Comparison of linkage disequilibrium patterns between the HapMap CEPH samples and a family-based cohort of Northern European descent

A Scale-Corrected Comparison of Linkage Disequilibrium Levels between Genic and Non-Genic Regions

The understanding of non-random association between loci, termed linkage disequilibrium (LD), plays a central role in genomic research. Since causal mutations are generally not included in genomic marker data, LD between those and available markers is essential for capturing the effects of causal loci on localizing genes responsible for traits. Thus, the interpretation of association studies requires a detailed knowledge of LD patterns. It is well known that most LD measures depend on minor allele frequencies (MAF) of the considered loci and the magnitude of LD is influenced by the physical distances between loci. In the present study, a procedure to compare the LD structure between genomic regions comprising several markers each is suggested. The approach accounts for different scaling factors, namely the distribution of MAF, the distribution of pair-wise differences in MAF, and the physical extent of compared regions, reflected by the distribution of pair-wise physical distances. In the first step, genomic regions are matched based on similarity in these scaling factors. In the second step, chromosome- and genome-wide significance tests for differences in medians of LD measures in each pair are performed. The proposed framework was applied to test the hypothesis that the average LD is different in genic and non-genic regions. This was tested with a genome-wide approach with data sets for humans (Homo sapiens), a highly selected chicken line (Gallus gallus domesticus) and the model plant Arabidopsis thaliana. In all three data sets we found a significantly higher level of LD in genic regions compared to non-genic regions. About 31% more LD was detected genome-wide in genic compared to non-genic regions in Arabidopsis thaliana, followed by 13.6% in human and 6% chicken. Chromosome-wide comparison discovered significant differences on all 5 chromosomes in Arabidopsis thaliana and on one third of the human and of the chicken chromosomes.

Linkage Disequilibrium Estimation of Chinese Beef Simmental Cattle Using High-density SNP Panels

Linkage disequilibrium (LD) plays an important role in genomic selection and mapping quantitative trait loci (QTL). In this study, the pattern of LD and effective population size (N_e) were investigated in Chinese beef Simmental cattle. A total of 640 bulls were genotyped with IlluminaBovinSNP50BeadChip and IlluminaBovinHDBeadChip. We estimated LD for each autosomal chromosome at the distance between two random SNPs of <0 to 25 kb, 25 to 50 kb, 50 to 100 kb, 100 to 500 kb, 0.5 to 1 Mb, 1 to 5 Mb and 5 to 10 Mb. The mean values of r² were 0.30, 0.16 and 0.08, when the separation between SNPs ranged from 0 to 25 kb to 50 to 100 kb and then to 0.5 to 1 Mb, respectively. The LD estimates decreased as the distance increased in SNP pairs, and increased with the increase of minor allelic frequency (MAF) and with the decrease of sample sizes. Estimates of effective population size for Chinese beef Simmental cattle decreased in the past generations and N_e was 73 at five generations ago.

Structural and population-based evaluations of TBC1D1 p.Arg125Trp

Obesity is now a leading cause of preventable death in the industrialised world. Understanding its genetic influences can enhance insight into molecular pathogenesis and potential therapeutic targets. A non-synonymous polymorphism (rs35859249, p.Arg125Trp) in the N-terminal TBC1D1 phosphotyrosine-binding (PTB) domain has shown a replicated association with familial obesity in women. We investigated these findings in the Avon Longitudinal Study of Parents and Children (ALSPAC), a large European birth cohort of mothers and offspring, and by generating a predicted model of the structure of this domain. Structural prediction involved the use of three separate algorithms; Robetta, HHpred/MODELLER and I-TASSER. We used the transmission disequilibrium test (TDT) to investigate familial association in the ALSPAC study cohort (N = 2,292 mother-offspring pairs). Linear regression models were used to examine the association of genotype with mean measurements of adiposity (Body Mass Index (BMI), waist circumference and Dual-energy X-ray absorptiometry (DXA) assessed fat mass), and logistic regression was used to examine the association with odds of obesity. Modelling showed that the R125W mutation occurs in a location of the TBC1D1 PTB domain that is predicted to have a function in a putative protein:protein interaction. We did not detect an association between R125W and BMI (mean per allele difference 0.27 kg/m² (95% Confidence Interval: 0.00, 0.53) P = 0.05) or obesity (odds ratio 1.01 (95% Confidence Interval: 0.77, 1.31, P = 0.96) in offspring after adjusting for multiple comparisons. Furthermore, there was no evidence to suggest that there was familial association between R125W and obesity (χ² = 0.06, P = 0.80). Our analysis suggests that R125W in TBC1D1 plays a role in the binding of an effector protein, but we find no evidence that the R125W variant is related to mean BMI or odds of obesity in a general population sample.

Quantification of the clinical modifiers impacting high-density lipoprotein cholesterol in the community: Personalized Medicine Research Project

High-density lipoprotein (HDL) cholesterol levels are inversely correlated with the development of cardiovascular disease. To date, genetic association studies have explained only a small proportion of the overall variance in HDL cholesterol. Further studies are needed, within practice-based cohorts, to place genetic findings into context alongside important clinical variables (eg, age, sex, body mass index, medication use, and clinical comorbidity). The Marshfield Clinic Personalized Medicine Research Project database was designed for large-scale studies of genetic epidemiology in a clinical practice-based setting. Because of its size and its unique practice-based design, this resource will provide adequate statistical power for the assessment of genetic findings related to HDL cholesterol level within the context of covariates known to modify lipid homeostasis. The authors report construction and validation of novel electronic phenotyping algorithms that can be used to model individual baseline HDL cholesterol levels within this practice-based resource. Because these algorithms were developed in a setting that reflects routine clinical care, future genetic studies using these algorithms within practice-based DNA biobanks should facilitate the identification of markers with optimal effect size after adjustment for known clinical factors contributing to the overall variance in HDL cholesterol level within the community.

Comparison of genome-wide variation between Malawians and African ancestry HapMap populations

Understanding genetic variation between populations is important because it affects the portability of human genome-wide analytical methods. We compared genetic variation and substructure between Malawians and other African and non-African HapMap populations. Allele frequencies and adjacent linkage disequilibrium (LD) were measured for 617 715 single nucleotide polymorphisms (SNPs) across subject genomes. Allele frequencies in the Malawian population (N=226) were highly correlated with allele frequencies in HapMap populations of African ancestry (AFA, N=376), namely Yoruban in Ibadan, Nigeria (Spearman's r(2)=0.97), Luhya in Webuye, Kenya (r(2)=0.97), African Americans in the southwest United States (r(2)=0.94) and Maasai in Kinyawa, Kenya (r(2)=0.91). This correlation was much lower between Malawians and other ancestry populations (r(2)<0.52). LD correlations between Malawians and HapMap populations were strongest for the populations of AFA (AFA r(2)>0.82, other ancestries r(2)<0.57). Principal components analyses revealed little population substructure within our Malawi sample but provided clear distinction between Malawians, AFA populations and two European populations. Five SNPs within the lactase gene (LCT) had substantially different allele frequencies between the Malawi population and Maasai in Kenyawa, Kenya (rs3769013, rs730005, rs3769012, rs2304370; P-values <1 x 10(-33)).

Obesity-related dyslipidemia associated with FAAH, independent of insulin response, in multigenerational families of Northern European descent

A more thorough understanding of the genetic architecture underlying obesity-related lipid disorders could someday facilitate cardiometabolic risk reduction through early clinical intervention based upon improved characterization of individual risk. In recent years, there has been tremendous interest in understanding the endocannabinoid system as a novel therapeutic target for the treatment of obesity-related dyslipidemia.

AIMS

N-arachidonylethanolamine activates G-protein-coupled receptors within the endocannabinoid system. Fatty acid amide hydrolase (FAAH) is a primary catabolic regulator of N-acylethanolamines, including arachidonylethanolamine. Genetic variants in FAAH have inconsistently been associated with obesity. It is conceivable that genetic variability in FAAH directly influences lipid homeostasis. The current study characterizes the relationship between FAAH and obesity-related dyslipidemia, in one of the most rigorously-phenotyped obesity study cohorts in the USA.

MATERIALS & METHODS

Members of 261 extended families (pedigrees ranging from 4 to 14 individuals) were genotyped using haplotype tagging SNPs obtained for the FAAH locus, including 5 kb upstream and 5 kb downstream. Each SNP was tested for basic obesity-related phenotypes (BMI, waist and hip circumference, waist:hip ratio, fasting glucose, fasting insulin and fasting lipid levels) in 1644 individuals within these 261 families. Each SNP was also tested for association with insulin responsiveness using data obtained from a frequently sampled intravenous glucose tolerance test in 399 individuals (32 extended families).

RESULTS

A well characterized coding SNP in FAAH (rs324420) was associated with increased BMI, increased triglycerides, and reduced levels of high-density lipoprotein cholesterol. Mean (standard deviation) high-density lipoprotein cholesterol level was 40.5 (14.7) mg/dl for major allele homozygotes, 39.1 (10.4) mg/dl for heterozygotes, and 34.8 (8.1) mg/dl for minor allele homozygotes (p < 0.01, Family-Based Association Test). This SNP was not associated with insulin sensitivity, acute insulin response to intravenous glucose, glucose effectiveness or glucose disposition index.

CONCLUSION

Genetic variability in FAAH is associated with dyslipidemia, independent of insulin response.

Serotonin (5-HT) receptor 5A sequence variants affect human plasma triglyceride levels

Neurotransmitters such as serotonin (5-hydroxytryptamine, 5-HT) work closely with leptin and insulin to fine-tune the metabolic and neuroendocrine responses to dietary intake. Losing the sensitivity to excess food intake can lead to obesity, diabetes, and a multitude of behavioral disorders. It is largely unclear how different serotonin receptor subtypes respond to and integrate metabolic signals and which genetic variations in these receptor genes lead to individual differences in susceptibility to metabolic disorders. In an obese cohort of families of Northern European descent (n = 2,209), the serotonin type 5A receptor gene, HTR5A, was identified as a prominent factor affecting plasma levels of triglycerides (TG), supported by our data from both genome-wide linkage and targeted association analyses using 28 publicly available and 12 newly discovered single nucleotide polymorphisms (SNPs), of which 3 were strongly associated with plasma TG levels (P < 0.00125). Bayesian quantitative trait nucleotide (BQTN) analysis identified a putative causal promoter SNP (rs3734967) with substantial posterior probability (P = 0.59). Functional analysis of rs3734967 by electrophoretic mobility shift assay (EMSA) showed distinct binding patterns of the two alleles of this SNP with nuclear proteins from glioma cell lines. In conclusion, sequence variants in HTR5A are strongly associated with high plasma levels of TG in a Northern European population, suggesting a novel role of the serotonin receptor system in humans. This suggests a potential brain-specific regulation of plasma TG levels, possibly by alteration of the expression of HTR5A.

Genetic variation in cannabinoid receptor 1 (CNR1) is associated with derangements in lipid homeostasis, independent of body mass index

AIMS

In humans, genetic variation in endocannabinergic signaling has been associated with anthropometric measures of obesity. In randomized trials, pharmacological blockade at the level of the cannabinoid receptor 1 (CNR1) receptor not only facilitates weight reduction, but also improves insulin sensitivity and clinical measures of lipid homeostasis. We therefore tested the hypothesis that genetic variation in CNR1 is associated with common obesity-related metabolic disorders.

MATERIALS & METHODS

A total of six haplotype tagging SNPs were selected for CNR1, using data available within the Human HapMap (Centre d'Etude du Polymorphisme Humain population) these included: two promoter SNPs, three exonic SNPs, and a single SNP within the 3'-untranslated region. These tags were then genotyped in a rigorously phenotyped family-based collection of obese study subjects of Northern European origin.

RESULTS & CONCLUSIONS

A common CNR1 haplotype (H4; prevalence 0.132) is associated with abnormal lipid homeostasis. Additional statistical tests using single tagging SNPs revealed that these associations are partly independent of body mass index.

Polymorphisms in CLEC16A and CIITA at 16p13 are associated with primary adrenal insufficiency

CONTEXT/OBJECTIVES

It is known that different autoimmune diseases often share the same susceptibility genes. In this study we aimed to investigate if loci found associated with common autoimmune diseases in recent genome-wide association studies also could be susceptibility loci for autoimmune Addison's disease (primary adrenal insufficiency).

DESIGN/PATIENTS

A total of 139 tagging single nucleotide polymorphisms (SNPs) in 11 candidate genes (IL2, IL21, IL2RA, CLEC2D, CD69, ERBB3, PTPN11, SH2B3, CLEC16A, CIITA, and PTPN2) were genotyped in a case/control study design consisting of Norwegian Addison's disease patients (n = 332) and Norwegian healthy control individuals (n = 1029). Five SNPs were subsequently selected for analysis in a United Kingdom sample set consisting of Addison's disease patients (n = 210) and controls (n = 191).

RESULTS

Polymorphisms in CLEC16A and CIITA remained significantly associated with Addison's disease in the Norwegian sample set at the 0.05 level, even after correction for multiple testing. CLEC16A and CIITA are both located at 16p13, but linkage disequilibrium patterns and logistical regression analyses suggest that SNPs in these two genes are independently associated with Addison's disease. We were not able to confirm these associations in the United Kingdom material, however, this may well be due to the limited sample size and lack of statistical power.

CONCLUSION

Two alleles at 16p13 are independently associated with the risk of Addison's disease in the Norwegian population, suggesting this chromosomal region to harbor common autoimmunity gene(s), CLEC16A and CIITA being possible independent candidates.

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3 K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.

HapMap tagSNP transferability in multiple populations: general guidelines

Linkage disequilibrium (LD) has received much attention recently because of its value in localizing disease-causing genes. Due to the extensive LD between neighboring loci in the human genome, it is believed that a subset of the single nucleotide polymorphisms in a region (tagSNPs) can be selected to capture most of the remaining SNP variants. In this study, we examined LD patterns and HapMap tagSNP transferability in more than 300 individuals. A South Indian sample and an African Mbuti Pygmy population sample were included to evaluate the performance of HapMap tagSNPs in geographically distinct and genetically isolated populations. Our results show that HapMap tagSNPs selected with r(2) >= 0.8 can capture more than 85% of the SNPs in populations that are from the same continental group. Combined tagSNPs from HapMap CEU and CHB+JPT serve as the best reference for the Indian sample. The HapMap YRI are a sufficient reference for tagSNP selection in the Pygmy sample. In addition to our findings, we reviewed over 25 recent studies of tagSNP transferability and propose a general guideline for selecting tagSNPs from HapMap populations.

An evaluation of the performance of HapMap SNP data in a Shanghai Chinese population: analyses of allele frequency, linkage disequilibrium pattern and tagging SNPs transferability on chromosome 1q21-q25

BACKGROUND

The HapMap project aimed to catalog millions of common single nucleotide polymorphisms (SNPs) in the human genome in four major populations, in order to facilitate association studies of complex diseases. To examine the transferability of Han Chinese in Beijing HapMap data to the Southern Han Chinese in Shanghai, we performed comparative analyses between genotypes from over 4,500 SNPs in a 21 Mb region on chromosome 1q21-q25 in 80 unrelated Shanghai Chinese and 45 HapMap Chinese data.

RESULTS

Three thousand and forty-two SNPs were analyzed after removal of SNPs that failed quality control and those not in the HapMap panel. We compared the allele frequency distributions, linkage disequilibrium patterns, haplotype frequency distributions and tagging SNP sets transferability between the HapMap population and Shanghai Chinese population. Among the four HapMap populations, Beijing Chinese showed the best correlation with Shanghai population on allele frequencies, linkage disequilibrium and haplotype frequencies. Tagging SNP sets selected from four HapMap populations at different thresholds were evaluated in the Shanghai sample. Under the threshold of r2 equal to 0.8 or 0.5, both HapMap Chinese and Japanese data showed better coverage and tagging efficiency than Caucasian and African data.

CONCLUSION

Our study supported the applicability of HapMap Beijing Chinese SNP data to the study of complex diseases among southern Chinese population.

Analysis of genetic variation in Ashkenazi Jews by high density SNP genotyping

BACKGROUND

Genetic isolates such as the Ashkenazi Jews (AJ) potentially offer advantages in mapping novel loci in whole genome disease association studies. To analyze patterns of genetic variation in AJ, genotypes of 101 healthy individuals were determined using the Affymetrix EAv3 500 K SNP array and compared to 60 CEPH-derived HapMap (CEU) individuals. 435,632 SNPs overlapped and met annotation criteria in the two groups.

RESULTS

A small but significant global difference in allele frequencies between AJ and CEU was demonstrated by a mean FST of 0.009 (P < 0.001); large regions that differed were found on chromosomes 2 and 6. Haplotype blocks inferred from pairwise linkage disequilibrium (LD) statistics (Haploview) as well as by expectation-maximization haplotype phase inference (HAP) showed a greater number of haplotype blocks in AJ compared to CEU by Haploview (50,397 vs. 44,169) or by HAP (59,269 vs. 54,457). Average haplotype blocks were smaller in AJ compared to CEU (e.g., 36.8 kb vs. 40.5 kb HAP). Analysis of global patterns of local LD decay for closely-spaced SNPs in CEU demonstrated more LD, while for SNPs further apart, LD was slightly greater in the AJ. A likelihood ratio approach showed that runs of homozygous SNPs were approximately 20% longer in AJ. A principal components analysis was sufficient to completely resolve the CEU from the AJ.

CONCLUSION

LD in the AJ versus was lower than expected by some measures and higher by others. Any putative advantage in whole genome association mapping using the AJ population will be highly dependent on regional LD structure.

Selection of genes and single nucleotide polymorphisms for fine mapping starting from a broad linkage region

Fine mapping of linkage peaks is one of the great challenges facing researchers who try to identify genes and genetic variants responsible for the variation in a certain trait or complex disease. Once the trait is linked to a certain chromosomal region, most studies use a candidate gene approach followed by a selection of polymorphisms within these genes, either based on their possibility to be functional, or based on the linkage disequilibrium between adjacent markers. For both candidate gene selection and SNP selection, several approaches have been described, and different software tools are available. However, mastering all these information sources and choosing between the different approaches can be difficult and time-consuming. Therefore, this article lists several of these in silico procedures, and the authors describe an empirical two-step fine mapping approach, in which candidate genes are prioritized using a bioinformatics approach (ENDEAVOUR), and the top genes are chosen for further SNP selection with a linkage disequilibrium based method (Tagger). The authors present the different actions that were applied within this approach on two previously identified linkage regions for muscle strength. This resulted in the selection of 331 polymorphisms located in 112 different candidate genes out of an initial set of 23,300 SNPs.

An assessment of the Irish population for large-scale genetic mapping studies involving epilepsy and other complex diseases

The recent completion of the International HapMap Project has rapidly advanced our understanding of linkage disequilibrium (LD) in the human genome. Today, tagging SNPs (tSNPs) can be quickly and easily selected and consequently HapMap data are regularly applied to both small- and large-scale genetic mapping studies. However, to correctly interpret the application of HapMap-derived tSNPs in a genetic mapping study, an understanding of how well HapMap data represents LD in the study population is critical. The Irish population had not previously been characterised in this way. Here, we do so using a set of 4424 SNPs selected from 279 candidate genes for epilepsy genotyped across 1118 healthy individuals from the Irish, British, Finnish and Australian populations. By considering the Irish population alongside surrounding European populations, our results confirm that the HapMap European-derived population accurately estimates patterning of LD in European descent populations. The Irish population appears notably well matched to the European HapMap population, and is markedly similar to the neighbouring British population. Although we were unable to detect significant substructure within the Irish population (a favourable result for genetic mapping), methods for controlling stratification should always be incorporated. This analysis therefore confirms that the genetic architecture of the Irish population is well suited to the study of complex traits and that tSNPs selected using the HapMap data can be confidently applied to the Irish population.

Using population mixtures to optimize the utility of genomic databases: linkage disequilibrium and association study design in India

When performing association studies in populations that have not been the focus of large-scale investigations of haplotype variation, it is often helpful to rely on genomic databases in other populations for study design and analysis - such as in the selection of tag SNPs and in the imputation of missing genotypes. One way of improving the use of these databases is to rely on a mixture of database samples that is similar to the population of interest, rather than using the single most similar database sample. We demonstrate the effectiveness of the mixture approach in the application of African, European, and East Asian HapMap samples for tag SNP selection in populations from India, a genetically intermediate region underrepresented in genomic studies of haplotype variation.

Chasing genes for mood disorders and schizophrenia in genetically isolated populations

Major affective disorders and schizophrenia are among the most common brain diseases worldwide and their predisposition is influenced by a complex interaction of genetic and environmental factors. So far, traditional linkage mapping studies for these complex disorders have not achieved the same success as the positional cloning of genes for Mendelian diseases. The struggle to identify susceptibility genes for complex disorders has stimulated the development of alternative approaches, including studies in genetically isolated populations. Since isolated populations are likely to have both a reduced number of genetic vulnerability factors and environmental background and are therefore considered to be more homogeneous compared to outbred populations, the use of isolated populations in genetic studies is expected to improve the chance of finding susceptibility loci and genes. Here we review the role of isolated populations, based on linkage and association studies, in the identification of susceptibility genes for bipolar disorder and schizophrenia.