Nonparametric Linkage Methods Research Articles

A quantitative trait rare variant nonparametric linkage method with application to age-at-onset of Alzheimer's disease.

To analyze pedigrees with quantitative trait (QT) and sequence data, we developed a rare variant (RV) quantitative nonparametric linkage (QNPL) method, which evaluates sharing of minor alleles. RV-QNPL has greater power than the traditional QNPL that tests for excess sharing of minor and major alleles. RV-QNPL is robust to population substructure and admixture, locus heterogeneity, and inclusion of nonpathogenic variants and can be readily applied outside of coding regions. When QNPL was used to analyze common variants, it often led to loci mapping to large intervals, e.g., >40 Mb. In contrast, when RVs are analyzed, regions are well defined, e.g., a gene. Using simulation studies, we demonstrate that RV-QNPL is substantially more powerful than applying traditional QNPL methods to analyze RVs. RV-QNPL was also applied to analyze age-at-onset (AAO) data for 107 late-onset Alzheimer's disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with whole-genome sequence data. When AAO of AD was analyzed regardless of APOE ε4 status, suggestive linkage (LOD = 2.4) was observed with RVs in KNDC1 and nominally significant linkage (p < 0.05) was observed with RVs in LOAD genes ABCA7 and IQCK. When AAO of AD was analyzed for APOE ε4 positive family members, nominally significant linkage was observed with RVs in APOE, while when AAO of AD was analyzed for APOE ε4 negative family members, nominal significance was observed for IQCK and ADAMTS1. RV-QNPL provides a powerful resource to analyze QTs in families to elucidate their genetic etiology.

A Rare Variant Nonparametric Linkage Method for Nuclear and Extended Pedigrees with Application to Late-Onset Alzheimer Disease via WGS Data

To analyze family-based whole-genome sequence (WGS) data for complex traits, we developed a rare variant (RV) non-parametric linkage (NPL) analysis method, which has advantages over association methods. The RV-NPL differs from the NPL in that RVs are analyzed, and allele sharing among affected relative-pairs is estimated only for minor alleles. Analyzing families can increase power because causal variants with familial aggregation usually have larger effect sizes than those underlying sporadic diseases. Differing from association analysis, for NPL only affected individuals are analyzed, which can increase power, since unaffected family members can be susceptibility variant carriers. RV-NPL is robust to population substructure and admixture, inclusion of nonpathogenic variants, as well as allelic and locus heterogeneity and can readily be applied outside of coding regions. In contrast to analyzing common variants using NPL, where loci localize to large genomic regions (e.g., >50 Mb), mapped regions are well defined for RV-NPL. Using simulation studies, we demonstrate that RV-NPL is substantially more powerful than applying traditional NPL methods to analyze RVs. The RV-NPL was applied to analyze 107 late-onset Alzheimer disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with WGS data, and statistically significant linkage (LOD ≥ 3.8) was found with RVs in PSMF1 and PTPN21 which have been shown to be involved in LOAD etiology. Additionally, nominally significant linkage was observed with RVs in ABCA7, ACE, EPHA1, and SORL1, genes that were previously reported to be associated with LOAD. RV-NPL is an ideal method to elucidate the genetic etiology of complex familial diseases.

Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms

Because of the high costs associated with ascertainment of families most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. While microsatellite markers spaced every 10 centimorgans typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carry out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 SNPs. Of the ~1100 families, 972 were informative for further analyses and mean information content was 0.86 after pruning for LD. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with Bipolar II disorder (BPII) and 702 subjects with Recurrent Major Depression. Three affection status models were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus Recurrent Major Depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (Nonparametric Pairs Lod 3.4 for rs1046943 at 119 cM) and 9q21 (Nonparametric Pairs Lod 3.4 for rs722642 at 78 cM) using only BPI and SA, BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis we observed 59 parametric lods of 2 or greater, many of which are likely to be close to maximum possible scores. While some linkage findings may be false positives the results could help prioritize the search for rare variants using whole exome or genome sequencing.

Robust Age at Onset Linkage Analysis in Nuclear Families

Objective: Standard methods for linkage analysis ignore the phenotype of the parents when they are not genotyped. However, this information can be useful for gene mapping. In this paper we propose methods for age at onset genetic linkage analysis in sibling pairs, taking into account parental age at onset. Methods:Two new score statistics are derived, one from an additive gamma frailty model and one from a log-normal frailty model. The score statistics are classical non-parametric linkage (NPL) statistics weighted by a function of the age at onset of the four family members. The weight depends on information from registries (age-specific incidences) and family studies (sib-sib and father-mother correlation). Results:In order to investigate how age at onset of sibs and their parents affect the information for linkage analysis the weight functions were studied for rare and common disease models, realistic models for breast cancer and human lifespan. We studied the performance of the weighted NPL methods by simulations. As illustration, the score statistics were applied to the GAW12 data. The results show that it is useful to include parental age at onset information in genetic linkage analysis.

Score test for age at onset genetic linkage analysis in selected sibling pairs

A new score statistic is derived, which uses information from registries (age-specific incidences) and family studies (sib-sib marginal correlation) to weight affected sibling pairs according to their age at onset. Age at onset of sibling pairs is modelled by a gamma frailty model. From this model we derive a bivariate survival function, which depends on the marginal survival and on the marginal correlation. The score statistic for linkage is a classical nonparametric linkage (NPL) statistic where the identical by descent sharing is weighted by a particular function of the age at onset data. Since the statistic is based on survival models, it can also be applied to discordant and healthy sibling pairs. Simulation studies show that the proposed method is robust and more powerful than standard NPL methods. As illustration we apply the new score statistic to data from a breast cancer study.

The cyclic GMP-dependent protein kinase II gene associates with gout disease: identified by genome-wide analysis and case–control study

Objective:To identify the position of a gout susceptibility gene.Methods:A genome-wide scan was performed using 382 random polymorphic microsatellite markers spread across 22 autosomes in a Taiwanese family with gout to...

Two-dimensional linkage analyses of rheumatoid arthritis

Rheumatoid arthritis (RA) is a multifactorial disease with complex genetic etiology, about which little is known. Here, we apply a two-stage procedure in which a quick first-stage analysis was used to narrow down targets for a more thorough and detailed testing for gene x gene interaction. Potentially interesting regions were first identified by testing for major gene effects using non-parametric linkage methods. To select regions of interest, we first tested for linkage to three different RA-related traits one at a time: RA affection status and the quantitative phenotypes rheumatoid factor IgM and anti-cyclic citrullinated peptide levels. These linkage analyses identified regions on chromosomes 3, 5, 6, 8, 16, 18, 19, and 20. We subsequently analyzed the selected regions in a pairwise manner to detect gene x gene interactions influencing RA using a recently developed two-dimensional linkage method. We found evidence of interacting loci on chromosomes 5, 6, and 18.

Comparison of affected sibling-pair linkage methods to identify gene x gene interaction in GAW15 simulated data.

Non-parametric linkage methods have had limited success in detecting gene by gene interactions. Using affected sibling-pair (ASP) data from all replicates of the simulated data from Problem 3, we assessed the statistical power of three approaches to identify the gene x gene interaction between two loci on different chromosomes. The first method conditioned on linkage at the primary disease susceptibility locus (DR), to find linkage to a simulated effect modifier at Locus A with a mean allele sharing test. The second approach used a regression-based mean test to identify either the presence of interaction between the two loci or linkage to the A locus in the presence of linkage to DR. The third method applied a conditional logistic model designed to test for the presence of interacting loci. The first approach had decreased power over an unconditional linkage analysis, supporting the idea that gene x gene interaction cannot be detected with ASP data. The regression-based mean test and the conditional logistic model had the lowest power to detect gene x gene interaction, possibly because of the complex recoding of the tri-allelic DR locus for use as a covariate. We conclude that the ASP approaches tested have low power to successfully identify the interaction between the DR and A loci despite the large sample size, which may be due to the low prevalence of the high-risk DR genotypes. Additionally, the lack of data on discordant sibships may have decreased the power to identify gene x gene interactions.

European Mathematical Genetics Meeting, Heidelberg, Germany, 12th–13th April 2007

European Mathematical Genetics Meeting, Heidelberg, Germany, 12^th–13^th April 2007

Fine-Mapping Chromosome 20 in 230 Systemic Lupus Erythematosus Sib Pair and Multiplex Families: Evidence for Genetic Epistasis with Chromosome 16q12

The presence of systemic lupus erythematosus (SLE) susceptibility genes on chromosome 20 is suggested by the observation of genetic linkage in several independent SLE family collections. To further localize the genetic effects, we typed 59 microsatellites in the two best regions, as defined by genome screens. Genotypes were analyzed for statistical linkage and/or association with SLE, by use of a combination of nonparametric linkage methods, family-based tests of association (transmission/disequilibrium and pedigree disequilibrium tests), and haplotype-sharing statistics (haplotype runs test), in a set of 230 SLE pedigrees. Maximal evidence for linkage to SLE was to 20p12 (LOD = 2.84) and 20q13.1 (LOD = 1.64) in the white pedigrees. Subsetting families on the basis of evidence for linkage to 16q12 significantly improved the LOD scores at both chromosome 20 locations (20p12 LOD = 5.06 and 20q13 LOD = 3.65), consistent with epistasis. We then typed 162 single-nucleotide polymorphism markers across a 1.3-Mb candidate region on 20q13.1 and identified several SNPs that demonstrated significant evidence for association. These data provide additional support for linkage and association to 20p12 and 20q13.1 in SLE and further refine the intervals of interest. These data further suggest the possibility of epistatic relationships among loci within the 20q12, 20q13, and 16q12 regions in SLE families.

Comparison of single-nucleotide polymorphisms and microsatellites in detecting quantitative trait loci for alcoholism: The Collaborative Study on the Genetics of Alcoholism

BackgroundThe feasibility of effectively analyzing high-density single nucleotide polymorphism (SNP) maps in whole genome scans of complex traits is not known. The purpose of this study was to compare variance components linkage results using different density marker maps in data from the Collaborative Study on the Genetics of Alcoholism (COGA). Marker maps having an average spacing of 10 cM (microsatellite), 0.78 cM (SNP1), and 0.31 cM (SNP2) were used to identify quantitative trait loci (QTLs) affecting maximum number of alcoholic drinks consumed in a 24-hour period (lnmaxalc).ResultsHeritability of lnmaxalc was estimated to be 15%. Multipoint variance components linkage analysis revealed similar linkage patterns among the three marker panels, with the SNP maps consistently yielding higher LOD scores. Robust LOD scores > 1.0 were observed on chromosomes 1 and 13 for all three marker maps. Additional LODs > 1.0 were observed on chromosome 4 with both SNP maps and on chromosomes 18 and 21 with the SNP2 map. Peak LOD scores for lnmaxalc were observed on chromosome 1, although none reached genome-wide statistical significance. Quantile-quantile plots revealed that the multipoint distribution of SNP results appeared to fit the asymptotic null distribution better than the twopoint results.ConclusionIn conclusion, variance-components linkage analysis using high-density SNP maps provided higher LOD scores compared with the standard microsatellite map, similar to studies using nonparametric linkage methods. Widespread application of SNP maps will depend on further improvements in the computational methods implemented in current software packages.

Testing for genetic associations in a spina bifida population: analysis of the HOX gene family and human candidate gene regions implicated by mouse models of neural tube defects.

Neural tube defects (NTDs) are among the most common severely disabling birth defects in the United States, affecting approximately 1-2 of every 1,000 live births. The etiology of NTDs is multifactorial, involving the combined action of both genetic and environmental factors. HOX genes play a central role in establishing the initial body plan by providing positional information along the anterior-posterior body and limb axis and have been implicated in neural tube closure. There are many mouse models that exhibit both naturally occurring NTDs in various mouse strains as well as NTDs that have been created by "knocking out" various genes. A nonparametric linkage method, the transmission disequilibrium test (TDT), was utilized to test the HOX gene family and human equivalents of genes (when known) or the syntenic region in humans to those in mouse models which could play a role in the formation of NTDs. DNA from 459 spina bifida (SB) affected individuals and their parents was tested for linkage and association utilizing polymorphic markers from within or very close to the HOXA, HOXB, HOXC, and HOXD genes as well as from within the genes/gene regions of eight mouse models that exhibit NTDs. No significant findings were obtained for the tested markers.

Testing for genetic associations with the PAX gene family in a spina bifida population.

Neural tube defects (NTDs) are among the most common severely disabling birth defects in the United States, affecting approximately 1-2 of every 1,000 live births. The etiology of NTDs is multifactorial, involving the combined action of both genetic and environmental factors. A nonparametric linkage method, the transmission disequilibrium test (TDT), was utilized to determine if the genes in the PAX family play a role in the formation of NTDs. DNA from 459 spina bifida (SB) patients and their parents (430 mothers and 239 fathers, for a total population of 1,128 subjects) was tested for linkage and association utilizing polymorphic markers from within or very close to the PAX genes of interest. Significant findings were obtained for the following markers: marker locus D20S101 flanking the PAX1 gene (P = 0.019), marker locus D1S228 within the PAX7 gene (P = 0.011), and marker locus D2S110 within the PAX8 gene (P = 0.013). Even though our findings are only mildly significant, given the known expression patterns of the PAX genes in development and the availability of their sequences, we elected to follow up these results by testing these genes directly for mutations utilizing single-strand conformational analysis (SSCA) and direct sequencing. Multiple variations were detected in each of the PAX genes with significant TDT results; however, these variations were not passed from parent to child in phase with the positively transmitted allele. Therefore, it is unlikely that these variations contribute to susceptibility for SB, but rather are previously unreported polymorphisms.

The Wellcome trust UK-Irish bipolar affective disorder sibling-pair genome screen: first stage report.

We have completed the first stage of a two-stage genome wide screen designed to identify chromosomal regions that may harbour susceptibility genes for bipolar affective disorder. The first stage screening sample included 509 subjects from 151 nuclear families recruited within the United Kingdom and Republic of Ireland. This sample contained 154 narrowly defined affected sibling pairs (DSM-IV BPI) and 258 broadly defined affected sibling pairs (DSM-IV BPI, SABP, BPII, BPNOS or MDD(R)), approximately two thirds of all families contained at least one other additional typed individual. All individuals were genotyped using 398 highly polymorphic microsatellite markers from Applied Biosystems's Linkage Mapping Set Version 2. The average inter-marker distance was 9.6 cM and the mean heterozygosity was 0.78. Analysis of these data using non-parametric linkage methods (MAPMAKER/SIBS) found no evidence for loci of major effect and no regions reached genome-wide significance for either suggestive or significant linkage. We identified 19 points across the genome where the MLS exceeded a value set for follow up in our second stage screen (MLS > or = 0.74 (equivalent to a nominal pointwise significance of 5%) under the narrowest diagnostic model). These points were on chromosomes 2, 3, 4, 6, 7, 9, 10, 12, 17, 18 & X. Some of these points overlapped with previous linkage reports both within bipolar affective disorder and other psychiatric illnesses. Under the narrowest diagnostic model, the single most significant multipoint linkage was on chromosome 18 at marker D18S452 (MLS=1.54). Overall the highest MLS was 1.70 on chromosome 2 at marker D2S125, under the broadest diagnostic model.

Testing for Gene–Gene Interaction Controlling Total IgE in Families from Barbados: Evidence of Sensitivity Regarding Linkage Heterogeneity among Families

Genetic heterogeneity has been proposed as a hallmark feature of allergic disease. To test the hypothesis that total IgE levels are jointly influenced by a locus on chromosome 12q21.1–q21.31 and a locus on 17q11.2–q21.2, we conducted multipoint allele-sharing analyses using nonparametric linkage (NPL) methods on Afro-Caribbean families from Barbados to test for evidence of gene–gene interactions. Significant correlations were observed between NPL scores at D12S1052 and both D17S1293 and D17S1299 for a dichotomized phenotype of total IgE. An analysis of family-specific NPL scores revealed that evidence for interaction was being driven largely by one multiplex pedigree (NPL = 12.01, 12.23, and 12.16 at D12S1052, D17S1293, and D17S1299, respectively). Using the programs SIMWALK (v2.0) and GOLD, a different set of haplotypes in this influential family was observed around D12S1052 and the 17q loci compared to the other Barbados pedigrees. Our findings are a classic example of founder effect, provide evidence for sensitivity of this type of linkage analysis to unusual pedigrees, and highlight an element of genetic heterogeneity that has been given little attention in the study of complex traits.

Impact of overlapping recruitment on linkage analysis of complex disorders: Simulation studies

Evidence for significant linkage in complexly inherited disorders usually necessitates independent, replicative studies. This study investigates the implications of including in the replicative studies families already used to suggest linkage in initial linkage analysis. We generated 1,000 unlinked replicates of 100 nuclear families with a complexly inherited disease but with no linkage to the markers analyzed. We then used a standard nonparametric linkage method to analyze these data. From the original 1,000 replicates of the original data set, one set was chosen as it yielded suggestive, but falsely positive, linkage results (LOD score = 3.4). Variable numbers of randomly selected families from this positive replicate (n = 100 families) were used to replace families in replicates of the original (unlinked) data set, and linkage analysis repeated. Overlap of families from the "positive data set" did increase the LOD scores for "unlinked data sets." While a small amount of overlap (replacement) between a positive linkage result and the replication sample is unlikely in practice to alter results, our study suggests that steps should be taken to ensure that overlap is minimized. The implications of this overlapping recruitment on replicative linkage studies are discussed.

Atopy and asthma genes--where do we stand?

Atopy and asthma genes--where do we stand?

Linkage of mood disorders with D2, D3 and TH genes: a multicenter study

Background: It has been suggested that the dopaminergic system is involved in the pathophysiology of mood disorders. We conducted a multicenter study of families with mood disorders, to investigate a possible linkage with genes coding for dopamine receptor D2, dopamine receptor D3 and tyrosine hydroxylase (TH). Methods: Twenty three mood disorder pedigrees collected within the framework of the European Collaborative Project on Affective Disorders were analyzed with parametric and non-parametric linkage methods. Various potential phenotypes were considered, from a narrow (only bipolar as affected) to a broad (bipolar+major depressive+schizoaffective disorders) definition of affection status. Results: Parametric analyses excluded linkage for all the candidate genes, even though small positive LOD (Limit of Detection) scores were observed for TH in three families. Non-parametric analyses yielded negative results for all markers. Conclusion: The D2 and D3 dopamine receptors were, therefore, not a major liability factor for mood disorders in our sample, whereas TH may play a role in a subgroup of patients.

Combined sib-TDT and TDT provide evidence for linkage of the interleukin-1 gene cluster to erosive rheumatoid arthritis.

Rheumatoid arthritis (RA) is a common disease of unknown aetiology which usually causes progressive destruction of the joints. Familial aggregation, twin studies and segregation analyses suggest that there is a genetic component to RA and the HLA-DRB1 locus in the major histocompatibility complex on chromosome 6 has been shown to be linked to, and associated with, RA susceptibility. It is likely that other genes with weaker effects are also involved, which may be difficult to detect using conventional parametric and non-parametric linkage methods. We have implemented the combined sib-TDT and TDT, in addition to parametric and non-parametric linkage methods, to investigate the candidate genes of the interleukin-1 (IL-1) gene cluster on chromosome region 2q13, since IL-1 is an important cytokine in the control of the inflammatory response that is central to RA pathology. Several tightly linked IL-1 cluster markers yielded suggestive evidence for linkage in the combined TDT in those families in which affected siblings did not share two HLA-DRB1 alleles identical by descent. The evidence was significant in those with severe disease, as assessed by the presence of bone erosions. In contrast, there was no evidence of linkage using non-parametric linkage analysis, but parametric analysis revealed weak evidence of linkage when marker-trait disequilibrium was incorporated into the analysis. The data provide preliminary evidence for linkage of genes of the IL-1 cluster to RA and suggest a possible role for this region in severe erosive disease.

Genome-wide scan for autism susceptibility genes. Paris Autism Research International Sibpair Study.

Family and twin studies have suggested a genetic component in autism. We performed a genome-wide screen with 264 microsatellites markers in 51 multiplex families, using non-parametric linkage methods. Families were recruited by a collaborative group including clinicians from Sweden, France, Norway, the USA, Italy, Austria and Belgium. Using two-point and multipoint affected sib-pair analyses, 11 regions gave nominal P -values of 0.05 or lower. Four of these regions overlapped with regions on chromosomes 2q, 7q, 16p and 19p identified by the first genome-wide scan of autism performed by the International Molecular Genetic Study of Autism Consortium. Another of our potential susceptibility regions overlapped with the 15q11-q13 region identified in previous candidate gene studies. Our study revealed six additional regions on chromosomes 4q, 5p, 6q, 10q, 18q and Xp. We found that the most significant multipoint linkage was close to marker D6S283 (maximum lod score = 2.23, P = 0.0013).