Joint oligogenic segregation and linkage analysis using bayesian Markov chain Monte Carlo methods

Clinical variability and onset age modifiers in an extended Belgian GRN founder family

We previously reported a granulin (GRN) null mutation, originating from a common founder, in multiple Belgian families with frontotemporal dementia. Here, we used data of a 10-year follow-up study to describe in detail the clinical heterogeneity observed in this extended founder pedigree. We identified 85 patients and 40 unaffected mutation carriers, belonging to 29 branches of the founder pedigree. Most patients (74.4%) were diagnosed with frontotemporal dementia, while others had a clinical diagnosis of unspecified dementia, Alzheimer's dementia or Parkinson's disease. The observed clinical heterogeneity can guide clinical diagnosis, genetic testing, and counseling of mutation carriers. Onset of initial symptomatology is highly variable, ranging from age 45 to 80 years. Analysis of known modifiers, suggested effects of GRN rs5848, microtubule-associated protein tau H1/H2, and chromosome 9 open reading frame 72 G₄C₂ repeat length on onset age but explained only a minor fraction of the variability. Contrary, the extended GRN founder family is a valuable source for identifying other onset age modifiers based on exome or genome sequences. These modifiers might be interesting targets for developing disease-modifying therapies.

Single nucleotide polymorphisms in an intergenic chromosome 2q region associated with tissue factor pathway inhibitor plasma levels and venous thromboembolism

Essentials Tissue factor pathway inhibitor (TFPI) regulates the blood coagulation cascade. We replicated previously reported linkage of TFPI plasma levels to the chromosome 2q region. The putative causal locus, rs62187992, was associated with TFPI plasma levels and thrombosis. rs62187992 was marginally associated with TFPI expression in human aortic endothelial cells. Click to hear Ann Gil's presentation on new insights into thrombin activatable fibrinolysis inhibitor SUMMARY: Background Tissue factor pathway inhibitor (TFPI) regulates fibrin clot formation, and low TFPI plasma levels increase the risk of arterial thromboembolism and venous thromboembolism (VTE). TFPI plasma levels are also heritable, and a previous linkage scan implicated the chromosome 2q region, but no specific genes. Objectives To replicate the finding of the linkage region in an independent sample, and to identify the causal locus. Methods We first performed a linkage analysis of microsatellite markers and TFPI plasma levels in 251 individuals from the F5L Family Study, and replicated the finding of the linkage peak on chromosome 2q (LOD = 3.06). We next defined a follow-up region that included 112 603 single nucleotide polymorphisms (SNPs) under the linkage peak, and meta-analyzed associations between these SNPs and TFPI plasma levels across the F5L Family Study and the Marseille Thrombosis Association (MARTHA) Study, a study of 1033 unrelated VTE patients. SNPs with false discovery rate q-values of < 0.10 were tested for association with TFPI plasma levels in 892 patients with coronary artery disease in the AtheroGene Study. Results and Conclusions One SNP, rs62187992, was associated with TFPI plasma levels in all three samples (β = + 0.14 and P = 4.23 × 10-6 combined; β = + 0.16 and P = 0.02 in the F5L Family Study; β = + 0.13 and P = 6.3 × 10-4 in the MARTHA Study; β = + 0.17 and P = 0.03 in the AtheroGene Study), and contributed to the linkage peak in the F5L Family Study. rs62187992 was also associated with clinical VTE (odds ratio 0.90, P = 0.03) in the INVENT Consortium of > 7000 cases and their controls, and was marginally associated with TFPI expression (β = + 0.19, P = 0.08) in human aortic endothelial cells, a primary site of TFPI synthesis. The biological mechanisms underlying these associations remain to be elucidated.

Genome scan for cognitive trait loci of dyslexia: Rapid naming and rapid switching of letters, numbers, and colors

Dyslexia, or specific reading disability, is a common developmental disorder that affects 5-12% of school-aged children. Dyslexia and its component phenotypes, assessed categorically or quantitatively, have complex genetic bases. The ability to rapidly name letters, numbers, and colors from rows presented visually correlates strongly with reading in multiple languages and is a valid predictor of reading and spelling impairment. Performance on measures of rapid naming and switching, RAN and RAS, is stable throughout elementary school years, with slowed performance persisting in adults who still manifest dyslexia. Targeted analyses of dyslexia candidate regions have included RAN measures, but only one other genome-wide linkage study has been reported. As part of a broad effort to identify genetic contributors to dyslexia, we performed combined oligogenic segregation and linkage analyses of measures of RAN and RAS in a family-based cohort ascertained through probands with dyslexia. We obtained strong evidence for linkage of RAN letters to the DYX3 locus on chromosome 2p and RAN colors to chromosome 10q, but were unable to confirm the chromosome 6p21 linkage detected for a composite measure of RAN colors and objects in the previous genome-wide study.

Lexical decision as an endophenotype for reading comprehension: an exploration of an association

Based on numerous suggestions in the literature, we evaluated lexical decision (LD) as a putative endophenotype for reading comprehension by investigating heritability estimates and segregation analyses parameter estimates for both of these phenotypes. Specifically, in a segregation analysis of a large sample of families, we established that there is little to no overlap between genes contributing to LD and reading comprehension and that the genetic mechanism behind LD derived from this analysis appears to be more complex than that for reading comprehension. We conclude that in our sample, LD is not a good candidate as an endophenotype for reading comprehension, despite previous suggestions from the literature. Based on this conclusion, we discuss the role and benefit of the endophenotype approach in studies of complex human cognitive functions.

Genome scan in familial late-onset Alzheimer's disease: a locus on chromosome 6 contributes to age-at-onset

Alzheimer's disease (AD) is a common, genetically complex, fatal neurodegenerative disorder of late life. Although several genes are known to play a role in early-onset AD, identification of the genetic basis of late onset AD (LOAD) has been challenging, with only the APOE gene known to have a high contribution to both AD risk and age-at-onset. Here, we present the first genome-scan analysis of the complete, well-characterized University of Washington LOAD sample of 119 pedigrees, using age-at-onset as the trait of interest. The analysis approach used allows for a multilocus trait model while at the same time accommodating age censoring, effects of APOE as a known genetic covariate, and full pedigree and marker information. The results provide strong evidence for linkage of loci contributing to age-at-onset to genomic regions on chromosome 6q16.3, and to 19q13.42 in the region of the APOE locus. There was evidence for interaction between APOE and the locus on chromosome 6q and suggestive evidence for linkage to chromosomes 11p13, 15q12-14, and 19p13.12. These results provide the first independent confirmation of an AD age-at-onset locus on chromosome 6 and suggest that further efforts towards identifying the underlying causal locus or loci are warranted.

Genome scan of age-at-onset in the NIMH Alzheimer disease sample uncovers multiple loci, along with evidence of both genetic and sample heterogeneity

Alzheimer's disease (AD) is a common neurodegenerative disorder of late life with a complex genetic basis. Although several genes are known to play a role in rare early onset AD, only the APOE gene is known to have a high contribution to risk of the common late-onset form of the disease (LOAD, onset >60 years). APOE genotypes vary in their AD risk as well as age-at-onset distributions, and it is likely that other loci will similarly affect AD age-at-onset. Here we present the first analysis of age-at-onset in the NIMH LOAD sample that allows for both a multilocus trait model and genetic heterogeneity among the contributing sites, while at the same time accommodating age censoring, effects of known genetic covariates, and full pedigree and marker information. The results provide evidence for genomic regions not previously implicated in this data set, including regions on chromosomes 7q, 15, and 19p. They also affirm evidence for loci on chromosomes 1q, 6p, 9q, 11, and, of course, the APOE locus on 19q, all of which have been reported previously in the same sample. The analyses failed to find evidence for linkage to chromosome 10 with inclusion of unaffected subjects and extended pedigrees. Several regions implicated in these analyses in the NIMH sample have been previously reported in genome scans of other AD samples. These results, therefore, provide independent confirmation of AD loci in family-based samples on chromosomes 1q, 7q, 19p, and suggest that further efforts towards identifying the underlying causal loci are warranted.

TMEM106B is associated with frontotemporal lobar degeneration in a clinically diagnosed patient cohort

In a genome-wide association study of frontotemporal lobar degeneration with pathological inclusions of TAR DNA-binding protein, significant association was obtained with three single nucleotide polymorphisms at 7p21.3, in a region encompassing the gene TMEM106B. This study also suggested a potential modifying effect of TMEM106B on disease since the association was strongest in progranulin mutation carriers. Further, the risk effect seemed to correlate with increased TMEM106B expression in patients. In the present study, we sought to replicate these three findings using an independent Flanders–Belgian cohort of primarily clinically diagnosed patients with frontotemporal lobar degeneration (n = 288). We were able to confirm the association with TMEM106B with a P-value of 0.008 for rs1990622, the top marker from the genome-wide association study [odds ratio 0.75 (95% confidence interval 0.61–0.93)]. Further, high-density single nucleotide polymorphism mapping suggested that the association was solely driven by the gene TMEM106B. Homozygous carriers of the TMEM106B protective alleles had a 50% reduced risk of developing frontotemporal lobar degeneration. However, we were unable to detect a modifying effect of the TMEM106B single nucleotide polymorphisms on onset age in progranulin mutation carriers belonging to an extended, clinical and pathological well-documented founder family segregating a progranulin null mutation. Also, we could not observe significant differences in messenger RNA expression between patients and control individuals in lymphoblast cell lines and in brain frontal cortex. In conclusion, we replicated the genetic TMEM106B association in a primarily clinically diagnosed cohort of patients with frontotemporal lobar degeneration from Flanders–Belgium. Additional studies are needed to unravel the molecular role of TMEM106B in disease onset and pathogenesis.

Genome-scan for IQ discrepancy in autism: evidence for loci on chromosomes 10 and 16

Performance IQ (PIQ) greater than verbal IQ (VIQ) is often observed in studies of the cognitive abilities of autistic individuals. This characteristic is correlated with social and communication impairments, key parts of the autism diagnosis. We present the first genetic analyses of IQ discrepancy (PIQ-VIQ) as an autism-related phenotype. We performed genome-wide joint linkage and segregation analyses on 287 multiplex families, using a Markov chain Monte Carlo approach. Genetic data included a genome-scan of 387 micro-satellite markers in 210 families augmented with additional markers added in a subset of families. Empirical P values were calculated for five interesting regions. Linkage analysis identified five chromosomal regions with substantial regional evidence of linkage; 10p12 [P = 0.001; genome-wide (gw) P = 0.05], 16q23 (P = .015; gw P = 0.53), 2p21 (P = 0.03, gw P = 0.78), 6q25 (P = 0.047, gw P = 0.91) and 15q23-25 (P = 0.053, gw P = 0.93). The location of the chromosome 10 linkage signal coincides with a region noted in a much earlier genome-scan for autism, and the chromosome 16 signal coincides exactly with a linkage signal for non-word repetition in specific language impairment. This study provides strong evidence for a QTL influencing IQ discrepancy in families with autistic individuals on chromosome 10, and suggestive evidence for a QTL on chromosome 16. The location of the chromosome 16 signal suggests a candidate gene, CDH13, a T-cadherin expressed in the brain, which has been implicated in previous SNP studies of autism and ADHD.

Genome scan for spelling deficits: effects of verbal IQ on models of transmission and trait gene localization

Dyslexia is a complex learning disability with evidence for a genetic basis. Strategies that may be useful for dissecting its genetic basis include the study of component phenotypes, which may simplify the underlying genetic complexity, and use of an analytic approach that accounts for the multilocus nature of the trait to guide the investigation and increase power to detect individual loci. Here we present results of a genetic analysis of spelling disability as a component phenotype. Spelling disability is informative in analysis of extended pedigrees because it persists into adulthood. We show that a small number of hypothesized loci are sufficient to explain the inheritance of the trait in our sample, and that each of these loci maps to one of four genomic regions. Individual trait models and locations are a function of whether a verbal IQ adjustment is included, suggesting mediation through both IQ-related and unrelated pathways.

Modifier locus of the skeletal muscle involvement in Emery-Dreifuss muscular dystrophy

Autosomal dominant Emery-Dreifuss muscular dystrophy is caused by mutations in LMNA gene encoding lamins A and C. The disease is characterized by early onset joint contractures during childhood associated with humero-peroneal muscular wasting and weakness, and by the development of a cardiac disease in adulthood. Important intra-familial variability characterized by a wide range of age at onset of myopathic symptoms (AOMS) has been recurrently reported, suggesting the contribution of a modifier gene. Our objective was to identify a modifier locus of AOMS in relation with the LMNA mutation. To map the modifier locus, we genotyped 291 microsatellite markers in 59 individuals of a large French family, where 19 patients carrying the same LMNA mutation, exhibited wide range of AOMS. We performed Bayesian Markov Chain Monte Carlo-based joint segregation and linkage methods implemented in the Loki software, and detected a strong linkage signal on chromosome 2 between markers D2S143 and D2S2244 (211 cM) with a Bayes factor of 28.7 (empirical p value = 0.0032). The linked region harbours two main candidate genes, DES and MYL1 encoding desmin and light chain of myosin. Importantly, the impact of the genotype on the phenotype for this locus showed an overdominant effect with AOMS 2 years earlier for the homozygotes of the rare allele and 37 years earlier for the heterozygotes than the homozygotes for the common allele. These results provide important highlights for the natural history and for the physiopathology of Emery-Dreifuss muscular dystrophy.

Evidence for three loci modifying age-at-onset of Alzheimer's disease in early-onset PSEN2 families

Families with early-onset Alzheimer's disease (AD) sharing a single PSEN2 mutation exhibit a wide range of age-at-onset, suggesting that modifier loci segregate within these families. While APOE is known to be an age-at-onset modifier, it does not explain all of this variation. We performed a genome scan within nine such families for loci influencing age-at-onset, while simultaneously controlling for variation in the primary PSEN2 mutation (N141I) and APOE. We found significant evidence of linkage between age-at-onset and chromosome 1q23.3 (P < 0.001) when analysis included all families, and to chromosomes 1q23.3 (P < 0.001), 17p13.2 (P = 0.0002), 7q33 (P = 0.017), and 11p14.2 (P = 0.017) in a single large pedigree. Simultaneous analysis of these four chromosomes maintained strong evidence of linkage to chromosomes 1q23.3 and 17p13.2 when all families were analyzed, and to chromosomes 1q23.3, 7q33, and 17p13.2 within the same single pedigree. Inclusion of major gene covariates proved essential to detect these linkage signals, as all linkage signals dissipated when PSEN2 and APOE were excluded from the model. The four chromosomal regions with evidence of linkage all coincide with previous linkage signals, associated SNPs, and/or candidate genes identified in independent AD study populations. This study establishes several candidate regions for further analysis and is consistent with an oligogenic model of AD risk and age-at-onset. More generally, this study also demonstrates the value of searching for modifier loci in existing datasets previously used to identify primary causal variants for complex disease traits.

Linkage and association analyses identify a candidate region for apoB level on chromosome 4q32.3 in FCHL families

Familial combined hyperlipidemia (FCHL) is a complex trait leading to cardiovascular disease (CVD) risk. Elevated levels and size of apolipoprotein B (apoB) and low-density lipoprotein (LDL) are associated with FCHL, which is genetically heterogeneous and is likely caused by rare variants. We carried out a linkage-based genome scan of four large FCHL pedigrees for apoB level that is independent of LDL: apoB level that is adjusted for LDL level and size. Follow-up included SNP genotyping in the region with the strongest evidence of linkage. Several regions with the evidence of linkage in individual pedigrees support the rare variant model. Evidence of linkage was strongest on chromosome 4q, with multipoint analysis in one pedigree giving LOD = 3.1 with a parametric model, and a log Bayes Factor = 1.5 from a Bayesian oligogenic approach. Of the 293 SNPs spanning the implicated region on 4q, rs6829588 completely explained the evidence of linkage. This SNP accounted for 39% of the apoB phenotypic variance, with heterozygotes for this SNP having a trait value that was approximately 30% higher than that of the high-frequency homozygote, thus identifying and considerably refining a strong candidate region. These results illustrate the advantage of using large pedigrees in the search for rare variants: reduced genetic heterogeneity within single pedigrees coupled with the large number of individuals segregating otherwise-rare single variants leads to high power to implicate such variants.

Same or different? Insights into the etiology of phonological awareness and rapid naming

This work's objective was to offer additional insights into the psychological and genetic bases of reading ability and disability, and to evaluate the plausibility of a variety of psychological models of reading involving phonological awareness (PA) and rapid naming (RN), both hypothesized to be principal components in such models. In Study 1, 488 unselected families were assessed with measures of PA and RN to investigate familial aggregation and to obtain estimates of both the number and effect-magnitude of genetic loci involved in these traits' transmission. The results of the analyses from Study 1 indicated the presence of genetic effects in the etiology of individual differences for PA and RN and pointed to both the shared and unique sources of this genetic variance, which appeared to be exerted by multiple (3-6 for PA and 3-5 for RN) genes. These results were used in Study 2 to parameterize a simulation of 3000 families with quantitatively distributed PA and RN, so that the robustness and generalizability of the Study 1 findings could be evaluated. The findings of both studies were interpreted according to established theories of reading and our own understanding of the etiology of complex developmental disorders.

Genome scan of a nonword repetition phenotype in families with dyslexia: evidence for multiple loci

To understand the genetic architecture of dyslexia and identify the locations of genes involved, we performed linkage analyses in multigenerational families using a phonological memory phenotype--Nonword Repetition (NWR). A genome scan was first performed on 438 people from 51 families (DS-1) and linkage was assessed using variance components (VC), Bayesian oligogenic (BO), and parametric analyses. For replication, the genome scan and analyses were repeated on 693 people from 93 families (DS-2). For the combined set (DS-C), analyses were performed with all three methods in the regions that were identified in both samples. In DS-1, regions on chromosomes 4p, 6q, 12p, 17q, and 22q exceeded our initial threshold for linkage, with 17q providing a parametric LOD score of 3.2. Analysis with DS-2 confirmed the locations on chromosomes 4p and 12p. The strongest VC and BO signals in both samples were on chromosome 4p in DS-C, with a parametric multipoint LOD(max) of 2.36 for the 4p locus. Our linkage analyses of NWR in dyslexia provide suggestive and reproducible evidence for linkage to 4p12 and 12p in both samples, and significant evidence for linkage to 17q in one of the samples. These results warrant further studies of phonological memory and chromosomal regions identified here in other datasets.

Empirical significance values for linkage analysis: trait simulation using posterior model distributions from MCMC oligogenic segregation analysis

Variance-components (VC) linkage analysis is a powerful model-free method for assessing linkage, but the distribution of VC logarithm of the odds ratio (LOD) scores may deviate substantially from the assumed asymptotic distribution. Typically, the null distribution of the VC-LOD score and other linkage statistics has been estimated by generating new genotype data independently of the trait data, and computing a linkage statistic for many such marker-simulated data sets. However, marker simulation is susceptible to errors in the assumed marker and map model and is computationally intensive. Here, we describe a method for generating posterior distributions of linkage statistics through simulation of trait data based on the original sample and on results from an initial scan using a Bayesian Markov-chain Monte Carlo (MCMC) approach for oligogenic segregation analysis. We use samples of oligogenic trait models taken from the posterior distribution to generate new samples of trait data, which were paired with the original marker data for analysis. Empirical P-values obtained from trait and marker simulation were similar when derived for several strong linkage signals from published linkage scans, and for analysis of data with a known, simulated, trait model. Furthermore, trait simulation produces the expected null distribution of VC-LOD scores and is computationally fast when marker identity-by-descent estimates from the original data could be reused. These results suggest that trait simulation gives valid estimates of statistical significance of linkage signals. Finally, these results also demonstrate the feasibility of obtaining empirical significance levels for evaluating Bayesian oligogenic linkage signals with either marker or trait simulation.

A Bayesian method for simultaneously detecting Mendelian and imprinted quantitative trait loci in experimental crosses of outbred species

Genomic imprinting is interpreted as a phenomenon, in which some genes inherited from one parent are not completely expressed due to modification of the genome caused during gametogenesis. Subsequently, the expression level of an allele at the imprinted gene is changed dependent on the parental origin, which is referred to as the parent-of-origin effect. In livestock, some QTL for reproductive performance and meat productivity have been reported to be imprinted. So far, methods detecting imprinted QTL have been proposed on the basis of interval mapping, where only a single QTL was tested at a time. In this study, we developed a Bayesian method for simultaneously mapping multiple QTL, allowing the inference about expression modes of QTL in an outbred F2 family. The inference about whether a QTL is Mendelian or imprinted was made using Markov chain Monte Carlo estimation by comparing the goodness-of-fits between models, assuming the presence and the absence of parent-of-origin effect at a QTL. We showed by the analyses of simulated data sets that the Bayesian method can effectively detect both Mendelian QTL and imprinted QTL.

Segregation analysis of a complex quantitative trait: approaches for identifying influential data points

BACKGROUND/AIMS

Complex traits pose a particular challenge to standard methods for segregation analysis (SA), and for such traits it is difficult to assess the ability of complex SA (CSA) to approximate the true mode of inheritance. Here we use an oligogenic Bayesian Markov chain Monte Carlo method for SA (OSA) to verify results from a single-locus likelihood-based CSA for data on a quantitative measure of reading ability.

METHODS

We compared the profile likelihood from CSA, maximized over the trait allele frequency, to the posterior distribution of genotype effects from OSA to explore differences in the overall parameter estimates from SA on the original phenotype data and the same data Winsorized to reduce the potential influence of three outlying data points.

RESULTS

Bayesian OSA revealed two modes of inheritance, one of which coincided with the QTL model from CSA. Winsorizing abolished the model originally estimated by CSA; both CSA and OSA identified only the second OSA model.

CONCLUSION

Differences between the results from the two methods alerted us to the presence of influential data points, and identified the QTL model best supported by the data. Thus, the Bayesian OSA proved a valuable tool for assessing and verifying inheritance models from CSA.

Current perspectives on the genetic analysis of autism

Although no definitive genetic mutations leading to autism susceptibility have been established, the field has many new resources to tackle this difficult problem. Numbers of families at many research sites are now large, and new collaborations among these groups will allow for collections of subjects with enough statistical power to detect relatively small gene effects. New technological advances in genotyping will allow for more fine-grained genetic analysis, and more sophisticated techniques have been developed to address the vast amounts of data acquired. Researchers have also begun to focus on intermediate phenotypes associated with autism, such as elevated serotonin, increased head circumference, social difficulties, or language impairment or delay. These phenotypes may help to stratify affected cases into more genetically homogeneous subgroups, and may also occur in their clinically unaffected relatives. The study of intermediate phenotypes may allow investigators to find common gene variants that lead to autism susceptibility. Here we discuss the major intermediate phenotypes, and give an overview of current genetic analysis techniques.

Genomewide scan for real-word reading subphenotypes of dyslexia: novel chromosome 13 locus and genetic complexity

Dyslexia is a common learning disability exhibited as a delay in acquiring reading skills despite adequate intelligence and instruction. Reading single real words (real-word reading, RWR) is especially impaired in many dyslexics. We performed a genome scan, using variance components (VC) linkage analysis and Bayesian Markov chain Monte Carlo (MCMC) joint segregation and linkage analysis, for three quantitative measures of RWR in 108 multigenerational families, with follow up of the strongest signals with parametric LOD score analyses. We used single-word reading efficiency (SWE) to assess speed and accuracy of RWR, and word identification (WID) to assess accuracy alone. Adjusting SWE for WID provided a third measure of RWR efficiency. All three methods of analysis identified a strong linkage signal for SWE on chromosome 13q. Based on multipoint analysis with 13 markers we obtained a MCMC intensity ratio (IR) of 53.2 (chromosome-wide P < 0.004), a VC LOD score of 2.29, and a parametric LOD score of 2.94, based on a quantitative-trait model from MCMC segregation analysis (SA). A weaker signal for SWE on chromosome 2q occurred in the same location as a significant linkage peak seen previously in a scan for phonological decoding. MCMC oligogenic SA identified three models of transmission for WID, which could be assigned to two distinct linkage peaks on chromosomes 12 and 15. Taken together, these results indicate a locus for efficiency and accuracy of RWR on chromosome 13, and a complex model for inheritance of RWR accuracy with loci on chromosomes 12 and 15.

A genome scan in multigenerational families with dyslexia: Identification of a novel locus on chromosome 2q that contributes to phonological decoding efficiency

Dyslexia is a common and complex developmental disorder manifested by unexpected difficulty in learning to read. Multiple different measures are used for diagnosis, and may reflect different biological pathways related to the disorder. Impaired phonological decoding (translation of written words without meaning cues into spoken words) is thought to be a core deficit. We present a genome scan of two continuous measures of phonological decoding ability: phonemic decoding efficiency (PDE) and word attack (WA). PDE measures both accuracy and speed of phonological decoding, whereas WA measures accuracy alone. Multipoint variance component linkage analyses (VC) and Markov chain Monte-Carlo (MCMC) multipoint joint linkage and segregation analyses were performed on 108 families. A strong signal was observed on chromosome 2 for PDE using both VC (LOD=2.65) and MCMC methods (intensity ratio (IR)=32.1). The IR is an estimate of the ratio of the posterior to prior probability of linkage in MCMC analysis. The chromosome 2 signal was not seen for WA. More detailed mapping with additional markers provided statistically significant evidence for linkage of PDE to chromosome 2, with VC-LOD=3.0 and IR=59.6 at D2S1399. Parametric analyses of PDE, using a model obtained by complex segregation analysis, provided a multipoint maximum LOD=2.89. The consistency of results from three analytic approaches provides strong evidence for a locus on chromosome 2 that influences speed but not accuracy of phonological decoding.

Genome scan for quantitative trait loci influencing HDL levels: evidence for multilocus inheritance in familial combined hyperlipidemia

Several genome scans in search of high-density lipoprotein (HDL) quantitative trait loci (QTLs) have been performed. However, to date the actual identification of genes implicated in the regulation of common forms of HDL abnormalities remains unsuccessful. This may be due, in part, to the oligogenic and multivariate nature of HDL regulation, and potentially, pleiotropy affecting HDL and other lipid-related traits. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, we recently provided evidence of linkage of HDL level variation to the APOA1-C3-A4-A5 gene complex, in familial combined hyperlipidemia pedigrees, with an estimated number of two to three large QTLs remaining to be identified. We also presented results consistent with pleiotropy affecting HDL and triglycerides at the APOA1-C3-A4-A5 gene complex. Here we use the same MCMC analytic strategy, which allows for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. We now present results from a genome scan in search for the additional HDL QTLs in these pedigrees. We provide evidence of linkage for additional HDL QTLs on chromosomes 3p14 and 13q32, with results on chromosome 3 further supported by maximum parametric and variance component LOD scores of 3.0 and 2.6, respectively. Weaker evidence of linkage was also obtained for 7q32, 12q12, 14q31-32 and 16q23-24.

Evidence for a novel late-onset Alzheimer disease locus on chromosome 19p13.2

Late-onset familial Alzheimer disease (LOFAD) is a genetically heterogeneous and complex disease for which only one locus, APOE, has been definitively identified. Difficulties in identifying additional loci are likely to stem from inadequate linkage analysis methods. Nonparametric methods suffer from low power because of limited use of the data, and traditional parametric methods suffer from limitations in the complexity of the genetic model that can be feasibly used in analysis. Alternative methods that have recently been developed include Bayesian Markov chain-Monte Carlo methods. These methods allow multipoint linkage analysis under oligogenic trait models in pedigrees of arbitrary size; at the same time, they allow for inclusion of covariates in the analysis. We applied this approach to an analysis of LOFAD on five chromosomes with previous reports of linkage. We identified strong evidence of a second LOFAD gene on chromosome 19p13.2, which is distinct from APOE on 19q. We also obtained weak evidence of linkage to chromosome 10 at the same location as a previous report of linkage but found no evidence for linkage of LOFAD age-at-onset loci to chromosomes 9, 12, or 21.