Genome Scan Meta-analysis Research Articles

Meta-Analysis of Repository Data: Impact of Data Regularization on NIMH Schizophrenia Linkage Results

Human geneticists are increasingly turning to study designs based on very large sample sizes to overcome difficulties in studying complex disorders. This in turn almost always requires multi-site data collection and processing of data through centralized repositories. While such repositories offer many advantages, including the ability to return to previously collected data to apply new analytic techniques, they also have some limitations. To illustrate, we reviewed data from seven older schizophrenia studies available from the NIMH-funded Center for Collaborative Genomic Studies on Mental Disorders, also known as the Human Genetics Initiative (HGI), and assessed the impact of data cleaning and regularization on linkage analyses. Extensive data regularization protocols were developed and applied to both genotypic and phenotypic data. Genome-wide nonparametric linkage (NPL) statistics were computed for each study, over various stages of data processing. To assess the impact of data processing on aggregate results, Genome-Scan Meta-Analysis (GSMA) was performed. Examples of increased, reduced and shifted linkage peaks were found when comparing linkage results based on original HGI data to results using post-processed data within the same set of pedigrees. Interestingly, reducing the number of affected individuals tended to increase rather than decrease linkage peaks. But most importantly, while the effects of data regularization within individual data sets were small, GSMA applied to the data in aggregate yielded a substantially different picture after data regularization. These results have implications for analyses based on other types of data (e.g., case-control GWAS or sequencing data) as well as data obtained from other repositories.

Meta-analyses of genome-wide linkage scans of anxiety-related phenotypes

Genetic factors underlying trait neuroticism, reflecting a tendency towards negative affective states, may overlap genetic susceptibility for anxiety disorders and help explain the extensive comorbidity amongst internalizing disorders. Genome-wide linkage (GWL) data from several studies of neuroticism and anxiety disorders have been published, providing an opportunity to test such hypotheses and identify genomic regions that harbor genes common to these phenotypes. In all, 11 independent GWL studies of either neuroticism (n=8) or anxiety disorders (n=3) were collected, which comprised of 5341 families with 15 529 individuals. The rank-based genome scan meta-analysis (GSMA) approach was used to analyze each trait separately and combined, and global correlations between results were examined. False discovery rate (FDR) analysis was performed to test for enrichment of significant effects. Using 10 cM intervals, bins nominally significant for both GSMA statistics, P(SR) and P(OR), were found on chromosomes 9, 11, 12, and 14 for neuroticism and on chromosomes 1, 5, 15, and 16 for anxiety disorders. Genome-wide, the results for the two phenotypes were significantly correlated, and a combined analysis identified additional nominally significant bins. Although none reached genome-wide significance, an excess of significant P(SR)P-values were observed, with 12 bins falling under a FDR threshold of 0.50. As demonstrated by our identification of multiple, consistent signals across the genome, meta-analytically combining existing GWL data is a valuable approach to narrowing down regions relevant for anxiety-related phenotypes. This may prove useful for prioritizing emerging genome-wide association data for anxiety disorders.

Genetic evidence for the association between the early growth response 3 (EGR3) gene and schizophrenia.

Recently, two genome scan meta-analysis studies have found strong evidence for the association of loci on chromosome 8p with schizophrenia. The early growth response 3 (EGR3) gene located in chromosome 8p21.3 was also found to be involved in the etiology of schizophrenia. However, subsequent studies failed to replicate this finding. To investigate the genetic role of EGR3 in Chinese patients, we genotyped four SNPs (average interval ∼2.3 kb) in the chromosome region of EGR3 in 470 Chinese schizophrenia patients and 480 healthy control subjects. The SNP rs35201266 (located in intron 1 of EGR3) showed significant differences between cases and controls in both genotype frequency distribution (P = 0.016) and allele frequency distribution (P = 0.009). Analysis of the haplotype rs35201266-rs3750192 provided significant evidence for association with schizophrenia (P = 0.0012); a significant difference was found for the common haplotype AG (P = 0.0005). Furthermore, significant associations were also found in several other two-, and three-SNP tests of haplotype analyses. The meta-analysis revealed a statistically significant association between rs35201266 and schizophrenia (P = 0.0001). In summary, our study supports the association of EGR3 with schizophrenia in our Han Chinese sample, and further functional exploration of the EGR3 gene will contribute to the molecular basis for the complex network underlying schizophrenia pathogenesis.

Voxelwise meta-analysis of gray matter reduction in major depressive disorder

Voxel-based morphometry (VBM) has been widely used in studies of major depressive disorder (MDD) and has provided cumulative evidence of gray matter abnormalities in patients relative to controls. Thus we performed a meta-analysis to integrate the reported studies to determine the consistent gray matter alterations in MDD. A systematic search was conducted to identify VBM studies which contrasted MDD patients against a comparison group. The coordinates of gray matter change across studies were meta-analyzed using the activation likelihood estimation (ALE) method hybridized with the rank-based Genome Scan Meta-Analysis (GSMA) to quantitatively estimate regional gray matter reductions in MDD. A total of 20 VBM studies comparing 543 major depressive patients with 750 healthy control subjects were included. Consistent gray matter reductions in all MDD patients relative to healthy controls were identified in the bilateral anterior cingulate cortex (ACC), right middle and inferior frontal gyrus, right hippocampus and left thalamus. Meta-analysis of all primary VBM studies indicates that significant gray matter reductions in MDD are localized in a distributed neural network which includes frontal, limbic and thalamic regions. Future studies will benefit from the use of a longitudinal approach to examine anatomical and functional abnormalities within this network and their relationship to clinical profile, particularly in first-episode and drug-naive MDD patients.

Meta-analysis of genome-wide linkage scans for renal function traits

Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance. We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance. No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information. While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.

HLA DRB1*1503 allelic haplotype predominance and associated immunodysregulation in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic, relapsing, and remitting disease affecting primarily African American females of child bearing age. Familial aggregation of this disease suggests that at least part of the susceptibility for this disease is genetic, although environmental and hormonal influences are also likely to play a role. Early studies of genetic susceptibility to SLE revealed several of the major histocompatibility complex molecules, namely HLA DR, to be linked to SLE. Meta-analysis of genome scans has yielded loci significant for lupus patients, one of which includes the MHC region. Regulatory T cells are immunoregulatory cells that modulate activated immune cells. These cells play a large role in homeostasis of the immune responses and maintenance of immunologic tolerance, i.e., prevention of autoimmunity. Decreased numbers of regulatory T cells have been described in many autoimmune diseases, including systemic lupus erythematosus. Autoantibody production in systemic lupus erythematosus and the resulting immune complex formation and complex deposition into tissues are arguably the central core of immune dysregulation leading to disease manifestations and symptoms. Inability of the immune system to recognize and inhibit autoreactive immune cells in this particular autoimmune disease may be the result of inappropriate numbers and function of regulatory T cells. This study aims to characterize the immune cell population in patients from our community suffering from systemic lupus erythematosus and to prove that these patients exhibit a unique cellular profile compared to healthy age, race and gender matched control subjects. Surprisingly, our findings demonstrate that patients from the local Mississippi area exhibit increased proportions of CD25 + FoxP3 + regulatory T cells and CD25 + FoxP3 − T cells (of CD45 + CD3 + CD4 + helper T cells) as compared to healthy controls. HLA tissue-typing of these lupus patients revealed a prominent subgroup (~ 30%) of patients possessing the HLA DRB1*1503 allele. The investigation of this subgroup demonstrated regulatory T cell composition similar to that of the total lupus group and to that of the non-HLA DRB1*1503 subgroup. Genetic analysis for molecular gene expression levels of various lupus-associated genes by real-time PCR demonstrated a unique profile as compared to healthy controls. Increased gene expression of FoxP3 together with decreased gene expression levels of GATA3, TNFAIP3, and TNFSF4 suggest that variations in gene products compared to healthy controls may be playing a role in the immune cell dysregulation and disproportionate CD25 + FoxP3 + regulatory T cells.

Identification of QTL genes for BMD variation using both linkage and gene-based association approaches

Low bone mineral density (BMD) is a risk factor for osteoporotic fracture with a high heritability. Previous large scale linkage study in Northern Chinese has identified four significant quantitative trait loci (QTL) for BMD variation on chromosome 2q24, 5q21, 7p21 and 13q21. We performed a replication study of these four QTL in 1,459 Southern Chinese from 306 pedigrees. Successful replication was observed on chromosome 5q21 for femoral neck BMD with a LOD score of 1.38 (nominal p value = 0.006). We have previously identified this locus in a genome scan meta-analysis of BMD variation in a white population. Subsequent QTL-wide gene-based association analysis in 800 subjects with extreme BMD identified CAST and ERAP1 as novel BMD candidate genes (empirical p value of 0.032 and 0.014, respectively). The associations were independently replicated in a Northern European population (empirical p value of 0.01 and 0.004 for CAST and ERAP1, respectively). These findings provide further evidence that 5q21 is a BMD QTL, and CAST and ERAP1 may be associated with femoral neck BMD variation.Electronic supplementary materialThe online version of this article (doi:10.1007/s00439-011-0972-2) contains supplementary material, which is available to authorized users.

PL.02.01 CSF biomarkers in Alzheimer's disease – use in clinical diagnosis and to monitor treatment effects

Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (Ravg) and then weighted for sample size ( N[affected cases]). A permutation test was used to compute the probability of observing, by chance, each bin’s average rank (PAvgRnk) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (Pord). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk<.000417). Two aggregate criteria for linkage were also met (clusters of nominally significant P values that did not occur in 1,000 replicates of the entire data set with no linkage present): 12 consecutive bins with both PAvgRnk and Pord<.05, including regions of chromosomes 5q, 3p, 11q, 6p, 1q, 22q, 8p, 20q, and 14p, and 19 consecutive bins with Pord<.05, additionally including regions of chromosomes 16q, 18q, 10p, 15q, 6q, and 17q. There is greater consistency of linkage results across studies than has been previously recognized. The results suggest that some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse populations.

Meta-analysis of 20 genome-wide linkage studies evidenced new regions linked to asthma and atopy

Asthma is caused by a heterogeneous combination of environmental and genetic factors. In the context of GA2LEN (Global Allergy and Asthma European Network), we carried out meta-analyses of almost all genome-wide linkage screens conducted to date in 20 independent populations from different ethnic origins (>or=3024 families with >or=10 027 subjects) for asthma, atopic asthma, bronchial hyper-responsiveness and five atopy-related traits (total immunoglobulin E level, positive skin test response (SPT) to at least one allergen or to House Dust Mite, quantitative score of SPT (SPTQ) and eosinophils (EOS)). We used the genome scan meta-analysis method to assess evidence for linkage within bins of traditionally 30-cM width, and explored the manner in which these results were affected by bin definition. Meta-analyses were conducted in all studies and repeated in families of European ancestry. Genome-wide evidence for linkage was detected for asthma in two regions (2p21-p14 and 6p21) in European families ascertained through two asthmatic sibs. With regard to atopy phenotypes, four regions reached genome-wide significance: 3p25.3-q24 in all families for SPT and three other regions in European families (2q32-q34 for EOS, 5q23-q33 for SPTQ and 17q12-q24 for SPT). Tests of heterogeneity showed consistent evidence of linkage of SPTQ to 3p11-3q21, whereas between-study heterogeneity was detected for asthma in 2p22-p13 and 6p21, and for atopic asthma in 1q23-q25. This large-scale meta-analysis provides an important resource of information that can be used to prioritize further fine-mapping studies and also be integrated with genome-wide association studies to increase power and better interpret the outcomes of these studies.

Meta-analysis of Genome-Wide Linkage Studies of Atopic Dermatitis

Atopic dermatitis (AD) is considered as a hereditary skin disease. Recently, a latest form of genetic research, genome-wide linkage study, has been carried out to detect its specific susceptibility genes. Since the results of these studies have been inconsistent, with linkage confirmed in different regions, we performed this meta-analysis. To assess heritability and identify chromosomal regions showing evidence of AD. A comprehensive and systematic search was conducted with PubMed databases. We combined results from three non-overlapping genome-wide linkage studies of AD, using the heterogeneity-based genome scan meta-analysis (HEGESMA) method, a rank-based analysis that assesses the strongest evidence for linkage within bins of a 30-centimorgan width on autosomes and the X chromosome. The following ten bins had a p value of less than .05 in both weighted and unweighted analyses, suggesting that these bins contain AD-linked loci: 3.2, 3.4, 3.5, 4.5, 5.1, 5.2, 6.3, 9.2, 9.4, and 22.1. HEGESMA produced significant genome-wide evidence for linkage on 3p14.1-q12.3, with high average rank and low between-study heterogeneity; 5pter-p15.1 represents new significant loci not reported previously. HEGESMA confirms the region encoding CD80, CD86, and interleukins on chromosomes 3 and 5. The filaggrin gene (FLG) may be the susceptibility factor.

Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci

We report the results of a meta-analysis of genome-wide association scans for multiple sclerosis (MS) susceptibility that includes 2,624 subjects with MS and 7,220 control subjects. Replication in an independent set of 2,215 subjects with MS and 2,116 control subjects validates new MS susceptibility loci at TNFRSF1A (combined P = 1.59 x 10(-11)), IRF8 (P = 3.73 x 10(-9)) and CD6 (P = 3.79 x 10(-9)). TNFRSF1A harbors two independent susceptibility alleles: rs1800693 is a common variant with modest effect (odds ratio = 1.2), whereas rs4149584 is a nonsynonymous coding polymorphism of low frequency but with stronger effect (allele frequency = 0.02; odds ratio = 1.6). We also report that the susceptibility allele near IRF8, which encodes a transcription factor known to function in type I interferon signaling, is associated with higher mRNA expression of interferon-response pathway genes in subjects with MS.

Meta-analysis of diffusion tensor imaging studies in schizophrenia

The objective of the study was to identify whether there are consistent regional white matter changes in schizophrenia. A systematic search was conducted for voxel-based diffusion tensor imaging fractional anisotropy studies of patients with schizophrenia (or related disorders) in relation to comparison groups. The authors carried out meta-analysis of the co-ordinates of fractional anisotropy differences. For the meta-analysis they used the Activation Likelihood Estimation (ALE) method hybridized with the rank approach used in Genome Scan Meta-Analysis (GSMA). This system detects three-dimensional conjunctions of co-ordinates from multiple studies and permits the weighting of studies in relation to sample size. Fifteen articles were identified for inclusion in the meta-analysis, including a total of 407 patients with schizophrenia and 383 comparison subjects. The studies reported fractional anisotropy reductions at 112 co-ordinates in schizophrenia and no fractional anisotropy increases. Over all studies, significant reductions were present in two regions: the left frontal deep white matter and the left temporal deep white matter. The first region, in the left frontal lobe, is traversed by white matter tracts interconnecting the frontal lobe, thalamus and cingulate gyrus. The second region, in the temporal lobe, is traversed by white matter tracts interconnecting the frontal lobe, insula, hippocampus–amygdala, temporal and occipital lobe. This suggests that two networks of white matter tracts may be affected in schizophrenia, with the potential for ‘disconnection’ of the gray matter regions which they link.

F.27. Meta-analysis of Genome Scans and Replication Identify CD6, ICSBP1, and TNFRSF1A as Novel Multiple Sclerosis Susceptibility Loci

F.27. Meta-analysis of Genome Scans and Replication Identify CD6, ICSBP1, and TNFRSF1A as Novel Multiple Sclerosis Susceptibility Loci

Meta-Analysis of Genome-Wide Linkage Studies in Celiac Disease

Objective: A meta-analysis of genome-wide linkage studies allows us to summarize the extensive information available from family-based studies, as the field moves into genome-wide association studies. Methods: Here we apply the genome scan meta-analysis (GSMA) method, a rank-based, model-free approach, to combine results across eight independent genome-wide linkages performed on celiac disease (CD), including 554 families with over 1,500 affected individuals. We also investigate the agreement between signals we identified from this meta-analysis of linkage studies and those identified from genome-wide association analysis using a hypergeometric distribution. Results: Not surprisingly, the most significant result was obtained in the HLA region. Outside the HLA region, suggestive evidence for linkage was obtained at the telomeric region of chromosome 10 (10q26.12-qter; p = 0.00366), and on chromosome 8 (8q22.2-q24.21; p = 0.00491). Testing signals of association and linkage within bins showed no significant evidence for co-localization of results. Conclusion: This meta-analysis allowed us to pool the results from available genome-wide linkage studies and to identify novel regions potentially harboring predisposing genetic variation contributing to CD. This study also shows that linkage and association studies may identify different types of disease-predisposing variants.

Meta-analysis of 32 genome-wide linkage studies of schizophrenia.

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (P(SR)) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for 'aggregate' genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

Meta-analysis of genome-wide linkage scans of attention deficit hyperactivity disorder.

Genetic contribution to the development of attention deficit hyperactivity disorder (ADHD) is well established. Seven independent genome-wide linkage scans have been performed to map loci that increase the risk for ADHD. Although significant linkage signals were identified in some of the studies, there has been limited replications between the various independent datasets. The current study gathered the results from all seven of the ADHD linkage scans and performed a Genome Scan Meta Analysis (GSMA) to identify the genomic region with most consistent linkage evidence across the studies. Genome-wide significant linkage (P(SR) = 0.00034, P(OR) = 0.04) was identified on chromosome 16 between 64 and 83 Mb. In addition there are nine other genomic regions from the GSMA showing nominal or suggestive evidence of linkage. All these linkage results may be informative and focus the search for novel ADHD susceptibility genes.

Meta-analysis of genome-wide linkage studies across autoimmune diseases

Autoimmune diseases are chronic disorders initiated by a loss of immunologic tolerance to self-antigens. They cluster within families, and patients may be diagnosed with more than one disease, suggesting pleiotropic genes are involved in the aetiology of different diseases. To identify potential loci, which confer susceptibility to autoimmunity independent of disease phenotype, we pooled results from genome-wide linkage studies, using the genome scan meta-analysis method (GSMA). The meta-analysis included 42 independent studies for 11 autoimmune diseases, using 7350 families with 18 291 affected individuals. In addition to the HLA region, which showed highly significant genome-wide evidence for linkage, we obtained suggestive evidence for linkage on chromosome 16, with peak evidence at 10.0-19.8 Mb. This region may harbour a pleiotropic gene (or genes) conferring risk for several diseases, although no such gene has been identified through association studies. We did not identify evidence for linkage at several genes known to confer increased risk to different autoimmune diseases (PTPN22, CTLA4), even in subgroups of diseases consistently found to be associated with these genes. The relative risks conferred by variants in these genes are modest (<1.5 in most cases), and even a large study like this meta-analysis lacks power to detect linkage. This study illustrates the concept that linkage and association studies have power to identify very different types of disease-predisposing variants.

Structural brain change in Attention Deficit Hyperactivity Disorder identified by meta-analysis

BackgroundThe authors sought to map gray matter changes in Attention Deficit Hyperactivity Disorder (ADHD) using a novel technique incorporating neuro-imaging and genetic meta-analysis methods.MethodsA systematic search was conducted for voxel-based structural magnetic resonance imaging studies of patients with ADHD (or with related disorders) in relation to comparison groups. The authors carried out meta-analyses of the co-ordinates of gray matter differences. For the meta-analyses they hybridised the standard method of Activation Likelihood Estimation (ALE) with the rank approach used in Genome Scan Meta-Analysis (GSMA). This system detects three-dimensional conjunctions of co-ordinates from multiple studies and permits the weighting of studies in relation to sample size.ResultsFor gray matter decreases, there were 7 studies including a total of 114 patients with ADHD (or related disorders) and 143 comparison subjects. Meta-analysis of these studies identified a significant regional gray matter reduction in ADHD in the right putamen/globus pallidus region. Four studies reported gray matter increases in ADHD but no regional increase was identified by meta-analysis.ConclusionIn ADHD there is gray matter reduction in the right putamen/globus pallidus region. This may be an anatomical marker for dysfunction in frontostriatal circuits mediating cognitive control. Right putamen lesions have been specifically associated with ADHD symptoms after closed head injuries in children.

Meta-analysis of genome-wide linkage studies of asthma and related traits

BackgroundAsthma and allergy are complex multifactorial disorders, with both genetic and environmental components determining disease expression. The use of molecular genetics holds great promise for the identification of novel drug targets for the treatment of asthma and allergy. Genome-wide linkage studies have identified a number of potential disease susceptibility loci but replication remains inconsistent. The aim of the current study was to complete a meta-analysis of data from genome-wide linkage studies of asthma and related phenotypes and provide inferences about the consistency of results and to identify novel regions for future gene discovery.MethodsThe rank based genome-scan meta-analysis (GSMA) method was used to combine linkage data for asthma and related traits; bronchial hyper-responsiveness (BHR), allergen positive skin prick test (SPT) and total serum Immunoglobulin E (IgE) from nine Caucasian asthma populations.ResultsSignificant evidence for susceptibility loci was identified for quantitative traits including; BHR (989 pedigrees, n = 4,294) 2p12-q22.1, 6p22.3-p21.1 and 11q24.1-qter, allergen SPT (1,093 pedigrees, n = 4,746) 3p22.1-q22.1, 17p12-q24.3 and total IgE (729 pedigrees, n = 3,224) 5q11.2-q14.3 and 6pter-p22.3. Analysis of the asthma phenotype (1,267 pedigrees, n = 5,832) did not identify any region showing genome-wide significance.ConclusionThis study represents the first linkage meta-analysis to determine the relative contribution of chromosomal regions to the risk of developing asthma and atopy. Several significant results were obtained for quantitative traits but not for asthma confirming the increased phenotype and genetic heterogeneity in asthma. These analyses support the contribution of regions that contain previously identified asthma susceptibility genes and provide the first evidence for susceptibility loci on 5q11.2-q14.3 and 11q24.1-qter.

Novel approach for genome scan meta-analysis of rheumatoid arthritis: a kernel-based estimation procedure

Genome scan meta-analysis (GSMA) can prove very useful in detecting genetic effects too small to be detected in an individual linkage study and can also lead to more consistent results. In this paper, we propose a new kernel-based estimation procedure for GSMA. Instead of estimating identity by descent between markers, as performed in interval mapping approaches, we estimated directly the nonparametric linkage score between markers using a kernel procedure. The GSMA is then extended to take into account the kernel estimate of the nonparametric linkage score and its variance at a given chromosomal position. The method is applied to the rheumatoid arthritis genome scan data (Genetic Analysis Workshop 15 Problem 2).