Quantitative Trait Linkage Analysis Research Articles

The relation between nicotinamide N-methyltransferase gene polymorphism and plasma homocysteine concentration in healthy Japanese men

0049-3848/$ see front matter © 2007 Elsevier Ltd. All rights reserv doi:10.1016/j.thromres.2007.02.012 polymorphisms are reported to associate with tHcy concentration, including the most notable methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism. Recently, a quantitative trait linkage (QTL) analysis on tHcy concentrationwas conducted in a Spanish family study of venous thrombosis [3]. The chromosome region 11q23 was shown to have a positive linkage signal, and in this region the nicotinamide Nmethyltransferase (NNMT) gene was located. Subsequent analysis for 10 single nucleotide polymorphisms (SNPs) in the NNMT gene identified one SNP (rs694539 in GenBank, dBSNP database) that was associated with the tHcy concentration. Since the SNP resides in the first intron, the functional significance of it is still unknown. NNMTenzyme activity was shown to have a significant variability among individual, and this difference was attributed not to the structure of the enzyme but to the expression levels of mRNA and protein [4,5]. Thus, this noncoding SNP might be related to the regulation of transcription, which correlates to the phenotype.

Heritability and genetic loci of fatty liver in familial combined hyperlipidemia

VLDL overproduction, a process that is driven by an excess amount of hepatic fat, is a well-documented feature of familial combined hyperlipidemia (FCHL). The aims of this study were to investigate whether fatty liver, measured with ultrasound and as plasma alanine aminotransferase (ALT) levels, develops against a genetic background in FCHL and to identify chromosomal loci that are linked to these traits. In total, 157 FCHL family members and 20 spouses participated in this study. Radiological evidence of fatty liver was more prevalent not only in FCHL probands (40%) but also in their relatives (35%) compared with spouses (15%) (P < 0.05). Heritability calculations revealed that 20-36% of the variability in ALT levels could be attributed to genetic factors. Nonparametric quantitative trait locus (QTL) analysis revealed three significant (P < 0.001) loci with either the ultrasound or the ALT trait in the male sample: 1q42.3, 7p12-21, and 22p13-q11; none was found in the female sample or the entire group. Of these QTLs, the 7p region was consistent over time, because reanalysis with ALT levels that were determined during a visit 5 years earlier yielded similar results. This study shows that fatty liver is a heritable aspect of FCHL. Replication of particularly the 7p region is awaited.

Idiopathic Scoliosis: Identification of Candidate Regions on Chromosome 19p13

We performed genomic screening, statistical linkage analysis, and fine mapping of 202 families with at least 2 individuals with idiopathic scoliosis. To identify regions on chromosome 19p13 statistically linked to the phenotypic expression of idiopathic scoliosis. Idiopathic scoliosis is a common structural curvature of the spine affecting otherwise healthy children. Presently, no clear consensus exists regarding the underlying abnormality or genetic determinants of this disease. Model-independent linkage analysis of qualitative and quantitative traits related to scoliosis was used to screen genotyping data from 391 markers in 202 families (1198 individuals). Subsets of families with probands having a curve > or = 30 degrees were dichotomized based on the most likely mode of inheritance for each family (autosomal dominant or X-linked dominant). Fine mapping was performed to show linkage to candidate regions on chromosome 19. When the threshold of disease was set at a curvature of > or = 30 degrees, qualitative linkage analysis revealed significant results at 2 successive markers on chromosome 19. The data confirm a previously reported genetic locus on chromosome 19 as potentially significant in the etiology of idiopathic scoliosis.

Allele frequency misspecification: effect on power and Type I error of model-dependent linkage analysis of quantitative traits under random ascertainment

BackgroundStudies of model-based linkage analysis show that trait or marker model misspecification leads to decreasing power or increasing Type I error rate. An increase in Type I error rate is seen when marker related parameters (e.g., allele frequencies) are misspecified and ascertainment is through the trait, but lod-score methods are expected to be robust when ascertainment is random (as is often the case in linkage studies of quantitative traits). In previous studies, the power of lod-score linkage analysis using the "correct" generating model for the trait was found to increase when the marker allele frequencies were misspecified and parental data were missing. An investigation of Type I error rates, conducted in the absence of parental genotype data and with misspecification of marker allele frequencies, showed that an inflation in Type I error rate was the cause of at least part of this apparent increased power. To investigate whether the observed inflation in Type I error rate in model-based LOD score linkage was due to sampling variation, the trait model was estimated from each sample using REGCHUNT, an automated segregation analysis program used to fit models by maximum likelihood using many different sets of initial parameter estimates.ResultsThe Type I error rates observed using the trait models generated by REGCHUNT were usually closer to the nominal levels than those obtained when assuming the generating trait model.ConclusionThis suggests that the observed inflation of Type I error upon misspecification of marker allele frequencies is at least partially due to sampling variation. Thus, with missing parental genotype data, lod-score linkage is not as robust to misspecification of marker allele frequencies as has been commonly thought.

Mapping Genetic Loci That Determine Leukocyte Telomere Length in a Large Sample of Unselected Female Sibling Pairs

Telomeres play a central role in cellular senescence and cancer pathobiology and are associated with age-related diseases such as atherosclerosis and dementia. Telomere length varies between individuals of the same age, is influenced by DNA-damaging factors such as oxidative stress, and is heritable. We performed a quantitative-trait linkage analysis using an approximate 10-cM genomewide map for mean leukocyte terminal-restriction fragment (TRF) lengths measured by Southern blotting, in 2,050 unselected women aged 18-80 years, comprising 1,025 complete dizygotic twin pairs. Heritability of mean batch-adjusted TRF was 36% (95% confidence interval [CI] 18%-48%), with a large common environmental effect of 49% (95% CI 40%-58%). Significant linkage was observed on chromosome 14 (LOD 3.9) at 14q23.2, and suggestive linkage at 10q26.13 (LOD 2.4) and 3p26.1 (LOD 2.7). This is the first report of loci, mapped in a sample of healthy individuals, that influence mean telomere variation in humans.

Linkage analysis of quantitative traits for obesity, diabetes, hypertension, and dyslipidemia on the island of Kosrae, Federated States of Micronesia.

Obesity, diabetes, hypertension, and heart disease are highly heritable conditions that in aggregate are the major causes of morbidity and mortality in the developed world and are growing problems in developing countries. To map the causal genes, we conducted a population screen for these conditions on the Pacific Island of Kosrae. Family history and genetic data were used to construct a pedigree for the island. Analysis of the pedigree showed highly significant heritability for the metabolic traits under study. DNA samples from 2,188 participants were genotyped with 405 microsatellite markers with an average intermarker distance of 11 cM. A protocol using loki, a Markov chain Monte Carlo sampling method, was developed to analyze the Kosraen pedigree for height, a model quantitative trait. Robust quantitative trait loci for height were found on 10q21 and 1p31. This protocol was used to map a set of metabolic traits, including plasma leptin to chromosome region 5q35; systolic blood pressure to 20p12; total cholesterol to 19p13, 12q24, and 16qter; hip circumference to 10q25 and 4q23; body mass index to 18p11 and 20q13; apolipoprotein B to 2p24-25; weight to 18q21; and fasting blood sugar to 1q31-1q43. Several of these same chromosomal regions have been identified in previous studies validating the use of loki. These studies add information about the genetics of the metabolic syndrome and establish an analytical approach for linkage analysis of complex pedigrees. These results also lay the foundation for whole genome scans with dense sets of SNPs aimed to identifying causal genes.

Genome-wide linkage analysis of age at onset of alcohol dependence: a comparison between microsatellites and single-nucleotide polymorphisms

BackgroundUsing the dataset provided for Genetic Analysis Workshop 14 by the Collaborative Study on the Genetics of Alcoholism, we performed genome-wide linkage analysis of age at onset of alcoholism to compare the utility of microsatellites and single-nucleotide polymorphisms (SNPs) in genetic linkage study.MethodsA multipoint nonparametric variance component linkage analysis method was applied to the survival distribution function obtained from semiparametric proportional hazards model of the age at onset phenotype of alcoholism. Three separate linkage analyses were carried out using 315 microsatellites, 2,467 and 9,467 SNPs, spanning the 22 autosomal chromosomes.ResultsHeritability of age at onset was estimated to be approximately 12% (p < 0.001). We observed weak correlation, both in trend and strength, of genome-wide linkage signals between microsatellites and SNPs. Results from SNPs revealed more and stronger linkage signals across the genome compared with those from microsatellites. The only suggestive evidence of linkage from microsatellites was on chromosome 1 (LOD of 1.43). Differences in map densities between the two sets of SNPs used in this study did not appear to confer an advantage in terms of strength of linkage signals.ConclusionOur study provided support for better performance of dense SNP maps compared with the sparse mirosatellite maps currently available for linkage analysis of quantitative traits. This better performance could be attributable to precise definition and high map resolutions achievable with dense SNP maps, thus resulting in increased power to detect possible loci affecting given trait or disease.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality.Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Boosting alternating decision trees modeling of disease trait information

We applied the alternating decision trees (ADTrees) method to the last 3 replicates from the Aipotu, Danacca, Karangar, and NYC populations in the Problem 2 simulated Genetic Analysis Workshop dataset. Using information from the 12 binary phenotypes and sex as input and Kofendrerd Personality Disorder disease status as the outcome of ADTrees-based classifiers, we obtained a new quantitative trait based on average prediction scores, which was then used for genome-wide quantitative trait linkage (QTL) analysis. ADTrees are machine learning methods that combine boosting and decision trees algorithms to generate smaller and easier-to-interpret classification rules. In this application, we compared four modeling strategies from the combinations of two boosting iterations (log or exponential loss functions) coupled with two choices of tree generation types (a full alternating decision tree or a classic boosting decision tree). These four different strategies were applied to the founders in each population to construct four classifiers, which were then applied to each study participant. To compute average prediction score for each subject with a specific trait profile, such a process was repeated with 10 runs of 10-fold cross validation, and standardized prediction scores obtained from the 10 runs were averaged and used in subsequent expectation-maximization Haseman-Elston QTL analyses (implemented in GENEHUNTER) with the approximate 900 SNPs in Hardy-Weinberg equilibrium provided for each population. Our QTL analyses on the basis of four models (a full alternating decision tree and a classic boosting decision tree paired with either log or exponential loss function) detected evidence for linkage (Z ≥ 1.96, p < 0.01) on chromosomes 1, 3, 5, and 9. Moreover, using average iteration and abundance scores for the 12 phenotypes and sex as their relevancy measurements, we found all relevant phenotypes for all four populations except phenotype b for the Karangar population, with suggested subgroup structure consistent with latent traits used in the model. In conclusion, our findings suggest that the ADTrees method may offer a more accurate representation of the disease status that allows for better detection of linkage evidence.

The quantitative trait linkage disequilibrium test: a more powerful alternative to the quantitative transmission disequilibrium test for use in the absence of population stratification

Linkage analysis based on identity-by-descent allele-sharing can be used to identify a chromosomal region harboring a quantitative trait locus (QTL), but lacks the resolution required for gene identification. Consequently, linkage disequilibrium (association) analysis is often employed for fine-mapping. Variance-components based combined linkage and association analysis for quantitative traits in sib pairs, in which association is modeled as a mean effect and linkage is modeled in the covariance structure has been extended to general pedigrees (quantitative transmission disequilibrium test, QTDT). The QTDT approach accommodates data not only from parents and siblings, but also from all available relatives. QTDT is also robust to population stratification. However, when population stratification is absent, it is possible to utilize even more information, namely the additional information contained in the founder genotypes. In this paper, we introduce a simple modification of the allelic transmission scoring method used in the QTDT that results in a more powerful test of linkage disequilibrium, but is only applicable in the absence of population stratification. This test, the quantitative trait linkage disequilibrium (QTLD) test, has been incorporated into a new procedure in the statistical genetics computer package SOLAR. We apply this procedure in a linkage/association analysis of an electrophysiological measurement previously shown to be related to alcoholism. We also demonstrate by simulation the increase in power obtained with the QTLD test, relative to the QTDT, when a true association exists between a marker and a QTL.

Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families

BackgroundIn this paper we apply two novel quantitative trait linkage statistics based on the posterior probability of linkage (PPL) to chromosome 4 from the GAW 14 COGA dataset. Our approaches are advantageous since they use the full likelihood, use full phenotypic information, do not assume normality at the population level or require population/sample parameter estimates; and like other forms of the PPL, they are specifically tailored to accumulate linkage evidence, either for or against linkage, across multiple sets of heterogeneous data.ResultsThe first statistic uses all quantitative trait (QT) information from the pedigree (QT-posterior probability of linkage, PPL); we applied the QT-PPL to the trait ecb21 (resting electroencephalogram). The second statistic allows simultaneous incorporation of dichotomous trait data into the QT analysis via a threshold model (QTT-PPL); we applied the QTT-PPL to combined data on ecb21 and ALDX1. We obtained a QT-PPL of 96% at GABRB1 and a QT-PPL of 18% at FABP2 while the QTT-PPL was 4% and 2% at the same two loci, respectively. By comparison, the variance-components (VC) method, as implemented in SOLAR, yielded multipoint VC LOD scores of 2.05 and 2.21 at GABRB1 and FABP2, respectively; no other VC LODs were greater than 2.ConclusionThe QTT-PPL was only 4% at GABARB1, which might suggest that the underlying ecb21 gene does not also cause ALDX1, although features of the data complicate interpretation of this result.

A genome-wide linkage scan for ankle–brachial index in African American and non-Hispanic white subjects participating in the GENOA study

Little is known about the genetics of peripheral arterial disease (PAD). We performed linkage analyses to identify genomic regions that influence ankle–brachial index (ABI), a measure of PAD, in 1310 African Americans (AA) (mean age 62 ± 9 years) and 796 non-Hispanic whites (NHW) (mean age 58 ± 9 years) belonging to hypertensive sibships. ABI was determined at two sites in each lower extremity and the lower of the two average ABIs was used in the analyses after adjustment for age, age 2, sex, weight, total cholesterol, HDL cholesterol, and ever-smoking. Genotypes were measured at microsatellite marker loci spaced approximately 10 cM apart across the 22 autosomes. Heritability was assessed by SOLAR and linkage analyses performed using a variance components approach. Modest heritability ( h 2) was noted for the fully adjusted ABI in each ethnic group ( h 2 = 0.195, P = 0.002 in AA; h 2 = 0.212, P = 0.006 in NHW). Univariate linkage analyses demonstrated tentative evidence of linkage (multipoint LOD = 1.3–2.0) for ABI on chromosomes 1p, 6q, 7q, 10p, and 16p in AA and on chromosome 3p and 3q in NHW. In conclusion, ABI is a modestly heritable trait in AA and NHW hypertensive sibships. Quantitative trait linkage analyses identified several chromosomal regions that may harbor genes influencing ABI.

Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia

We conducted a genome-wide scan using variance components linkage analysis to localize quantitative-trait loci (QTLs) influencing triglyceride (TG), high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol, and total cholesterol (TC) levels in 3,071 subjects from 459 families with atherogenic dyslipidemia. The most significant evidence for linkage to TG levels was found in a subset of Turkish families at 11q22 [logarithm of the odds ratio (LOD)=3.34] and at 17q12 (LOD=3.44). We performed sequential oligogenic linkage analysis to examine whether multiple QTLs jointly influence TG levels in the Turkish families. These analyses revealed loci at 20q13 that showed strong epistatic effects with 11q22 (conditional LOD=3.15) and at 7q36 that showed strong epistatic effects with 17q12 (conditional LOD=3.21). We also found linkage on the 8p21 region for TG in the entire group of families (LOD=3.08). For HDL-C levels, evidence of linkage was identified on chromosome 15 in the Turkish families (LOD=3.05) and on chromosome 5 in the entire group of families (LOD=2.83). Linkage to QTLs for TC was found at 8p23 in the entire group of families (LOD=4.05) and at 5q13 in a subset of Turkish and Mediterranean families (LOD=3.72). These QTLs provide important clues for the further investigation of genes responsible for these complex lipid phenotypes. These data also indicate that a large proportion of the variance of TG levels in the Turkish population is explained by the interaction of multiple genetic loci.

A Variant in XPNPEP2 Is Associated with Angioedema Induced by Angiotensin I–Converting Enzyme Inhibitors

Angiotensin I-converting enzyme inhibitors (ACEi), which are used to treat common cardiovascular diseases, are associated with a potentially life-threatening adverse reaction known as angioedema (AE-ACEi). We have previously documented a significant association between AE-ACEi and low plasma aminopeptidase P (APP) activity. With eight large pedigrees, we hereby demonstrate that this quantitative trait is partially regulated by genetic factors. We tested APP activity using a variance-component QTL analysis of a 10-cM genomewide microsatellite scan enriched with seven markers over two candidate regions. We found significant linkage (LOD = 3.75) to a locus that includes the XPNPEP2 candidate gene encoding membrane-bound APP. Mutation screening of this QTL identified a large coding deletion segregating in one pedigree and an upstream single-nucleotide polymorphism (C-2399A SNP), which segregates in the remaining seven pedigrees. Measured genotype analysis strongly suggests that the linkage signal for APP activity at this locus is accounted for predominantly by the SNP association. In a separate case-control study (20 cases and 60 controls), we found significant association of this SNP to ACEi-induced AE (P=.0364). In conclusion, our findings provide supporting evidence that the C-2399A variant in XPNPEP2 is associated with reduced APP activity and a higher incidence of AE-ACEi.

A new method of linkage analysis using LOD scores for quantitative traits supports linkage of monoamine oxidase activity to D17S250 in the Collaborative Study on the Genetics of Alcoholism pedigrees

Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance. The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism. With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set, suggesting that QMFLINK may have been able to detect a true linkage which was not picked up by the other methods. The application of model-free LOD score analysis to quantitative traits is novel and deserves further evaluation of its merits and disadvantages relative to other methods.

The genetic contribution to longitudinal changes in knee structure and muscle strength: A sibpair study

To estimate the heritability of longitudinal changes in knee cartilage volume, chondral defects, subchondral bone size, and lower limb muscle strength. A sibpair design was used. Longitudinal changes in lateral and medial tibial cartilage volume and bone size, as well as progression of chondral defects, were determined on serial magnetic resonance images. Radiographs were obtained and scored for individual features of radiographic osteoarthritis (OA) at baseline. Lower limb muscle strength was measured by dynamometry. Heritability was estimated using the SOLAR software package. A total of 115 subjects (55 men and 60 women, mean age 45 years) from 48 families representing 95 sibling pairs were successfully followed up for a mean of 2.4 years. The adjusted heritability estimates for changes in cartilage volume were 73% for the medial compartment (P < 0.01) and 40% for the lateral compartment (P = 0.10). The adjusted heritability estimates for changes in bone size were 62% for the lateral compartment (P = 0.03) and 20% for the medial compartment (P = 0.22). The adjusted heritability estimate for changes in muscle strength was 64% (P = 0.01). The adjusted heritability estimates for progression of chondral defects were 80% for the lateral compartment (P = 0.06) and 98% for the medial compartment (P = 0.03). These estimates changed little after adjusting for each other and for the predominantly mild radiographic OA, with the exception of progression of chondral defects in the lateral compartment. Early longitudinal changes in knee structures of relevance to later OA, such as changes in medial tibial cartilage volume, lateral tibial bone size, progression of chondral defects, and muscle strength, have high heritability, most likely reflecting a strong genetic component and suggesting their potential to be studied in quantitative trait linkage and association analysis.

Genomewide Significant Linkage to Migrainous Headache on Chromosome 5q21

Familial typical migraine is a common, complex disorder that shows strong familial aggregation. Using latent-class analysis (LCA), we identified subgroups of people with migraine/severe headache in a community sample of 12,245 Australian twins (60% female), drawn from two cohorts of individuals aged 23-90 years who completed an interview based on International Headache Society criteria. We report results from genomewide linkage analyses involving 756 twin families containing a total of 790 independent sib pairs (130 affected concordant, 324 discordant, and 336 unaffected concordant for LCA-derived migraine). Quantitative-trait linkage analysis produced evidence of significant linkage on chromosome 5q21 and suggestive linkage on chromosomes 8, 10, and 13. In addition, we replicated previously reported typical-migraine susceptibility loci on chromosomes 6p12.2-p21.1 and 1q21-q23, the latter being within 3 cM of the rare autosomal dominant familial hemiplegic migraine gene (ATP1A2), a finding which potentially implicates ATP1A2 in familial typical migraine for the first time. Linkage analyses of individual migraine symptoms for our six most interesting chromosomes provide tantalizing hints of the phenotypic and genetic complexity of migraine. Specifically, the chromosome 1 locus is most associated with phonophobia; the chromosome 5 peak is predominantly associated with pulsating headache; the chromosome 6 locus is associated with activity-prohibiting headache and photophobia; the chromosome 8 locus is associated with nausea/vomiting and moderate/severe headache; the chromosome 10 peak is most associated with phonophobia and photophobia; and the chromosome 13 peak is completely due to association with photophobia. These results will prove to be invaluable in the design and analysis of future linkage and linkage disequilibrium studies of migraine.

Genomewide linkage analysis of soluble transferrin receptor plasma levels

Genetic control of soluble transferrin receptor (sTfR) levels was demonstrated using family-based studies (GAIT, Genetic Analysis of Idiopathic Thrombophilia project); moreover, a genetic relationship was observed between sTfR and the risk for thrombosis, suggesting that these phenotypes shared genetic determinants. We studied the regions that control sTfR. To assess such regions, a full genome scan was carried out using 604 highly polymorphic deoxyribonucleic acid markers (resolution 7.3 cM) in 21 extended pedigrees (358 individuals). Then, a quantitative trait linkage analysis was performed using variance components methods. The genomewide scan linkage analysis showed two regions (quantitative trait locus or QTL) with significant limit of detection (LOD) scores (2q23.14, LOD score = 2.64, nominal p = 0.00024; 3q21.2, LOD score = 1.94, nominal p = 0.0014). There were no obvious candidate genes in these regions. In conclusion, this linkage analysis suggested the existence of a QTL in 2q23.14 that probably harbored a gene (or genes) controlling sTfR levels. Moreover, a second linkage signal was observed in 3q21.2; albeit the evidence for this second locus was lower. The next step will be to identify the gene(s) and its possible involvement in thrombosis and iron homeostasis.

Identification of Candidate Regions for Familial Idiopathic Scoliosis

A genomic screen and statistical linkage analysis of 202 families with at least two individuals with idiopathic scoliosis was performed. To identify candidate regions or the autosomal loci that may be involved in the expression of familial idiopathic scoliosis. A large sample of families with individuals having idiopathic scoliosis (202 families; 1,198 individuals) was ascertained; diagnoses were based on physical examination and radiographic criteria. Model-independent linkage analysis of qualitative and quantitative traits (degree of lateral curvature) related to scoliosis was used to screen genotyping data from 391 markers in the 202 families. Subsets of families were determined before genotyping based on the most likely mode of inheritance for each family (autosomal dominant vs. X-linked dominant). Fine mapping results corroborated linkage in the primary candidate regions. Candidate regions on chromosomes 6, 9, 16, and 17 were considered to have the strongest evidence for linkage across all subsets considered. Linkage analyses have identified several candidate regions, a significant step in defining the genetic etiology of this disorder.

A genome wide quantitative trait linkage analysis for serum lipids in type 2 diabetes in an African population

Lipid abnormalities are strongly linked with coronary heart disease and are common in type 2 diabetes. However, little is known about the genetic determinants of serum lipids in African populations. An autosomal genome scan was performed for linkage to five plasma lipid phenotypes (total cholesterol, triglycerides (TG), HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C) and VLDL-cholesterol (VLDL-C)) in the Africa–America Diabetes Mellitus (AADM) study. Two hundred and ninety-five affected sibling pairs with type 2 diabetes mellitus enrolled from Ghana and Nigeria were genotyped for 390 microsatellite markers with an average inter-marker distance of 9 cM. Multipoint variance components linkage analysis showed that HDL-C had a LOD score of 4.34 near marker D7S3061 and 3.00 near marker D7S513. Some clustering of linkage evidence to several lipid phenotypes was observed on chromosomes 5 (LDL-C, total cholesterol, VLDL-C), chromosome 7 (HDL-C, TG) and chromosome 19 (total cholesterol, LDL-C, TG). Principal component analysis of the five phenotypes yielded two factors, one (TG, HDL-C and VLDL) of which was linked to QTLs on chromosomes 2, 5 and 7, while the other (total cholesterol and LDL-C) was linked to a different set of QTLs on chromosomes 2, 5 and 18. Several of these regions have been reported to be linked to lipids in other studies. Follow up investigations are warranted in view of the central role serum lipids play in the aetiopathogenesis of cardiovascular disease.