Cladistic structure within the human Lipoprotein lipase gene and its implications for phenotypic association studies

The False Dawn of Polygenic Risk Scores for Human Disease Prediction

Polygenic risk scores (PRSs) are being constructed for many diseases and are presented today as a promising avenue in the field of human genetics. These scores aim at predicting the risk of developing a disease by leveraging the many genome-wide association studies (GWAS) conducted during the two last decades. Important investments are being made to improve score estimates by increasing GWAS sample sizes, by developing more sophisticated methods, and by proposing different corrections for potential biases. PRSs have entered the market with direct-to-consumer companies proposing to compute them from saliva samples and even recently to help parents select the healthiest embryos. In this paper, we recall how PRSs arose and question the credit they are given by revisiting underlying assumptions in light of the history of human genetics and by comparing them with estimated breeding values (EBVs) used for selection in livestock.

Latitudinal Clines of the Human Vitamin D Receptor and Skin Color Genes

The well-documented latitudinal clines of genes affecting human skin color presumably arise from the need for protection from intense ultraviolet radiation (UVR) vs. the need to use UVR for vitamin D synthesis. Sampling 751 subjects from a broad range of latitudes and skin colors, we investigated possible multilocus correlated adaptation of skin color genes with the vitamin D receptor gene (VDR), using a vector correlation metric and network method called BlocBuster. We discovered two multilocus networks involving VDR promoter and skin color genes that display strong latitudinal clines as multilocus networks, even though many of their single gene components do not. Considered one by one, the VDR components of these networks show diverse patterns: no cline, a weak declining latitudinal cline outside of Africa, and a strong in- vs. out-of-Africa frequency pattern. We confirmed these results with independent data from HapMap. Standard linkage disequilibrium analyses did not detect these networks. We applied BlocBuster across the entire genome, showing that our networks are significant outliers for interchromosomal disequilibrium that overlap with environmental variation relevant to the genes’ functions. These results suggest that these multilocus correlations most likely arose from a combination of parallel selective responses to a common environmental variable and coadaptation, given the known Mendelian epistasis among VDR and the skin color genes.

Vascular endothelial growth factor (VEGF) gene polymorphisms and breast cancer risk in Punjabi population from North West India

The purpose of this study was to evaluate the association of seven VEGF promoter polymorphisms with breast cancer risk in Punjabi population from North West India. We screened DNA samples of 102 sporadic breast cancer patients and 102 unrelated healthy, gender, and age-matched individuals for seven VEGF promoter polymorphisms [-417 C/T (rs833062), -172 C/A (rs59260042), -165 C/T (rs79469752), -160 C/T, -152 G/A (rs13207351), -141 A/C (rs28357093) and -116 G/A (rs1570360)] by direct sequencing. The frequency of GG, GA, and AA genotype of -152 G/A polymorphism was 26.47 vs 38.34%, 46.08 vs 51.96%, and 27.45 vs 9.80%, in patients and controls, respectively. VEGF -152 AA genotype was significantly associated with increased risk for breast cancer (OR = 4.04, 95%CI, 1.69-9.68, p = 0.001; recessive model OR = 3.48, 95%CI, 1.59-7.63, p = 0.001). For VEGF -116 G/A polymorphism, G and A allele frequencies were 65.2 vs 76.47% and 34.8 vs 23.53% in patients and controls, respectively. Individuals having -116 AA genotype (OR = 3.40; 95%CI, 1.24-9.37; p = 0.014) and A allele (OR = 1.73; 95%CI, 1.12-2.67; p = 0.012) were associated with increased risk for breast cancer. VEGF -165 C/T and -141 A/C polymorphisms were associated with reduced risk for breast cancer. There was significantly decreased frequency of CT genotype (4.90 vs 18.63%; p = 0.002) and T allele (2.45 vs 9.31%; p = 0.003) of -165 C/T polymorphism among breast cancer patients as compared to controls. VEGF -141 A and C allele frequency were 96.57 vs 91.18% and 3.43 vs 8.82% in patients and controls, respectively. Significant reduced risk for breast cancer was observed with AC genotype (OR = 0.34, 95%CI, 0.14-0.86; p = 0.019) and C allele (OR = 0.37; 95%CI, 0.15-0.89; p = 0.023) of -141 A/C polymorphism. We did not observe association of VEGF -417 T/C, -172 C/A, -160 C/T polymorphisms with breast cancer risk in the studied subjects (p > 0.05). The VEGF -152 G/A and -116 G/A polymorphisms were found to be significantly associated with increased risk for breast cancer while -165 C/T and -141 A/C polymorphisms were found to be associated with decreased risk for breast cancer in Punjabi population from North West India.

Phylogenetic analyses: a brief introduction to methods and their application

Phylogenetic analysis of molecular sequence data plays an increasingly important role in clinical medicine, both in the emerging field of molecular epidemiology and in the rational design of new therapeutic agents. The aims of this review are to introduce some of the methods used to construct phylogenetic trees, to illustrate some of the pitfalls that can introduce artifactual results and to speculate on the long-term importance of this area of computational biology in clinical medicine.

A nonsynonymous polymorphism of IRAK4 associated with increased prevalence of gram-positive infection and decreased response to toll-like receptor ligands

Mutations in IRAK4 have been associated with recurrent Gram-positive infections in children. Given the central role of IRAK4 in innate immunity signaling, we hypothesized that common genetic variants of IRAK4 may be associated with prevalence of Gram-positive infection in critically ill adults. Haplotype clade tag single nucleotide polymorphisms (SNPs) of the IRAK4 gene were selected and genotyped in a cohort of 1,029 critically ill patients with systemic inflammatory response syndrome (SIRS). We found that a haplotype clade tagged by the A allele of the htSNP G29429A (Ala428Thr) was associated with increased relative risk of Gram-positive infection at admission to ICU (RR = 1.2, p < 0.05). Furthermore, the 29429A allele was associated with decreased lymphoblastoid cell response to CpG (as measured by IL-6 production) (raw values ± 95% CI 40.3 ± 32.3 vs. 85.8 ± 29.4 pg/ml; log-transformed values ± 95% CI 1.13 ± 0.37 vs. 1.55 ± 0.18, p < 0.04). We also found that IRAK4-deficient fibroblasts transfected with an IRAK4 expression plasmid containing the 29429A allele produced less IL-6 in response to lipopolysaccharide (p = 0.07). Our data suggest that the IRAK4 haplotype clade marked by 29429A (428Thr) alters susceptibility to Gram-positive bacteria, by decreasing cellular response to TLR ligands.

Responses to historical climate change identify contemporary threats to diversity in Dodecatheon

Anthropogenic climate change may threaten many species with extinction. However, species at risk today survived global climate change in recent geological history. Describing how habitat tracking and adaptation allowed species to survive warming since the end of the Pleistocene can indicate the relative importance of dispersal and natural selection during climate change. By taking this historical perspective, we can identify how contemporary climate change could interfere with these mechanisms and threaten the most vulnerable species. We focused on a group of closely related plant species in the genus Dodecatheon (Primulaceae) in eastern North America. Two rare species (Dodecatheon amethystinum and Dodecatheon frenchii) that are endemic to patchy cool cliffs may be glacial relicts whose ranges constricted following the last glacial maximum. Alternatively, these species may be extreme ecotypes of a single widespread species (Dodecatheon meadia) that quickly adapted to microclimatic differences among habitats. We test support for these alternative scenarios by combining ecophysiological and population genetic data at a regional scale. An important ecophysiological trait distinguishes rare species from D. meadia, but only a few northern populations of D. amethystinum are genetically distinctive. These relict populations indicate that habitat tracking did occur with historical climate change. However, relatively stronger evidence for isolation by distance and admixture suggests that local adaptation and genetic introgression have been at least as important. The complex response of Dodecatheon to historical climate change suggests that contemporary conservation efforts should accommodate evolutionary processes, in some cases by restoring genetic connectivity between ecologically differentiated populations.

Determination of lipoprotein lipase activity in post heparin plasma of streptozotocin-induced diabetic rats by high-performance liquid chromatography with fluorescence detection

The activity of lipoprotein lipase (LPL), an enzyme responsible for lipoprotein metabolism, would vary in diseases and metabolic disorders. For determination of LPL activity, a highly sensitive high performance liquid chromatography (HPLC) method using a fluorescent reagent, 4-nitro-7-piperazino-2,1,3-benzoxadiazole (NBD-PZ) was applied to determinate the oleic acid (OA) generated from triolein by LPL activity without multiple solvents extraction step. We studied the optimal conditions of the reaction including the effect of emulsifiers, deproteinizing solvents, and the concentration of bovine serum albumin (BSA). Ten millimolar concentrations of triolein, 5% of BSA, 1% of Gum arabic (GA), and acetonitrile showed the optimum conditions for measuring the LPL activity. The accuracy values for the determination of LPL activity in 10 microL of rat post heparin plasma were 108.73 approximately 114.36%, and the intra- and inter-day precision values were within 1.28% and 2.91%, respectively. The limit of detection was about 4.53 nM (signal-to-noise ratio 3). The proposed method was applied to determination of LPL activity in post heparin plasma of normal and streptozotocininduced diabetic rats associated with 52.3% reduction. The established assay system could be used for determining LPL activity in different physiological and pathological conditions to clarify the relationship between LPL activity and diabetes mellitus.

On transferability of genome-wide tagSNPs

The question of tagging single nucleotide polymorphism (tagSNP) transferability is an important one because many ongoing and upcoming Genome-Wide Association studies rely critically upon the validity, and practical feasibility of using a universal core set of tagSNPs. A series of recent studies analyzed performance of tagSNPs selected based on the HapMap. While these studies showed largely satisfactory transferability of the tagSNPs, they also reported that the level of transferability varies, substantively sometimes, especially when tagSNPs selected in one population were used in another distant population. We present a review of the literature about where and why tagSNP transferability may become a problem and suggest research directions that may help the resolution.

Characterization of LD structures and the utility of HapMap in genetic association studies

Observed distribution of and variation in linkage disequilibrium (LD) with respect to the evolution history and disease transmission in a population is the driving force behind the current wave of genome-wide association (GWA) studies of complex human diseases. An extensive literature covers topics from haplotype analysis that utilizes local LD structures in candidate genes and regions to genome-wide organization of LD blocks (neighborhood) that led to the development of International HapMap Project and panels of "tagSNPs" used by current GWA studies. In this chapter, we examine the scenarios where each of the major types of analysis methods may be applicable and where the current popular genotyping platforms for GWA might come short. We discuss current association analysis methods by emphasizing their reliance on the local LD structures or the global organization of the LD structures, and highlight the need to consider individual marker information content in large-scale association mapping.

Haplotype-association analysis

Association methods based on linkage disequilibrium (LD) offer a promising approach for detecting genetic variations that are responsible for complex human diseases. Although methods based on individual single nucleotide polymorphisms (SNPs) may lead to significant findings, methods based on haplotypes comprising multiple SNPs on the same inherited chromosome may provide additional power for mapping disease genes and also provide insight on factors influencing the dependency among genetic markers. Such insights may provide information essential for understanding human evolution and also for identifying cis-interactions between two or more causal variants. Because obtaining haplotype information directly from experiments can be cost prohibitive in most studies, especially in large scale studies, haplotype analysis presents many unique challenges. In this chapter, we focus on two main issues: haplotype inference and haplotype-association analysis. We first provide a detailed review of methods for haplotype inference using unrelated individuals as well as related individuals from pedigrees. We then cover a number of statistical methods that employ haplotype information in association analysis. In addition, we discuss the advantages and limitations of different methods.

Dopamine genes and schizophrenia: case closed or evidence pending?

The dopamine hypothesis of schizophrenia (SZ) has motivated a large number of genetic association studies but few if any dopaminergic (DA) polymorphisms are accepted as credible risk factors at present. To evaluate whether dopamine-related genes have been investigated adequately, we surveyed public genetic databases and published SZ association studies with regard to 14 conventional DA genes and 7 selected dopamine-interacting proteins. We estimate that 325 polymorphisms would be required to evaluate the impact of common variation on SZ risk among Caucasian samples. To date, 98 polymorphisms have been analyzed in published association studies. We estimate that only 19 of these variations have been evaluated in samples with at least 50% power to detect an association of the effect size commonly found in genetically complex disorders. While it is possible that DA genes do not harbor genetic risk factors for SZ, our review suggests that satisfactory conclusions for most genes cannot be drawn at present. Whole-genome association studies have begun to fill this void, but additional analyses are likely to be needed. Recommendations for future association studies include analysis of adequately powered samples, judiciously selected polymorphisms, multiple ethnic groups, and concurrent evaluation of function at associated single-nucleotide polymorphisms.

GENETICS AND RECENT HUMAN EVOLUTION

Starting with "mitochondrial Eve" in 1987, genetics has played an increasingly important role in studies of the last two million years of human evolution. It initially appeared that genetic data resolved the basic models of recent human evolution in favor of the "out-of-Africa replacement" hypothesis in which anatomically modern humans evolved in Africa about 150,000 years ago, started to spread throughout the world about 100,000 years ago, and subsequently drove to complete genetic extinction (replacement) all other human populations in Eurasia. Unfortunately, many of the genetic studies on recent human evolution have suffered from scientific flaws, including misrepresenting the models of recent human evolution, focusing upon hypothesis compatibility rather than hypothesis testing, committing the ecological fallacy, and failing to consider a broader array of alternative hypotheses. Once these flaws are corrected, there is actually little genetic support for the out-of-Africa replacement hypothesis. Indeed, when genetic data are used in a hypothesis-testing framework, the out-of-Africa replacement hypothesis is strongly rejected. The model of recent human evolution that emerges from a statistical hypothesis-testing framework does not correspond to any of the traditional models of human evolution, but it is compatible with fossil and archaeological data. These studies also reveal that any one gene or DNA region captures only a small part of human evolutionary history, so multilocus studies are essential. As more and more loci became available, genetics will undoubtedly offer additional insights and resolutions of human evolution.

Association studies testing for risk for late-onset Alzheimer's disease with common variants in the beta-amyloid precursor protein (APP)

Linkage studies have suggested a susceptibility locus for late-onset Alzheimer's disease (LOAD) on chromosome 21. A functional candidate gene in this region is the beta-amyloid precursor protein (APP) gene. Previously, coding mutations in APP have been associated with early onset Alzheimer's Disease (EOAD). Three copies of APP are associated with AD pathology in Down's syndrome and in EOAD, suggesting that overexpression of APP may be a risk factor for LOAD. Although APP is a strong functional and positional candidate, to date there has been no thorough investigation using a dense map of SNPs across the APP gene. In order to investigate the role of common variation in the APP gene in the risk of LOAD, we genotyped 44 SNPs, spanning 300 kb spanning the entire gene, in a large case-control series of 738 AD cases and 657 healthy controls. The SNPs showed no association in genotypic or allelic tests, even after stratification for presence or absence of the APOE 4 allele. Haplotype analysis also failed to reveal significant association with any common haplotypes. These results suggest that common variation in the APP gene is not a significant risk factor for LOAD. However, we cannot rule out the possibility that multiple rare variants that increase APP expression or Abeta production might influence the risk for LOAD.

Human recombination rates are increased around accelerated conserved regions—evidence for continued selection?

MOTIVATION

We hypothesized that recombination rates might be increased at genetic loci that are subject to more intense selection. Here, we test this hypothesis by using a recently published set of accelerated conserved regions and fine-scale recombination rate estimates provided by the HapMap project.

RESULTS

We observed that fine-scale recombination rates are increased around conserved noncoding regions that show accelerated evolution in human or chimp, as compared to noncoding regions showing accelerated evolution in mouse and those being conserved between human and fugu. Recombination rates around hominid accelerated conserved regions (ACRs) are furthermore increased as compared to exonic regions. On the other hand, GC-content is reduced around ACRs, excluding a major confounding influence of GC-content on the observed variation in recombination rate.

CONCLUSION

Our observations indicate that selection intensity could be an important determinant of local recombination rate variation and that continued positive selection might act at many ACR loci. Alternatively, a confounding factor needs to be found that causes a congruent signal in recombination rate estimates based on human polymorphism data and in the comparative genomic data. Researchers who consider the explanation involving selection as more likely may expect more common functional sequence variants at ACRs in genetic association studies.

Generalized genomic distance-based regression methodology for multilocus association analysis

Large-scale, multilocus genetic association studies require powerful and appropriate statistical-analysis tools that are designed to relate genotype and haplotype information to phenotypes of interest. Many analysis approaches consider relating allelic, haplotypic, or genotypic information to a trait through use of extensions of traditional analysis techniques, such as contingency-table analysis, regression methods, and analysis-of-variance techniques. In this work, we consider a complementary approach that involves the characterization and measurement of the similarity and dissimilarity of the allelic composition of a set of individuals' diploid genomes at multiple loci in the regions of interest. We describe a regression method that can be used to relate variation in the measure of genomic dissimilarity (or "distance") among a set of individuals to variation in their trait values. Weighting factors associated with functional or evolutionary conservation information of the loci can be used in the assessment of similarity. The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates. In addition, the proposed method actually encompasses both single-locus and haplotype-phylogeny analysis methods, which are two of the most widely used approaches in genetic association analysis. We showcase the method with data described in the literature. Ultimately, our method is appropriate for high-dimensional genomic data and anticipates an era when cost-effective exhaustive DNA sequence data can be obtained for a large number of individuals, over and above genotype information focused on a few well-chosen loci.

Measuring marker information content by the ambiguity of block boundaries observed in dense SNP data

Recent studies have noted that the boundary of common haplotype blocks in hapmap constructions involve a certain degree of ambiguity, and so do the resulting "tagSNPs". Here, we report how to address this issue at the level of individual SNP markers. We introduce a measure called the marker ambiguity score (MAS), and evaluate its utility by simulation studies based on a real dataset of 2949 SNPs spanning a region of 56.1M bp. We show that the MAS method can be used to assess the level of boundary ambiguity caused by varying ethnic background, sample sizes for hapmap construction, and disease aggregation. We find a striking difference in overall patterns of block boundary distributions in two ethnic groups (blacks and whites), and subtle changes in block structures that agree with the evolutionary history of the two populations. Our analyses suggest that a sample size of 200 or more subjects is probably needed for "stable" hapmap constructions. In addition, we demonstrate that there are subtle changes in block boundaries in hapmaps constructed in disease populations versus normal controls. This approach can quantify the information content of individual markers in the context of highly dense SNP data, which may have important implications in designing efficient genome-wide association mapping projects.

Trick or treat: the effect of placebo on the power of pharmacogenetic association studies

The genetic mapping of drug-response traits is often characterised by a poor signal-to-noise ratio that is placebo related and which distinguishes pharmacogenetic association studies from classical case-control studies for disease susceptibility. The goal of this study was to evaluate the statistical power of candidate gene association studies under different pharmacogenetic scenarios, with special emphasis on the placebo effect. Genotype/phenotype data were simulated, mimicking samples from clinical trials, and response to the drug was modelled as a binary trait. Association was evaluated by a logistic regression model. Statistical power was estimated as a function of the number of single nucleotide polymorphisms (SNPs) genotyped, the frequency of the placebo 'response', the genotype relative risk (GRR) of the response polymorphism, the strategy for selecting SNPs for genotyping, the number of individuals in the trial and the ratio of placebo-treated to drugtreated patients. We show that: (i) the placebo 'response' strongly affects the statistical power of association studies -- even a highly penetrant drug-response allele requires at least a 500-patient trial in order to reach 80 per cent power, several-fold more than the value estimated by standard tools that are not calibrated to pharmacogenetics; (ii) the power of a pharmacogenetic association study depends primarily on the penetrance of the response genotype and, when this penetrance is fixed, power decreases for larger placebo effects; (iii) power is dramatically increased when adding markers; (iv) an optimal study design includes a similar number of placebo- and drugtreated patients; and (v) in this setting, straightforward haplotype analysis does not seem to have an advantage over single marker analysis.

High-resolution characterization of linkage disequilibrium structure and selection of tagging single nucleotide polymorphisms: application to the cholesteryl ester transfer protein gene

Full characterization of intragenic variation may improve candidate gene associations. This study selected tagging (t) single nucleotide polymorphisms (SNPs) to comprehensively represent genetic variability in the cholesteryl ester transfer protein (CETP) gene. Nineteen SNPs were identified in 50 unrelated individuals in the SNP discovery phase, and 13 intronic SNPs were added from the literature. These 32 SNPs were genotyped in 339 apparently healthy individuals and 190 coronary artery disease (CAD) patients. Using phased haplotypes, linkage disequilibrium (LD) structure was characterized and tSNPs selected using a principal component analysis (PCA) method. In healthy individuals, seven LD groups were identified that accounted for 93.4% of the observed genetic variation. These LD groups highlighted a complex LD structure for CETP, including both recombination and mutation, and eleven tSNPs were selected. Among CAD patients the results were essentially the same. Results from PCA using diploid genotype data were reasonably comparable. Finally, the selected tSNPs successfully represented the association evidence discovered for all of the other SNPs studied. This study provides an optimal set of tSNPs for association analyses of CETP. The observed complexity of LD structure highlights the importance of using methods, such as PCA, that allow for multiple dynamics in intragenic LD structure.

Haplotype trees and modern human origins

A haplotype is a multisite haploid genotype at two or more polymorphic sites on the same chromosome in a defined DNA region. An evolutionary tree of the haplotypes can be estimated if the DNA region had little to no recombination. Haplotype trees can be used to reconstruct past human gene-flow patterns and historical events, but any single tree captures only a small portion of evolutionary history, and is subject to error. A fuller view of human evolution requires multiple DNA regions, and errors can be minimized by cross-validating inferences across loci. An analysis of 25 DNA regions reveals an out-of-Africa expansion event at 1.9 million years ago. Gene flow with isolation by distance was established between African and Eurasian populations by about 1.5 million years ago, with no detectable interruptions since. A second out-of-Africa expansion occurred about 700,000 years ago, and involved interbreeding with at least some Eurasian populations. A third out-of-Africa event occurred around 100,000 years ago, and was also characterized by interbreeding, with the hypothesis of a total Eurasian replacement strongly rejected (P < 10(-17)). This does not preclude the possibility that some Eurasian populations could have been replaced, and the status of Neanderthals is indecisive. Demographic inferences from haplotype trees have been inconsistent, so few definitive conclusions can be made at this time. Haplotype trees from human parasites offer additional insights into human evolution and raise the possibility of an Asian isolate of humanity, but once again not in a definitive fashion. Haplotype trees can also indicate which genes were subject to positive selection in the lineage leading to modern humans. Genetics provides many insights into human evolution, but those insights need to be integrated with fossil and archaeological data to yield a fuller picture of the origin of modern humans.

DAPK1 variants are associated with Alzheimer's disease and allele-specific expression

Genetic factors play an important role in the etiology of late-onset Alzheimer's disease (LOAD). We tested gene-centric single nucleotide polymorphisms (SNPs) on chromosome 9 and identified two SNPs in the death-associated protein kinase, DAPK1, that show significant association with LOAD. SNP rs4878104 was significantly associated with LOAD in our discovery case-control sample set (WU) and replicated in each of two initial validation case-control sample sets (P<0.05, UK1, SD). The risk-allele frequency of this SNP showed a similar direction in three other case-control sample sets. A meta-analysis of the six sample sets combined, totaling 2012 cases and 2336 controls, showed an allelic P-value of 0.0016 and an odds ratio (OR) of 0.87 (95%CI: 0.79-0.95). Minor allele homozygotes had a consistently lower risk than major allele homozygotes in the discovery and initial two replication sample sets, which remained significant in the meta-analysis of all six sample sets (OR=0.7, 95%CI: 0.58-0.85), whereas the risk for heterozygous subjects was not significantly different from that of major allele homozygotes. A second SNP, rs4877365, which is in high linkage disequilibrium with rs4878104 (r2=0.64), was also significantly associated with LOAD (meta P=0.0017 in the initial three sample sets). Furthermore, DAPK1 transcripts show differential allelic gene expression, and both rs4878104 and rs4877365 were significantly associated with DAPK1 allele-specific expression (P=0.015 to <0.0001). These data suggest that genetic variation in DAPK1 modulates susceptibility to LOAD.

Conserved extended haplotypes of the major histocompatibility complex: further characterization

Since the complete sequencing of a human major histocompatibility complex (MHC) haplotype, interest in non-human leucocyte antigen (HLA) genes encoded in the MHC has been growing. Non-HLA genes, which outnumber the HLA genes, may contribute to or account for HLA and disease associations. Most information on non-HLA genes has been obtained in separate studies of individual loci. To comprehensively address polymorphisms of relevant non-HLA genes in 'conserved extended haplotypes' (CEH), we investigated 101 International Histocompatibility Workshop reference cell lines and nine additional anonymous samples representing all 37 unambiguously characterized CEHs at MICA, NFKBIL1, LTA, NCR3, AIF1, HSPA1A, HSPA1B, BF, NOTCH4 and a single nucleotide polymorphism (SNP) at HLA-DQA1 as well as MICA, NOTCH4, HSPA1B and all five tumour necrosis factor short tandem repeat (STR) polymorphisms. This work (1) provides an extensive catalogue of MHC polymorphisms in all CEHs, (2) unravels interrelationships between HLA and non-HLA haplotypical lineages, (3) resolves reported typing ambiguities and (4) describes haplospecific markers for a number of CEHs. Analysis also identified a DQA1 SNP and segments containing MHC class III polymorphisms that corresponded with class II (DRB3 and DRB4) lineages. These results portray the MHC where lineages containing non-HLA and HLA variants in linkage disequilibrium may operate in concert and can guide more thorough design and interpretation of HLA-disease relationships.

Haplotypes in the lipoprotein lipase gene influence high-density lipoprotein cholesterol response to statin therapy and progression of atherosclerosis in coronary artery bypass grafts

Lipoprotein lipase (LPL) hydrolyzes circulating triglycerides (TGs). We previously showed that 3'-end haplotypes in the LPL gene influence atherosclerosis and insulin resistance. This study asked whether these LPL haplotypes influence response to lipid-lowering therapy among 829 subjects from the Post-Coronary Artery Bypass Graft trial. Lipid profiles were obtained at baseline and 4-5 years after treatment with lovastatin. Haplotypes were based on 12 SNPs. The fourth most frequent haplotype, 12-4, was associated with a decreased increment in high-density lipoprotein-cholesterol (HDL-C) following treatment. Haplotypes 12-6, 12-7 and 12-8 were each associated with increased HDL-C response to therapy, and haplotype 12-2 with decreased TG response. The most common haplotype, 12-1, was protective against graft worsening or occlusion. Haplotype 12-4 reduced HDL-C response to lovastatin, possibly consistent with our prior observations of this haplotype as predisposing to coronary artery disease. LPL may influence atherosclerosis risk through pleiotropic effects on each aspect of the metabolic syndrome.

IL-6 haplotypes, inflammation, and risk for cardiovascular disease in a multiethnic dialysis cohort

It is unknown whether IL-6, a central regulator of inflammation, is a cause of or just a marker of atherosclerosis. Studies of genetic susceptibility to inflammation, however, avoid the potential for reverse causality. Variation in IL6 gene was studied as a predictor of cardiovascular disease (CVD) risk in a cohort of 775 incident dialysis patients, in whom IL-6 levels are elevated. On the basis of published resequencing data on the IL6 gene, a phylogenetic tree with three main branches (clades 1 to 3) was constructed. Two "clade tag" polymorphisms, -174G/C and 1888G/T, and two missense variants, Pro32Ser and Asp162Val, were genotyped. Circulating IL-6 and albumin were measured a median of 5 mo after the start of dialysis. CVD events were ascertained from medical records. During a median follow-up of 2.5 yr, 294 CVD events occurred. The two coding variants, Pro32Ser (present only in black patients, 10% Ser allele) and Asp162Val (present only in white patients, 1% Val), were associated with lower levels of IL-6 and higher levels of albumin. The common variant in the promoter region, -174G/C, was strongly associated with higher CVD risk and weakly with IL-6 levels. Clade 3 (-174C carriers in the absence of 162 Val allele) was associated with higher IL-6 levels (P=0.03) and higher CVD risk (hazard ratio 1.44, P=0.006) after adjustment for covariates. The IL6 gene has functional variants that affect inflammation and risk for CVD among dialysis patients, supporting a causal role for IL6 in CVD.

A scan of chromosome 10 identifies a novel locus showing strong association with late-onset Alzheimer disease

Strong evidence of linkage to late-onset Alzheimer disease (LOAD) has been observed on chromosome 10, which implicates a wide region and at least one disease-susceptibility locus. Although significant associations with several biological candidate genes on chromosome 10 have been reported, these findings have not been consistently replicated, and they remain controversial. We performed a chromosome 10-specific association study with 1,412 gene-based single-nucleotide polymorphisms (SNPs), to identify susceptibility genes for developing LOAD. The scan included SNPs in 677 of 1,270 known or predicted genes; each gene contained one or more markers, about half (48%) of which represented putative functional mutations. In general, the initial testing was performed in a white case-control sample from the St. Louis area, with 419 LOAD cases and 377 age-matched controls. Markers that showed significant association in the exploratory analysis were followed up in several other white case-control sample sets to confirm the initial association. Of the 1,397 markers tested in the exploratory sample, 69 reached significance (P < .05). Five of these markers replicated at P < .05 in the validation sample sets. One marker, rs498055, located in a gene homologous to RPS3A (LOC439999), was significantly associated with Alzheimer disease in four of six case-control series, with an allelic P value of .0001 for a meta-analysis of all six samples. One of the case-control samples with significant association to rs498055 was derived from the linkage sample (P = .0165). These results indicate that variants in the RPS3A homologue are associated with LOAD and implicate this gene, adjacent genes, or other functional variants (e.g., noncoding RNAs) in the pathogenesis of this disorder.

The efficacy of short tandem repeat polymorphisms versus single-nucleotide polymorphisms for resolving population structure

Accurately resolving population structure in a sample is important for both linkage and association studies. In this study we investigated the power of single-nucleotide polymorphisms (SNPs) in detecting population structure in a sample of 286 unrelated individuals. We varied the number of SNPs to determine how many are required to approach the degree of resolution obtained with the Collaborative Study on the Genetics of Alcoholism (COGA) short tandem repeat polymorphisms (STRPs). In addition, we selected SNPs with varying minor allele frequencies (MAFs) to determine whether low or high frequency SNPs are more efficient in resolving population structure. We conclude that a set of at least 100 evenly spaced SNPs with MAFs of 40–50% is required to resolve population structure in this dataset. If SNPs with lower MAFs are used, then more than 250 SNPs may be required to obtain reliable results.

Issues with Polymorphism Analysis in Sepsis

Genetic variation has been shown to play a large role in determining susceptibility to and outcome of such complex diseases as sepsis. There is a much higher heritability of death due to infection than death due to cancer or heart disease. More than 8 million single nucleotide polymorphisms (SNPs) have been detected in the human genome, and there is very little understanding of their effect on gene expression and protein function. The use of haplotypes, which are inherited sets of linked SNPs, as the unit of genetic variation in association studies and the marking of these haplotypes with unique "tag SNPs" may help to narrow down the search for causal SNPs. Future studies must be large (thousands of patients) and must be carefully designed to avoid false associations resulting from ethnic differences in genotype frequencies and disease prevalence in order to find true, reproducible associations between genotype and phenotype. Functional studies and careful characterization of intermediate phenotypes must be done to lend biological plausibility to genotype-phenotype associations. Examination of the association between genetic polymorphisms and sepsis promises to provide clinicians with new tools to evaluate prognosis, to intervene early and aggressively in treating high-risk persons, and to avoid the use of therapies with adverse effects in treating low-risk persons.

Haplotype diversity: the link between statistical and biological association

In the rapidly growing field of association mapping in plants, the use of (marker) haplotypes rather than single markers can be an effective way of improving detection power. Here, we highlight the information that can be obtained from deducing the historical relationships between haplotypes. The ordering of haplotype classes according to deduced historical relationships should further enhance association detection power, but can also be used to predict the genotypic and phenotypic values of unobserved germplasm.

Association studies between risk for late-onset Alzheimer's disease and variants in insulin degrading enzyme

Linkage studies have suggested there is a susceptibility gene for late onset Alzheimer's disease (LOAD) in a broad region of chromosome 10. A strong positional and biological candidate is the gene encoding the insulin-degrading enzyme (IDE), a protease involved in the catabolism of Abeta. However, previous association studies have produced inconsistent results. To systematically evaluate the role of variation in IDE in the risk for LOAD, we genotyped 18 SNPs spanning a 276 kb region in and around IDE, including three "tagging" SNPs identified in an earlier study. We used four case-control series with a total of 1,217 cases and 1,257 controls. One SNP (IDE_7) showed association in two samples (P-value = 0.0066, and P = 0.026, respectively), but this result was not replicated in the other two series. None of the other SNPs showed association with LOAD in any of the tested samples. Haplotypes, constructed from the three tagging SNPs, showed no globally significant association. In the UK2 series, the CTA haplotype was over-represented in cases (P = 0.046), and in the combined data set, the CCG haplotype was more frequent in controls (P = 0.015). However, these weak associations observed in our series were in the opposite direction to the results in previous studies. Although our results are not universally negative, we were unable to replicate the results of previous studies and conclude that common variants or haplotypes of these variants in IDE are not major risk factors for LOAD.

Evaluating associations of haplotypes with traits

Haplotypes have played a major role in the study of highly-penetrant single-gene disorders, and recent evidence that the human genome has hot-spots and cold-spots for recombination have suggested that haplotype-based methods may play a key role in the study of common complex traits. This report reviews the motivation of using haplotypes for the study of the genetic basis of human traits, ranging from biologic function, to statistical power advantages of haplotypes, to linkage disequilibrium fine-mapping. Recent developments of regression models for haplotype analyses are reviewed, offering a synthesis of current methods, as well as their limitations and areas that require further research. Regression models provide significant advantages, such as the ability to control for non-genetic covariates, the effects of the haplotypes can be modeled, step-wise selection can be used to screen for a subset of markers that explain most of the association, haplotype x environment interactions can be evaluated, and regression diagnostics are well developed. Despite these strengths, the current regression methods tend to lack the sophisticated population genetic perspectives offered by coalescent and other similar approaches. Future work that links regression methods with population genetic models may prove beneficial.

Linkage disequilibrium grouping of single nucleotide polymorphisms (SNPs) reflecting haplotype phylogeny for efficient selection of tag SNPs

Single nucleotide polymorphisms (SNPs) have been proposed to be grouped into haplotype blocks harboring a limited number of haplotypes. Within each block, the portion of haplotypes is expected to be tagged by a selected subset of SNPs; however, none of the proposed selection algorithms have been definitive. To address this issue, we developed a tag SNP selection algorithm based on grouping of SNPs by the linkage disequilibrium (LD) coefficient r(2) and examined five genes in three ethnic populations--the Japanese, African Americans, and Caucasians. Additionally, we investigated ethnic diversity by characterizing 979 SNPs distributed throughout the genome. Our algorithm could spare 60% of SNPs required for genotyping and limit the imprecision in allele-frequency estimation of nontag SNPs to 2% on average. We discovered the presence of a mosaic pattern of LD plots within a conventionally inferred haplotype block. This emerged because multiple groups of SNPs with strong intragroup LD were mingled in their physical positions. The pattern of LD plots showed some similarity, but the details of tag SNPs were not entirely concordant among three populations. Consequently, our algorithm utilizing LD grouping allows selection of a more faithful set of tag SNPs than do previous algorithms utilizing haplotype blocks.

TreeScan: a bioinformatic application to search for genotype/phenotype associations using haplotype trees

SUMMARY

We present the software implementation of the tree scanning method to detect associations between genetic haplotypes and quantitative traits, utilizing the evolutionary history of the haplotypes, in samples of unrelated individuals.

AVAILABILITY

The program is available free of charge, under the GNU General Public License. A package including C source code, a Makefile, and Windows (DOS) and Macintosh binaries, can be downloaded from http://darwin.uvigo.es

Nucleotide variation at the myrosinase-encoding locus, TGG1, and quantitative myrosinase enzyme activity variation in Arabidopsis thaliana

The Arabidopsis thaliana TGG1 gene encodes thioglucoside glucohydrolase (myrosinase), an enzyme catalysing the hydrolysis of glucosinolate compounds. The enzyme is involved in plant defence against some insect herbivores, and is present in species of the order Capparales (Brassicales). Nucleotide variation was surveyed by sequencing c. 2.4 kb of the TGG1 locus in a sample of 28 worldwide A. thaliana accessions, and one Arabidopsis lyrata ssp. lyrata individual. Myrosinase activity was quantified for 27 of these same A. thaliana accessions, plus five additional others. Overall, estimated nucleotide diversity in A. thaliana was low compared to other published A. thaliana surveys, and the frequency distribution was skewed toward an excess of low-frequency variants. Furthermore, comparison to the outgroup species A. lyrata demonstrated that A. thaliana exhibited an excess of high-frequency derived variants relative to a neutral equilibrium model, suggesting a selective sweep. A. thaliana accessions differed significantly in total myrosinase activity, but analysis of variance detected no statistical evidence for an association between quantitative enzyme activity and alleles at the TGG1 myrosinase-encoding locus. We thus conclude that other, unsurveyed factors primarily affect the observed myrosinase activity levels in this species. The pattern of nucleotide variation was consistent with a model of positive selection but might also be compatible with a completely neutral model that takes into account the metapopulation behaviour of this highly inbreeding species which experienced a relatively recent worldwide expansion.

Lipoprotein lipase locus and progression of atherosclerosis in coronary-artery bypass grafts

PURPOSE

Our aim was to test whether polymorphisms in the lipoprotein lipase (LPL) gene were associated with the progression of atherosclerosis in grafts examined in the Post-Coronary Artery Bypass Graft Trial (Post-CABG Trial).

METHODS

843 subjects in the post-CABG trial were genotyped for the LPL-D9N, N291S, PvuII, (TTTA)n, and HindIII polymorphisms. Associations between genotype and angiographically measured progression of atherosclerosis in grafts, medical history, and family history were examined.

RESULTS

Greater progression of atherosclerosis was observed in subjects with LPL-HindIII 2/2 (56% versus 42% of those with other LPL HindIII genotypes, P = 0.025) and with LPL (TTTA)n 4/4 (63% versus 43% of those with other (TTTA)n genotypes, P = 0.020). Mantel-Haenszel analysis yielded an odds ratio of 1.84 for the effect of LPL HindIII 2/2 genotype on the progression of atherosclerosis in grafts (P = 0.015) and demonstrated that the effect of genotype on progression was of the same magnitude as, but independent of, the effect of drug treatment.

CONCLUSION

The LPL-HindIII 2/2 genotype is a marker for genetic variation in the 3'-end of LPL that acts as an independent risk factor for the progression of atherosclerosis in grafts examined in the Post-CABG Trial.

Unexpected complexity in the haplotypes of commonly used inbred strains of laboratory mice

Investigation of sequence variation in common inbred mouse strains has revealed a segmented pattern in which regions of high and low variant density are intermixed. Furthermore, it has been suggested that allelic strain distribution patterns also occur in well defined blocks and consequently could be used to map quantitative trait loci (QTL) in comparisons between inbred strains. We report a detailed analysis of polymorphism distribution in multiple inbred mouse strains over a 4.8-megabase region containing a QTL influencing anxiety. Our analysis indicates that it is only partly true that the genomes of inbred strains exist as a patchwork of segments of sequence identity and difference. We show that the definition of haplotype blocks is not robust and that methods for QTL mapping may fail if they assume a simple block-like structure.

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.

Will haplotype maps be useful for finding genes?

From its introduction into the literature, the idea of haplotype map-based linkage disequilibrium (LD) studies has been the subject of disputes. These queries involve the extent to which the haplotype blocks exist, the validity of fundamental concepts such as the recombination hotspot, and the application of this idea in the form of the HapMap project. In this article, we review the relevant literature to evaluate the potential importance of haplotype maps for psychiatric genetics. We first take a closer look at the nature of haplotype blocks and then address the impact of block definitions and methodological factors, such as single-nucleotide polymorphism density and sample size, on findings from haplotype block studies. After distinguishing between two types of haplotype map-based LD studies, we discuss the importance of the recombination hotspot and the nature of the disease mutations affecting complex traits. In the final section, we summarize our main conclusions and comment on the usefulness of haplotype maps for finding genes.

The role of haplotypes in candidate gene studies

Human geneticists working on systems for which it is possible to make a strong case for a set of candidate genes face the problem of whether it is necessary to consider the variation in those genes as phased haplotypes, or whether the one-SNP-at-a-time approach might perform as well. There are three reasons why the phased haplotype route should be an improvement. First, the protein products of the candidate genes occur in polypeptide chains whose folding and other properties may depend on particular combinations of amino acids. Second, population genetic principles show us that variation in populations is inherently structured into haplotypes. Third, the statistical power of association tests with phased data is likely to be improved because of the reduction in dimension. However, in reality it takes a great deal of extra work to obtain valid haplotype phase information, and inferred phase information may simply compound the errors. In addition, if the causal connection between SNPs and a phenotype is truly driven by just a single SNP, then the haplotype-based approach may perform worse than the one-SNP-at-a-time approach. Here we examine some of the factors that affect haplotype patterns in genes, how haplotypes may be inferred, and how haplotypes have been useful in the context of testing association between candidate genes and complex traits.

Haplotypes and the systematic analysis of genetic variation in genes and genomes

Haplotypes have been used in various fields of genetics for a long time, in a variety of contexts, and for different purposes. Now, haplotype-based approaches to the analysis of candidate genes and genome-wide linkage disequilibrium (LD) mapping have gained center stage. It is time to explicitly distinguish the different concepts implied in the present haplotype approaches: haplotypes are not haplotypes, after all. The distinction of three different categories, ancestral, common haplotypes or haplotype blocks, gene-based haplotypes as complex genetic markers and gene-based functional haplotypes, is proposed. These categories serve as framework to review and analyze in particular the recent work suggesting evidence for a haplotype block structure of the human genome and the body of comparative sequencing studies addressing haplotype and LD structures at the gene level. Haplotype approaches will be evaluated along the dimensions preselection of variants versus complete DNA sequence information, role of LD and stages in the process of disease gene identification. Overall, the content of haplotypes is conceived as a function of available technologies to evaluate genetic variation and general advances in human genome research.

Selection and evaluation of tagging SNPs in the neuronal-sodium-channel gene SCN1A: implications for linkage-disequilibrium gene mapping

Association studies are widely seen as the most promising approach for finding polymorphisms that influence genetically complex traits, such as common diseases and responses to their treatment. Considerable interest has therefore recently focused on the development of methods that efficiently screen genomic regions or whole genomes for gene variants associated with complex phenotypes. One key element in this search is the use of linkage disequilibrium to gain maximal information from typing a selected subset of highly informative single-nucleotide polymorphism (SNP) markers, now often called "tagging SNPs" (tSNPs). Probably the most common approach to linkage-disequilibrium gene mapping involves a three-step program: (1) characterization of the haplotype structure in candidate genes or genomic regions of interest, (2) identification of tSNPs sufficient to represent the most common haplotypes, and (3) typing of tSNPs in clinical material. Early definitions of tSNPs focused on the amount of haplotype diversity that they explained. To select tSNPs that would have maximal power in a genetic association study, however, we have developed optimization criteria based on the r2 measure of association and have compared these with other criteria based on the haplotype diversity. To evaluate the full program and to assess how well the selected tags are likely to perform, we have determined the haplotype structure and have assessed tSNPs in the SCN1A gene, an important candidate gene for sporadic epilepsy. We find that as few as four tSNPs are predicted to maintain a consistently high r2 value with all other common SNPs in the gene, indicating that the tags could be used in an association study with only a modest reduction in power relative to direct assays of all common SNPs. This implies that very large case-control studies can be screened for variation in hundreds of candidate genes with manageable experimental effort, once tSNPs are identified. However, our results also show that tSNPs identified in one population may not necessarily perform well in another, indicating that the preliminary study to identify tSNPs and the later case-control study should be performed in the same population. Our results also indicate that tSNPs will not easily identify discrepant SNPs, which lie on importantly discriminating but apparently short genealogical branches. This could significantly complicate tagging approaches for phenotypes influenced by variants that have experienced positive selection.

Mathematical multi-locus approaches to localizing complex human trait genes

Statistical analysis methods for gene mapping originated in counting recombinant and non-recombinant offspring, but have now progressed to sophisticated approaches for the mapping of complex trait genes. Here, we outline new statistical methods that capture the simultaneous effects of multiple gene loci and thereby achieve a more global view of gene action and interaction than is possible by traditional gene-by-gene analysis. We aim to show that the work of statisticians goes far beyond the running of computer programs.

Recombination in evolutionary genomics

Recombination can be a dominant force in shaping genomes and associated phenotypes. To better understand the impact of recombination on genomic evolution, we need to be able to identify recombination in aligned sequences. We review bioinformatic approaches for detecting recombination and measuring recombination rates. We also examine the impact of recombination on the reconstruction of evolutionary histories and the estimation of population genetic parameters. Finally, we review the role of recombination in the evolutionary history of bacteria, viruses, and human mitochondria. We conclude by highlighting a number of areas for future development of tools to help quantify the role of recombination in genomic evolution.

Determination and use of haplotypes: ethnic comparison and association of the lipoprotein lipase gene and coronary artery disease in Mexican-Americans

PURPOSE

To illustrate an approach of deriving haplotypes for genetic association studies, using the lipoprotein lipase (LPL) gene and coronary artery disease.

METHODS

Six polymorphisms sufficient to distinguish the most common haplotypes in the 3' end of LPL were identified by genotyping 10 polymorphisms in a small pilot population. These were used to haplotype LPL in large family samples of Mexican-Americans and non-Hispanic Caucasians. A case-control association study was performed comparing Mexican-Americans with and without coronary artery disease.

RESULTS

The two ethnic groups exhibited significant genetic differences. Among Mexican-Americans, homozygosity for LPL haplotype 1 was protective against coronary artery disease (OR = 0.50, 95% CI 0.27-0.91).

CONCLUSION

This study outlines the haplotype structure of the LPL gene, illustrates the utility of haplotype-based analysis in association studies, and demonstrates the importance of defining haplotype frequencies for different ethnic groups.

Haplotype structure, LD blocks, and uneven recombination within the LRP5 gene

Patterns of linkage disequilibrium (LD) in the human genome are beginning to be characterized, with a paucity of haplotype diversity in "LD blocks," interspersed by apparent "hot spots" of recombination. Previously, we cloned and physically characterized the low-density lipoprotein-receptor-related protein 5 (LRP5) gene. Here, we have extensively analysed both LRP5 and its flanking three genes, spanning 269 kb, for single nucleotide polymorphisms (SNPs), and we present a comprehensive SNP map comprising 95 polymorphisms. Analysis revealed high levels of recombination across LRP5, including a hot-spot region from intron 1 to intron 7 of LRP5, where there are 109 recombinants/Mb (4882 meioses), in contrast to flanking regions of 14.6 recombinants/Mb. This region of high recombination could be delineated into three to four hot spots, one within a 601-bp interval. For LRP5, three haplotype blocks were identified, flanked by the hot spots. Each LD block comprised over 80% common haplotypes, concurring with a previous study of 14 genes that showed that common haplotypes account for at least 80% of all haplotypes. The identification of hot spots in between these LD blocks provides additional evidence that LD blocks are separated by areas of higher recombination.

SNP haplotype tagging from DNA pools of two individuals

BACKGROUND

DNA pooling is a technique to reduce genotyping effort while incurring only minor losses in accuracy of allele frequency estimates for single nucleotide polymorphism (SNP) markers.

RESULTS

We present an algorithm for reconstructing haplotypes (alleles for multiple SNPs on same chromosome) from pools of two individual DNAs, in which Hardy-Weinberg equilibrium conditions or other assumptions are not required. The program outputs, in addition to inferred haplotypes, a minimal number of haplotype-tagging SNPs that are identified after an exhaustive search procedure.

CONCLUSION

Our method and algorithms lead to a significant reduction in genotyping effort, for example, in case-control disease association studies while maintaining the possibility of reconstructing haplotypes under very general conditions.