keystones of learning and memory. First, we broadly sketch the neurogenetic analysis of complex traits in mice. We then discuss two general strategies to find genes affecting learning and memory: candidate gene studies and whole genome searches. Next, we briefly review more recently developed techniques, such as microarrays and RNA interference. In addition, we focus on gene-environment interactions and endophenotypes. All sections are illustrated with examples from the learning and memory field, including a table summarizing the latest information about genes that have been shown to have effects on learning and memory.

Animals↗
PubMedDate not supplied

Mapping in the sequencing era.

The present phase of the Human Genome Project is concerned with sequencing. The shift of emphasis has left an impression that mapping is in some sense complete or finished. On the contrary, faced with the challenges of mapping genes for complex traits and efforts to understand recombination and other biological processes, the need for accurate integrated metric maps is greater than ever. Furthermore, sequencing could be regarded as merely a way of improving the map, since the most useful 'end product' of the sequencing effort must be the annotated sequence that gives precise physical coordinates for markers and expressed sequences. Integration of both location and functional information, the latter provided by homology, expression and other functional studies, is the main target for the future.

Chromosome Mapping↗
PubMedDate not supplied

Complex inheritance and localizing disease genes.

Most methods for localizing genes underlying complex traits work under the implicit or explicit assumption of a single disease gene with the possible exception of heterogeneity, that is, different disease genes in different families. We discuss current single-locus and multi-locus methods. Novel approaches are proposed that take into account all marker loci over the genome. A simple example is given for an unconventional statistic, i.e. the mean of allele sharing over all markers on a chromosome.

Chromosome Mapping↗
PubMedDate not supplied

Gene-environment interactions and the affected-sib-pair designs.

In genetic mapping of complex traits, the affected-sib-pair method (ASP) and the transmission disequilibrium test (TDT) are two methods of choice. The major appeal of both ASP and TDT is that they do not require the knowledge of mode of inheritance underlying the trait in question. The relative ease and economy for data collection also is the reason for their popularity. The basic idea of the ASP is to identify genes or chromosomal regions through identifying genetic similarity based on phenotypical similarity. TDT, on the other hand, detects susceptibility genes through detecting unusual transmission patterns in families. Since phenotypic similarity can also be caused by environmental similarity, we investigate how the presence of gene-environment interaction (GEI) affects the power of both methods. For a simple one-locus-one-risk-factor model, our results indicate that, in the presence of GEI, methods developed based on marginal penetrance functions (i.e. ignoring the risk factor) can give spurious results. The triangular restriction on allele-sharing probability may no longer be valid. If the environment effect is strong, using exposure-discordant affected sib pairs may have advantage over other designs. Above all, a genetic model involving both genetic and environmental factors behaves differently from a single-locus genetic model.

Analysis of Variance↗
PubMed1998

Molecular variant of the human paraoxonase/arylesterase gene is associated with central retinal vein occlusion in the Japanese population.

Central retinal vein occlusion (CRVO) is a complex trait caused by a number of local and systemic factors. Among the latter, atherosclerosis has been attributed a major pathogenic role. Recently, the paraoxonase/arylesterase (PONA) enzyme has been implicated in the pathogenesis of atherosclerosis. There is a 10- to 40-fold variability in the activity of this enzyme among individuals. This variability is due to the presence of an A/G polymorphism in the coding region of the gene. The A and G alleles code for glutamine (A genotype) and arginine (B genotype), respectively. We determined the PONA genotypes and alleles in 42 patients with CRVO and in 45 control subjects of the Japanese population. The distribution of AA, AB and BB genotypes were 9.6, 45.2 and 45.2%, respectively, in the patients and 26.7, 53.3 and 20.0% in the control subjects, respectively (p < 0.05). The A allele frequency was 0.32 in patients and 0.53 in controls (p < 0.01). In conclusion, molecular variants of the PONA gene are involved in the predisposition to CRVO. Further studies are needed to characterize the molecular mechanism by which the PONA enzyme is involved in atherosclerosis.

Aged↗
PubMed2001

Y chromosome binary markers to study the high prevalence of males in Sardinian centenarians and the genetic structure of the Sardinian population.

We have analyzed a sample of 40 centenarians and 116 young controls from Sardinia, with a set of new Y chromosome binary markers, to evaluate if Y chromosome genes are involved in the high prevalence of males among centenarian Sardinians (1/2 vs. 1/4 in other populations studied). The results indicate that none of the seven lineages that account for >97% of the Y chromosome diversity in Sardinia provide an advantage with respect to the extreme longevity. However, our results, although based on the male-specific Y chromosome polymorphisms, give a clear profile of the pattern of genetic variability in Sardinia. Indeed they indicate that the Sardinian population had two main founder populations that have evolved in isolation for at least the last 5,000 years. These findings set the stage for future studies on longevity and other complex traits in Sardinia.

Aged↗
PubMed2002

Log-linear models for gene mapping with affected sib pair data.

In genome-wide screens of genetic marker loci, non-mendelian inheritance of a marker is taken to indicate its vicinity to a disease locus. Heritable complex traits are thought to be under the influence of multiple possibly interacting susceptibility loci yet the most frequently used methods of linkage and association analysis focus on one susceptibility locus at a time. Here we introduce log-linear models for the joint analysis of multiple marker loci and interaction effects between them. Our approach focuses on affected sib pair data and identical by descent (IBD) allele sharing values observed on them. For each heterozygous parent, the IBD values at linked markers represent a sequence of dependent binary variables. We develop log-linear models for the joint distribution of these IBD values. An independence log-linear model is proposed to model the marginal means and the neighboring interaction model is advocated to account for associations between adjacent markers. Under the assumption of conditional independence, likelihood methods are applied to simulated data containing one or two susceptibility loci. It is shown that the neighboring interaction log-linear model is more efficient than the independence model, and incorporating interaction in the two-locus analysis provides increased power and accuracy for mapping of the trait loci.

Alleles↗
PubMed2003

Genome sharing in large pedigrees: multiple imputation of ibd for linkage detection.

Our objective is the development of robust methods for assessment of evidence for linkage of loci affecting a complex trait to a marker linkage group, using data on extended pedigrees. Using Markov chain Monte Carlo (MCMC) methods, it is possible to sample realizations from the distribution of gene identity by descent (IBD) patterns on a pedigree, conditional on observed data YM at multiple marker loci. Measures of gene IBDW which capture joint genome sharing in extended pedigrees often have unknown and highly skewed distributions, particularly when conditioned on marker data. MCMC provides a direct estimate of the distribution of such measures. Let W be the IBD measure from data YM, and W* the IBD measure from pseudo-data Y*M simulated with the same data availability and genetic marker model as the true data YM, but in the absence of linkage. Then measures of the difference in distributions of W and W* provide evidence for linkage. This approach extracts more information from the data YM than either comparison to the pedigree prior distribution of W or use of statistics that are expectations of W given the data YM. A small example is presented.

Chromosome Mapping↗
PubMed2006

Multilocus linkage analysis of affected sib pairs.

OBJECTIVE: The conventional affected sib pair methods evaluate the linkage information at a locus by considering only marginal information. We describe a multilocus linkage method that uses both the marginal information and information derived from the possible interactions among several disease loci, thereby increasing the significance of loci with modest effects. METHODS: Our method is based on a statistic that quantifies the linkage information contained in a set of markers. By a marker selection-reduction process, we screen a set of polymorphisms and select a few that seem linked to disease. RESULTS: We test our approach on genome scan data for inflammatory bowel disease (InfBD) and on simulated data. On real data we detect 6 of the 8 known InfBD loci; on simulated data we obtain improvements in power of up to 40% compared to a conventional single-locus method. CONCLUSION: Our extensive simulations and the results on real data show that our method is in general more powerful than single-locus methods in detecting disease loci responsible for complex traits. A further advantage of our approach is that it can be extended to make use of both the linkage and the linkage disequilibrium between disease loci and nearby markers.

Genetic Linkage↗
PubMed2000

Genome-wide linkage analysis of systolic and diastolic blood pressure: the Québec Family Study.

BACKGROUND: Blood pressure (BP), an important risk factor for coronary heart disease, is a complex trait with multiple genetic etiologies. While some loci affecting BP variation are known (eg, angiotensinogen), there are likely to be novel signals that can be detected with a genome scan approach. METHODS AND RESULTS: A genome-wide scan was performed in 125 random and 81 obese families participating in the Québec Family Study. A multipoint variance-components linkage analysis of 420 markers (353 microsatellites and 67 restriction fragment length polymorphisms) revealed several signals (P:<0.0023) for systolic BP on 1p (D1S551, ATP1A1), 2p (D2S1790, D2S2972), 5p (D5S1986), 7q (D7S530), 8q (CRH), and 19p (D19S247). Suggestive evidence (0.0023<P:<0.01) was found on 3q, 10p, 12p, 14q, and 22q. The results were encouraging for HSD3B1 (P:<0.03), AGT (P:<0.03), ACE (P:<0.02), and adipsin (P:<0.005) but null with regard to other candidates (eg, renin, and glucocorticoid and adrenergic receptors). CONCLUSIONS: Multiple linkage regions support the notion that risk for hypertension is due to multiple (ie, oligogenic) susceptibility loci. Comparisons across the complete, random, and obese samples suggest that some regions are specific to BP and others may involve obesity (eg, pleiotropy, epistasis, or gene-environment interaction). Some of these areas harbor known candidates. Others involve novel regions, some of which replicate previous reports and provide a focus for future studies to identify novel genes that influence interindividual variation in BP.

Age Distribution↗
PubMed2002

Genome scan among Nigerians linking blood pressure to chromosomes 2, 3, and 19.

An understanding of the genetic influences on hypertension would help unravel the pathophysiology of this complex disorder and improve our understanding of causal mechanisms. Contemporary technology makes it possible to examine enough genetic markers to support a generalized search across the entire genome for candidate regions. In the present study, a family set was recruited from southwest Nigeria, and 378 microsatellite markers were typed on 792 individuals in 196 families. Multipoint variance component analysis identified linkage signals (logarithm of the odds [LOD] 1.74, P<0.0023) for systolic blood pressure on 19p (D19S714) and 19q (D19S246), whereas for diastolic blood pressure, linkage was observed on 2p (D2S1790), 3p (D3S1304), 5q (D5S1462), 7p (D7S3046), 7q (D7S821), and 10q (D10S1221). Other regions of interest (1.18<LOD<1.74, 0.0023<P<0.01) were found on chromosomes 1, 6, 8, 9, and 11. These results provide additional evidence of linkage between blood pressure and several genomic regions reported in previous studies. Some of these regions additionally harbor hypertension candidate genes. Although evidence of linkage for blood pressure has been very slow to accumulate, even in comparison to other complex traits, the sum of current evidence appears to implicate, in particular, 2p, 3p, and 19p. Study designs that make it possible to confirm these results with association analysis and narrow the genomic interval are needed in order to make progress in this field.

Adolescent↗
PubMed2004

Genome-wide scan for blood pressure suggests linkage to chromosome 11, and replication of loci on 16, 17, and 22.

Hypertension was one of the first complex traits to be studied and is thought to be influenced by polygenic and multiple environmental risk factors. Several genomic studies have found suggestive logarithm of odds (LOD) scores for either blood pressure or essential hypertension, but few loci have been replicated. In this study, we performed a genome-wide linkage analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP) on 1109 white female dizygotic twin pairs from the TwinsUK registry in London. Multipoint linkage analysis replicated the locations of 3 previously reported linkage peaks: on chromosome 16 at 65 cM (LOD 0.8 for SBP and 1.8 for DBP); on chromosome 17 at 70 cM (LOD 1.8 SBP); and at 35 cM on chromosome 22 (LOD 0.97 SBP and 0.99 DBP). Results from multipoint analysis showed 1 novel suggestive linkage for SBP (multipoint LOD 2.28; 2-point P=0.0007) at 35 cM on chromosome 11. Results were similar when those on blood pressure medication were excluded. These are encouraging results for hypertensive research and demonstrate that despite past disappointments, linkage studies can be used to replicate regions from other studies and potentially discover new genetic risk factors of moderate to large effect size. Considering the differences in selection and ascertainment of the previous linkage studies, these results also suggest that some quantitative trait loci are likely to influence the normal range of blood pressure and clinical hypertension, whereas others will be specific to each trait. Future studies should focus on the fine mapping of these replicated regions, which include potential candidate genes.

Adult↗
PubMed1999

Genome scan for blood pressure loci in mice.

Hypertension is a complex trait of unknown cause in humans. Mice of the inbred strain BPH/2 serve as a rodent model of human hypertension and display elevated blood pressure compared with the hypotensive strain BPL/1. An F2 intercross of BPH/2 and BPL/1 and 2 backcrosses of BPL/1 with Mus spretus were used to perform interval linkage mapping for systolic blood pressure in a genome scan. Significant linkage was observed in the F2s on chromosome 10 (logarithm of the odds score [LOD]=4.9) and on chromosome 13 in the M spretus backcross (LOD=3.3), with additional suggestive LODs on chromosomes 2, 6, 8, and 18. In addition, several suggestive linkages were observed for phenotypes associated with human hypertension. Our study is the first reported genome-wide linkage scan for blood pressure genes in the mouse.

Alleles↗
PubMed2006

Contribution of clinical correlates and 13 C-reactive protein gene polymorphisms to interindividual variability in serum C-reactive protein level.

BACKGROUND: Serum C-reactive protein (CRP) level is a heritable complex trait that predicts incident cardiovascular disease. We investigated the clinical and genetic sources of interindividual variability in serum CRP. METHODS AND RESULTS: We studied serum CRP in 3301 Framingham Heart Study (FHS) participants (mean age 61 years, 53% women). Twelve clinical covariates explained 26% of the variability in CRP level, with body mass index alone explaining 15% (P<0.0001) of the variance. To investigate the influence of genetic variation at the CRP gene on CRP levels, we first constructed a dense linkage disequilibrium map for common single-nucleotide polymorphisms (SNPs) spanning the CRP locus (1 SNP every 850 bases, 26 kilobase [kb] genomic region). Thirteen CRP SNPs were genotyped in 1640 unrelated FHS participants with measured CRP levels. After adjustment for clinical covariates, 9 of 13 SNPs were associated with CRP level (P<0.05). To account for correlation among SNPs, we conducted forward stepwise selection among all 13 SNPs; a triallelic SNP (rs3091244) remained associated with CRP level (stepwise P<0.0001). The triallelic SNP (C-->T-->A; allele frequencies 62%, 31%, and 7%), located in the promoter sequence, explained 1.4% of total serum CRP variation; haplotypes harboring the minor T and A alleles of this SNP were associated with higher CRP level (haplotype P=0.0002 and 0.004). CONCLUSIONS: In our community-based sample, clinical variables explained 26% of the interindividual variation in CRP, whereas a common triallelic CRP SNP contributed modestly. Studies of larger samples are warranted to assess the association of genetic variation in CRP and risk of cardiovascular disease.

Age Factors↗
PubMed2001

Genetic locus in mice that blocks development of atherosclerosis despite extreme hyperlipidemia.

The genes contributing to the common forms of atherosclerosis are largely unknown. One approach to dissecting complex traits such as atherosclerosis is to use animal models, such as the mouse, to map and characterize the genetic loci involved. We now report the identification of a locus for aortic lesion formation on mouse chromosome 6 that exhibits a highly significant lod score of 6.7 in a genetic cross between the susceptible strain, C57BL/6J, and the resistant strain, CAST/Ei. The locus was confirmed by constructing a congenic strain in which the chromosome 6 segment from CAST/Ei was transferred to a C57BL/6J background in a series of backcrosses. The congenic strain was almost completely resistant to diet-induced atherosclerosis. The chromosome 6 segment was also transferred onto the background of an LDL receptor-null mutation and resulted again in almost complete resistance to aortic lesion formation. This locus also influenced insulin levels but did not affect plasma lipoprotein levels, blood pressure, or body fat. The chromosome 6 gene, which we call Artles (for arterial lesions), did not affect endothelial cell responses to oxidized LDL, but lesion formation was partially reduced through bone marrow transplantation. The locus contains the candidate gene peroxisome proliferator-activated receptor-gamma, and the congenic mice exhibited significantly reduced expression of peroxisome proliferator-activated receptor-gamma.

Animals↗
PubMed1997

Genetics of native airway responsiveness in mice.

The inbred mouse represents a powerful tool for dissecting both simple and complex traits. Genetic studies in the mouse should identify disease genes acting in the same biochemical pathway as in the human. Problems associated with genetic heterogeneity, inability to control environmental conditions, lack of an abundant supply of genetic markers, and ethical considerations regarding human genetic crosses are but some of the reasons to study airway responsiveness in the mouse. At present, only a handful of studies have shed light on the genetics of airway responsiveness; even fewer have sought to identify genetic loci that regulate this trait. It is clear that both genetic and environmental factors influence the asthma phenotype and that genetic background is an important consideration when interpreting segregation analysis data. The controversy over the specific mode of inheritance and number and location of quantitative trait loci (QTL) illustrates the need for additional studies. However, given that numerous candidate loci implicated in the pathogenesis of asthma map near QTLs identified in two recent studies, and given the considerable homology between the human and mouse genome, a targeted search for susceptibility genes is warranted in the human. Ideally, these regions will demonstrate linkage in humans. Thus, further work remains to be done to create detailed maps of the regions of linkage in the mouse, and to ultimately identify gene(s) that modify airway responsiveness. mice.

Animals↗