Combined analysis of three whole genome linkage scans for Ankylosing Spondylitis

Objective. Ankylosing spondylitis (AS) is a debilitating chronic inflammatory condition with a high degree of familiality (λs=82) and heritability (>90%) that primarily affects spinal and sacroiliac joints. Whole genome scans for linkage to AS phenotypes have been conducted, although results have been inconsistent between studies and all have had modest sample sizes. One potential solution to these issues is to combine data from multiple studies in a retrospective meta-analysis. Methods: The International Genetics of Ankylosing Spondylitis Consortium combined data from three whole genome linkage scans for AS (n=3744 subjects) to determine chromosomal markers that show evidence of linkage with disease. Linkage markers typed in different centres were integrated into a consensus map to facilitate effective data pooling. We performed a weighted meta-analysis to combine the linkage results, and compared them with the three individual scans and a combined pooled scan. Results: In addition to the expected region surrounding the HLA-B27 gene on chromosome 6, we determined that several marker regions showed significant evidence of linkage with disease status. Regions on chromosome 10q and 16q achieved 'suggestive' evidence of linkage, and regions on chromosomes 1q, 3q, 5q, 6q, 9q, 17q and 19q showed at least nominal linkage in two or more scans and in the weighted meta-analysis. Regions previously associated with AS on chromosome 2q (the IL-1 gene cluster) and 22q (CYP2D6) exhibited nominal linkage in the meta-analysis, providing further statistical support for their involvement in susceptibility to AS. Conclusion: These findings provide a useful guide for future studies aiming to identify the genes involved in this highly heritable condition. . Published by on behalf of the British Society for Rheumatology.

How accurate are the marker orders in crop linkage maps generated from large marker datasets?

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

A genome wide linkage scan for dizygotic twinning in 525 families of mothers of dizygotic twins

BACKGROUND: The tendency to conceive dizygotic (DZ) twins is a complex trait influenced by genetic and environmental factors. To search for new candidate loci for twinning, we conducted a genome-wide linkage scan in 525 families using microsatellite and single nucleotide polymorphism marker panels. METHODS AND RESULTS: Non-parametric linkage analyses, including 523 families containing a total of 1115 mothers of DZ twins (MODZT) from Australia and New Zealand (ANZ) and The Netherlands (NL), produced four linkage peaks above the threshold for suggestive linkage, including a highly suggestive peak at the extreme telomeric end of chromosome 6 with an exponential logarithm of odds \[(exp)LOD] score of 2.813 (P = 0.0002). Since the DZ twinning rate increases steeply with maternal age independent of genetic effects, we also investigated linkage including only families where at least one MODZT gave birth to her first set of twins before the age of 30. These analyses produced a maximum expLOD score of 2.718 (P = 0.0002), largely due to linkage signal from the ANZ cohort, however, ordered subset analyses indicated this result is most likely a chance finding in the combined dataset. Linkage analyses were also performed for two large DZ twinning families from the USA, one of which produced a peak on chromosome 2 in the region of two potential candidate genes. Sequencing of FSHR and FIGLA, along with INHBB in MODZTs from two large NL families with family specific linkage peaks directly over this gene, revealed a potentially functional variant in the 5' untranslated region of FSHR that segregated with the DZ twinning phenotype in the Utah family. CONCLUSION: Our data provide further evidence for complex inheritance of familial DZ twinning.

Genetic influences on handedness: data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

A genome-wide linkage scan provides evidence for both new and previously reported loci influencing common migraine

Latent class analysis was performed on migraine symptom data collected in a Dutch population sample (N = 12,210, 59% female) in order to obtain empirical groupings of individuals suffering from symptoms of migraine headache. Based on these heritable groupings (h(2) = 0.49, 95% CI: 0.41-0.57) individuals were classified as affected (migrainous headache) or unaffected. Genome-wide linkage analysis was performed using genotype data from 105 families with at least 2 affected siblings. In addition to this primary phenotype, linkage analyses were performed for the individual migraine symptoms. Significance levels, corrected for the analysis of multiple traits, were determined empirically via a novel simulation approach. Suggestive linkage for migrainous headache was found on chromosomes 1 (LOD = 1.63; pointwise P = 0.0031), 13 (LOD = 1.63; P = 0.0031), and 20 (LOD = 1.85; P = 0.0018). Interestingly, the chromosome 1 peak was located close to the ATP1A2 gene, associated with familial hemiplegic migraine type 2 (FHM2). Individual symptom analysis produced a LOD score of 1.97 (P = 0.0013) on chromosome 5 (photo/phonophobia), a LOD score of 2.13 (P = 0.0009) on chromosome 10 (moderate/severe pain intensity) and a near significant LOD score of 3.31 (P = 0.00005) on chromosome 13 (pulsating headache). These peaks were all located near regions previously reported in migraine linkage studies. Our results provide important replication and support for the presence of migraine susceptibility genes within these regions, and further support the utility of an LCA-based phenotyping approach and analysis of individual symptoms in migraine genetic research. Additionally, our novel "2-step" analysis and simulation approach provides a powerful means to investigate linkage to individual trait components.

A reanalysis of 409 European-Ancestry and African American schizophrenia pedigrees reveals significant linkage to 8p23.3 with evidence of locus heterogeneity

The detection and replication of schizophrenia risk loci can require substantial sample sizes, which has prompted various collaborative efforts for combining multiple samples. However, pooled samples may comprise sub-samples with substantial population genetic differences, including allele frequency differences. We investigated the impact of population differences via linkage reanalysis of Molecular Genetics of Schizophrenia 1 (MGS1) affected sibling-pair data, comprising two samples of distinct ancestral origin: European (EA: 263 pedigrees) and African-American (AA: 146 pedigrees). To exploit the linkage information contained within these distinct continental samples, we performed separate analyses of the individual samples, allowing for within-sample locus heterogeneity, and the pooled sample, allowing for both within-sample and between-sample heterogeneity. Significance levels, corrected for the multiple tests, were determined empirically. For all suggestive peaks, stronger linkage evidence was obtained in either the EA or AA sample than the combined sample, regardless of how heterogeneity was modeled for the latter. Notably, we report genomewide significant linkage of schizophrenia to 8p23.3 and evidence for a second, independent susceptibility locus, reaching suggestive linkage, 29 cM away on 8p21.3. We also detected suggestive linkage on chromosomes 5p13.3 and 7q36.2. Many regions showed pronounced differences in the extent of linkage between the EA and AA samples. This reanalysis highlights the potential impact of population differences upon linkage evidence in pooled data and demonstrates a useful approach for the analysis of samples drawn from distinct continental groups.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Exclusion of angiotensinogen gene in molecular basis of human hypertension: Sibpair linkage and association analyses in Australian anglo-caucasians

Linkage with essential hypertension has been claimed for a microsatellite marker near the angiotensinogen gene (AGT; chromosome 1q42), as has association for the AGT variants M235T, G(-6)A and A(-20)C. To more rigorously evaluate AGT as a candidate gene for hypertension we performed sibpair analysis with multiple microsatellite markers surrounding this locus and using more sophisticated analysis programs. We also performed an association study of the AGT variants in unrelated subjects with a strong family history (two affected parents). For the linkage study, single and multiplex polymerase chain reaction (PCRs) and automated genescan analysis were conducted on DNA from 175 Australian Anglo-Celtic Caucasian hypertensives for the following markers: D1S2880-(2.1 cM)-D1S213-(2.8 cM)-D1S251-(6.5 cM)-AGT-(2.0 cM) -D1S235. Statistical evaluation of genotype data by nonparametric methods resulted in the following scores: Single-point analysis - SPLINK, P > 0.18; APM method, P > 0.25; ASPEX, MLOD < 0.28; SIB-PAIR, P > 0. 24; Multipoint analysis - MAPMAKER/SIBS, MLOD < 0.24; GENEHUNTER, P > 0.35. Exclusion scores of Lod -4.1 to -5.1 were obtained for these markers using MAPMAKER/SIBS for a lambda(s) of 1.6. The association study of G(-6)A, A(-20)C and M235T variants in 111 hypertensives with strong family history and 190 normotensives with no family history showed significant linkage disequilibrium between particular haplotypes, but we could find no association with hypertension. The present study therefore excludes AGT in the etiology of hypertension, at least in the population of Australian Anglo-Celtic Caucasians studied.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

Confirmation of linkage and refinement of the RP28 locus for autosomal recessive retinitis pigmentosa on chromosome 2p14-p15 in an Indian family

PURPOSE: To report the linkage analysis of retinitis pigmentosa (RP) in an Indian family. METHODS: Individuals were examined for symptoms of retinitis pigmentosa and their blood samples were withdrawn for genetic analysis. The disorder was tested for linkage to known 14 adRP and 22 arRP loci using microsatellite markers. RESULTS: Seventeen individuals including seven affecteds participated in the study. All affected individuals had typical RP. The age of onset of the disease ranged from 8-18 years. The disorder in this family segregated either as an autosomal recessive trait with pseudodominance or an autosomal dominant trait. Linkage to an autosomal recessive locus RP28 on chromosome 2p14-p15 was positive with a maximum two-point lod score of 3.96 at theta=0 for D2S380. All affected individuals were homozygous for alleles at D2S2320, D2S2397, D2S380, and D2S136. Recombination events placed the minimum critical region (MCR) for the RP28 gene in a 1.06 cM region between D2S2225 and D2S296. CONCLUSIONS : The present data confirmed linkage of arRP to the RP28 locus in a second Indian family. The RP28 locus was previously mapped to a 16 cM region between D2S1337 and D2S286 in a single Indian family. Haplotype analysis in this family has further narrowed the MCR for the RP28 locus to a 1.06 cM region between D2S2225 and D2S296. Of 15 genes reported in the MCR, 14 genes (KIAA0903, OTX1, MDH1, UGP2, VPS54, PELI1, HSPC159, FLJ20080, TRIP-Br2, SLC1A4, KIAA0582, RAB1A, ACTR2, and SPRED2) are either expressed in the eye or retina. Further study needs to be done to test which of these genes is mutated in patients with RP linked to the RP28 locus.

Evolutionary characters, phenotypes and ontologies: curating data from the systematic biology literature.

BACKGROUND: The wealth of phenotypic descriptions documented in the published articles, monographs, and dissertations of phylogenetic systematics is traditionally reported in a free-text format, and it is therefore largely inaccessible for linkage to biological databases for genetics, development, and phenotypes, and difficult to manage for large-scale integrative work. The Phenoscape project aims to represent these complex and detailed descriptions with rich and formal semantics that are amenable to computation and integration with phenotype data from other fields of biology. This entails reconceptualizing the traditional free-text characters into the computable Entity-Quality (EQ) formalism using ontologies. METHODOLOGY/PRINCIPAL FINDINGS: We used ontologies and the EQ formalism to curate a collection of 47 phylogenetic studies on ostariophysan fishes (including catfishes, characins, minnows, knifefishes) and their relatives with the goal of integrating these complex phenotype descriptions with information from an existing model organism database (zebrafish, http://zfin.org). We developed a curation workflow for the collection of character, taxonomic and specimen data from these publications. A total of 4,617 phenotypic characters (10,512 states) for 3,449 taxa, primarily species, were curated into EQ formalism (for a total of 12,861 EQ statements) using anatomical and taxonomic terms from teleost-specific ontologies (Teleost Anatomy Ontology and Teleost Taxonomy Ontology) in combination with terms from a quality ontology (Phenotype and Trait Ontology). Standards and guidelines for consistently and accurately representing phenotypes were developed in response to the challenges that were evident from two annotation experiments and from feedback from curators. CONCLUSIONS/SIGNIFICANCE: The challenges we encountered and many of the curation standards and methods for improving consistency that we developed are generally applicable to any effort to represent phenotypes using ontologies. This is because an ontological representation of the detailed variations in phenotype, whether between mutant or wildtype, among individual humans, or across the diversity of species, requires a process by which a precise combination of terms from domain ontologies are selected and organized according to logical relations. The efficiencies that we have developed in this process will be useful for any attempt to annotate complex phenotypic descriptions using ontologies. We also discuss some ramifications of EQ representation for the domain of systematics.

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

We propose a novel unsupervised approach for linking records across arbitrarily many files, while simultaneously detecting duplicate records within files. Our key innovation is to represent the pattern of links between records as a {\em bipartite} graph, in which records are directly linked to latent true individuals, and only indirectly linked to other records. This flexible new representation of the linkage structure naturally allows us to estimate the attributes of the unique observable people in the population, calculate $k$-way posterior probabilities of matches across records, and propagate the uncertainty of record linkage into later analyses. Our linkage structure lends itself to an efficient, linear-time, hybrid Markov chain Monte Carlo algorithm, which overcomes many obstacles encountered by previously proposed methods of record linkage, despite the high dimensional parameter space. We assess our results on real and simulated data.

A genome-wide linkage scan for genes controlling variation in urinary albumin excretion in type ll diabetes

The main hallmark of diabetic nephropathy is elevation in urinary albumin excretion. We performed a genome-wide linkage scan in 63 extended families with multiple members with type II diabetes. Urinary albumin excretion, measured as the albumin-to-creatinine ratio (ACR), was determined in 426 diabetic and 431 nondiabetic relatives who were genotyped for 383 markers. The data were analyzed using variance components linkage analysis. Heritability (h2) of ACR was significant in diabetic (h2=0.23, P=0.0007), and nondiabetic (h2=0.39, P=0.0001) relatives. There was no significant difference in genetic variance of ACR between diabetic and nondiabetic relatives (P=0.16), and the genetic correlation (rG=0.64) for ACR between these two groups was not different from 1 (P=0.12). These results suggested that similar genes contribute to variation in ACR in diabetic and nondiabetic relatives. This hypothesis was supported further by the linkage results.

Significant correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy

Prior family and adoption studies have suggested a genetic relationship between schizophrenia and schizotypy. However, this has never been verified using linkage methods. We therefore attempted to test for a correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. The Irish study of high-density schizophrenia families comprises 270 families with at least two members with schizophrenia or poor-outcome schizoaffective disorder (n = 637). Non-psychotic relatives were assessed using the structured interview for schizotypy (n = 746). A 10-cM multipoint, non-parametric, autosomal genomewide scan of schizophrenia was performed in Merlin. A scan of a quantitative trait comprising ratings of DSM-III-R criteria for schizotypal personality disorder in non-psychotic relatives was also performed. Schizotypy logarithm of the odds (LOD) scores were regressed onto schizophrenia LOD scores at all loci, with adjustment for spatial autocorrelation. To assess empirical significance, this was also carried out using 1000 null scans of schizotypy. The number of jointly linked loci in the real data was compared to distribution of jointly linked loci in the null scans. No markers were suggestively linked to schizotypy based on strict Lander Kruglyak criteria. Schizotypy LODs predicted schizophrenia LODs above chance expectation genome wide (empirical P = 0.04). Two and four loci yielded nonparametric LOD (NPLs) > 1.0 and > 0.75, respectively, for both schizophrenia and schizotypy (genome-wide empirical P = 0.04 and 0.02, respectively). These results suggest that at least a subset of schizophrenia susceptibility genes also affects schizotypy in non-psychotic relatives. Power may therefore be increased in molecular genetic studies of schizophrenia if they incorporate measures of schizotypy in non-psychotic relatives.

Two non-synonymous markers in PTPN21, identified by genome-wide association study data-mining and replication, are associated with schizophrenia

We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.