A genome-wide linkage search for bipolar disorder susceptibility loci in a large and complex pedigree from the eastern part of Cuba.

We present results from a genome-wide scan of a six generation pedigree with 28 affected members with apparently dominant bipolar I disorder from eastern Cuba. Genotypes were obtained using the early access version of the Genechip Mapping 10K Xba array from AFFYMETRIX. Parametric and non-parametric linkage analyses under dominant and recessive models were performed using GENEHUNTER v2.1r5. Two phenotypic models were included in the analyses: bipolar I disorder and recurrent depressive disorder, or bipolar I disorder only. LOD scores were calculated for the entire family combined, and for four subdivisions of the family. For the entire family a suggestive parametric LOD score was obtained under the dominant model and the broader phenotype at 14q11.2-12 (LOD = 2.05). In the same region, a non-parametric LOD score close to genome-wide significance was also obtained, based on the entire family (NPL = 7.31, P-value = 0.07). For two individual branches of the pedigree, genome-wide significance (P < 0.005) was obtained with NPL scores of 8.71 and 12.99, respectively, also in the same region on chromosome 14. Chromosome 5q21.3-22.3 also showed close to genome-wide significant linkage for the complete pedigree (NPL = 7.26, P = 0.07), also supported by significant linkage in one individual branch (NPL = 9.86, P < 0.005). In addition, genome-wide significant nonparametric results (P-values <0.005) were obtained for individual branches at 5p13.1-q12.3, 6p22.3, 8q13.3-21.13, and 10q22.3-23.32. Finally, 2p25.1-25.3, 2p13.3-14, 3p14.2, 6p22.3-24.1, 7p14.1-14.2, 8q12.2-12.3, 10q21.1-21.2, 14q13.1-21.1, 15q15.1-21.2, and 22q12.3-13.32 showed suggestive linkage in the complete family. Most of these potential susceptibility loci overlap with, or are close, to previous linkage findings. The locus on 5q may, however, represent a novel susceptibility locus.     

Selection of eating-disorder phenotypes for linkage analysis.

Vulnerability to anorexia nervosa (AN) and bulimia nervosa (BN) arise from the interplay of genetic and environmental factors. To explore the genetic contribution, we measured over 100 psychiatric, personality, and temperament phenotypes of individuals with eating disorders from 154 multiplex families accessed through an AN proband (AN cohort) and 244 multiplex families accessed through a BN proband (BN cohort). To select a parsimonious subset of these attributes for linkage analysis, we subjected the variables to a multilayer decision process based on expert evaluation and statistical analysis. Criteria for trait choice included relevance to eating disorders pathology, published evidence for heritability, and results from our data. Based on these criteria, we chose six traits to analyze for linkage. Obsessionality, Age-at-Menarche, and a composite Anxiety measure displayed features of heritable quantitative traits, such as normal distribution and familial correlation, and thus appeared ideal for quantitative trait locus (QTL) linkage analysis. By contrast, some families showed highly concordant and extreme values for three variables-lifetime minimum Body Mass Index (lowest BMI attained during the course of illness), concern over mistakes, and food-related obsessions-whereas others did not. These distributions are consistent with a mixture of populations, and thus the variables were matched with covariate linkage analysis. Linkage results appear in a subsequent report. Our report lays out a systematic roadmap for utilizing a rich set of phenotypes for genetic analyses, including the selection of linkage methods paired to those phenotypes.     

Identification of QTLs for serum lipid levels in a female sib-pair cohort: a novel application to improve the power of two-locus linkage analysis

Using a novel approach for a two-locus model that provides a greatly increased power to detect multiple quantitative trait loci (QTLs) in simulated data, we identified in a sample of 961 female sib-pairs, three genome-wide significant QTLs for apolipoprotein A1 on chromosomes 8p21.1-q13.1 (LOD score 3.71), 9q21.32-33.1 (LOD score 3.28) and 10p15.1-p13 (LOD score 5.51), two for lipoprotein (a) on chromosomes 6q25.2-q27 (LOD score 10.18) and 21q21.1-q21.3 (LOD score 4.57) and two for triglycerides on chromosomes 4q28.3-32.1 (LOD score 3.71) and 5q23.1-q32 (LOD score 3.60). The two-locus ordered-subset analysis has led to the confirmation of known and likely identification of novel regions linked to serum lipid levels that would have otherwise been missed and deserves wider application in linkage analyses of quantitative traits. Given the relative lack of power for the sample sizes commonly used in human genetics linkage studies, minor QTL effects often go undetected and those that are detected will be upwardly biased. We show through simulation that the discrepancy between the real and estimated QTL-effects is often likely to generate an unpredictable source of false-negative errors, using multi-locus models, reducing the power to detect multiple QTLs through oligogenic linkage analysis. The successful simultaneous modelling of the identified QTLs in a multi-locus context helps to eliminate false positives and increases the power to detect linkages, adding compelling evidence that they are likely to be reliable QTLs for these lipid traits.     

Two-dimensional genome-scan identifies novel epistatic loci for essential hypertension

It is well established that gene interactions influence common human diseases, but to date linkage studies have been constrained to searching for single genes across the genome. We applied a novel approach to uncover significant gene-gene interactions in a systematic two-dimensional (2D) genome-scan of essential hypertension. The study cohort comprised 2076 affected sib-pairs and 66 affected half-sib-pairs of the British Genetics of HyperTension study. Extensive simulations were used to establish significance thresholds in the context of 2D genome-scans. Our analyses found significant and suggestive evidence for loci on chromosomes 5, 9, 11, 15, 16 and 19, which influence hypertension when gene-gene interactions are taken into account (5q13.1 and 11q22.1, two-locus lod score=5.72; 5q13.1 and 19q12, two-locus lod score=5.35; 9q22.3 and 15q12, two-locus lod score=4.80; 16p12.3 and 16q23.1, two-locus lod score=4.50). For each significant and suggestive pairwise interaction, the two-locus genetic model that best fitted the data was determined. Regions that were not detected using single-locus linkage analysis were identified in the 2D scan as contributing significant epistatic effects. This approach has discovered novel loci for hypertension and offers a unique potential to use existing data to uncover novel regions involved in complex human diseases.     

Analysis of genetic alterations in salivary gland tumors by comparative genomic hybridization.

In order to define and map chromosomal copy number alterations in salivary gland tumors (SGTs), a comparative genomic hybridization (CGH) technique was applied to two pleomorphic adenomas (PAs), one adenoid cystic carcinoma (ACC), and one basal cell adenocarcinoma (BCAC). The PAs exhibited regional copy number losses at 5q12.4-q14.1, 9q12-q21.13, and 16q11.2, as well as a gain at 20p12.1; among these, the losses at the 9q12-q21.11 and 16q11.2 regions were common to both PAs. The ACC showed overrepresentations of the entire regions of chromosomes 16 and 20, a regional gain at 22q12.3-q13.1, and no losses. In the BCAC, regional gains at 9p21.1-pter, 18q21.1-q22.3, and 22q11.23-q13.31 as well as losses at 2q24.2 and 4q25-q27 were seen; the gain at 22q12.3-q13.1 was common in both the ACC and the BCAC. These CGH data indicate that different genetic alterations are present in the different types of SGTs, and that the alterations involve several chromosomes. The discovery of common alterations in the same and/or different types of tumors might be important in the understanding of the development and progression of the SGTs.     

Loci for regulation of bone mineral density in men and women identified by genome wide linkage scan: the FAMOS study

Osteoporosis is a common disease with a strong genetic component, characterized by reduced bone mass and an increased risk of fracture. Bone mineral density (BMD) is a highly heritable trait and a key determinant of osteoporotic fracture risk, but the genes responsible are incompletely defined. Here, we identified quantitative trait loci (QTL) for regulation of BMD by a genome wide scan involving 3691 individuals from 715 families, who were selected because of reduced BMD values at the lumbar spine (LS-BMD) or femoral neck (FN-BMD) in probands. Linkage analysis was conducted in the study group as a whole with correction for age, gender, weight and height. Further analyses were conducted for men and women separately to identify gender-specific QTL and for those under and over the age of 50 years to distinguish QTL for peak bone mass from those that influence bone mass in older people. No regions of suggestive or significant linkage were identified when data from all subjects were analyzed together. On subgroup analysis, however, we identified a significant QTL for FN-BMD on chromosome 10q21 (LOD score +4.42; men < or =50 years) and two suggestive QTL for LS-BMD on chromosomes 18p11 (LOD score +2.83; women >50 years) and 20q13 (LOD score +3.20; women < or =50 years). We identified five other QTL for BMD with LOD scores of greater than +2.20 on chromosomes 3q25, 4q25, 7p14, 16p13 and 16q23. This study provides evidence for gender-specific, site-specific and age-specific QTL, which regulate BMD in humans, and illustrates the importance of conducting subgroup analysis to detect these loci.     

A male-specific quantitative trait locus on 1p21 controlling human stature

Background: Many genome-wide scans aimed at complex traits have been statistically underpowered due to small sample size. Combining data from several genome-wide screens with comparable quantitative phenotype data should improve statistical power for the localisation of genomic regions contributing to these traits. Objective: To perform a genome-wide screen for loci affecting adult stature by combined analysis of four previously performed genome-wide scans. Methods: We developed a web based computer tool, Cartographer, for combining genetic marker maps which positions genetic markers accurately using the July 2003 release of the human genome sequence and the deCODE genetic map. Using Cartographer, we combined the primary genotype data from four genome-wide scans and performed variance components (VC) linkage analyses for human stature on the pooled dataset of 1417 individuals from 277 families and performed VC analyses for males and females separately. Results: We found significant linkage to stature on 1p21 (multipoint LOD score 4.25) and suggestive linkages on 9p24 and 18q21 (multipoint LOD scores 2.57 and 2.39, respectively) in males-only analyses. We also found suggestive linkage to 4q35 and 22q13 (multipoint LOD scores 2.18 and 2.85, respectively) when we analysed both females and males and to 13q12 (multipoint LOD score 2.66) in females-only analyses. Conclusions: We strengthened the evidence for linkage to previously reported quantitative trait loci (QTL) for stature and also found significant evidence of a novel male-specific QTL on 1p21. Further investigation of several interesting candidate genes in this region will help towards characterisation of this first sex-specific locus affecting human stature.     

ADHD in Dutch adults: Heritability and linkage study

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental phenotype that persists into adulthood. This study investigated the heritability of inattentive and hyperactive symptoms and of total ADHD symptomatology load (ADHD index) in adults and performed linkage scans for these dimensions. Data on sibling pairs and their family members from the Netherlands Twin Register with genotype and phenotype data for inattention, hyperactivity and ADHD index (～750 sib‐pairs) were analyzed. Phenotypes were assessed with the short self‐report form of the Conners' Adult ADHD Rating Scales (CAARS). Heritabilities were estimated in SOLAR under polygenic models. Genome‐wide linkage scans were performed using variance components (VC) in MERLIN and MINX and model‐based linkage analysis was carried out in MENDEL with empirical evaluation of the results via simulations. Heritability estimates for inattention, hyperactivity and ADHD index were 35%, 23%, and 31%, respectively. Chromosomes 18q21.31–18q21.32 (VC LOD = 4.58, p_emp = 0.0026) and 2p25.1 (LOD = 3.58, p_emp = 0.0372) provided significant evidence for linkage for inattention and the ADHD index, respectively. The QTL on chromosome 2p25.1 also showed suggestive linkage for hyperactivity. Two additional suggestive QTLs for hyperactivity and the ADHD index shared the same location on chromosome 3p24.3–3p24.1. Finally, a suggestive QTL on 8p23.3–8p23.2 for hyperactivity was also found. Heritability of inattention, hyperactivity and total ADHD symptoms is lower in adults than in children. Chromosomes 18q and 2p are likely to harbor genes that influence several aspects of adult ADHD. © 2011 Wiley‐Liss, Inc.     

Meta-analysis of genome-wide linkage studies for bone mineral density

Genome-wide linkage studies have shown several chromosome loci that may harbor genes that regulate bone mineral density (BMD), but results have been inconsistent. A meta-analysis was performed to assess evidence for linkage of BMD across whole genome scan studies. Eleven whole-genome scans of BMD or osteoporosis containing 3,097 families with 12,685 individuals were included in this genome scan meta-analysis (GSMA). For each study, 120 genomic bins of ~30 cM were defined and ranked according to maximum evidence for linkage within each bin. Bin ranks were weighted and summed across all studies. The summed rank for each bin was assessed empirically for significance using permutation methods. A total of seven bins lie above the 95% confidence level (P=0.05) and one bin was above the 99% confidence level (P=0.01) in the GSMA of eleven linkage studies: bins 16.1 (16pter-16p12.3, Psumrnk <0.01), 3.3 (3p22.2-3p14.1), 1.1 (1pter-1p36.22), 18.2 (18p11.23-18q12.2), 6.3 (6p21.1-6q15), 20.1 (20pter-20p12.3), and 18.1 (18pter-18p11.23). GSMA was performed with seven studies with linkage scores of LOD >1–1.85 for sensitivity test, confirming the linkage on chromosome 16p and 3p and revealing evidence of new linkage in bins 10.2 (10p14-10q11.21) and 22.2 (22q12.3-22pter). In conclusion, the meta-analysis of whole-genome linkage studies of BMD has shown chromosome 16pter-16p12.3 to have the greatest evidence of linkage as well as revealing evidence of linkage in chromosomes 1p, 3p, 6, 10, 18, 20p, and 22q across studies. This data may provide a basis with which to carry out targeted linkage and candidate gene studies particularly in these regions.     

Replication of reported linkages for dyslexia and spelling and suggestive evidence for novel regions on chromosomes 4 and 17

We report the first genome-wide linkage analysis for reading and spelling in a sample of 403 families of twins, aged between 12 and 25 years taken from the normal population and unselected for reading ability. These traits showed heritabilities of 0.52-0.73, and support for linkage exceeded replication levels (lod > 1.44) of seven of the 11 linkages reported in dyslexic samples, namely: 2q22.3, 3p12-q13, 6q11.2, 7q32, 15q21.1, 18p21, and Xq27.3. For five of these (2q22.3, 6q11.2, 7q32, 18p21, and Xq27), this study provides the first independent replication. 1p34-36 and 2p15-16 received some support, with lods of 1.2 and 0.83, respectively, whereas two regions received little support (6p23-21.3 and 11p15.5). This study also identified two novel linkages at 4p15.33-16.1 and 17p13.3, which received suggestive support (max. lod 2.08 and 1.99, respectively).     

Genomewide Linkage Scan for Combined Obesity Phenotypes using Principal Component Analysis

Traditional whole genome linkage scans for obesity were usually performed for a number of correlated obesity related phenotypes separately without considering their correlations. The purpose of this study was to identify quantitative trait loci (QTLs) underlying variations in multiple correlated obesity phenotypes. We performed principal component analysis (PCA) for four highly correlated obesity phenotypes (body mass index [BMI], fat mass, percentage of fat mass [PFM], and lean mass) in a sample of 427 pedigrees (comprising 3,273 individuals) and generated two independent principal components (PC1 and PC2). A whole genome linkage scan (WGS) was then conducted for PC1 and PC2. For PC1, the strongest linkage signal was identified on chromosome 20p12 (LOD = 2.67). For PC2, two suggestive linkages were found on 5q35 (LOD = 2.03) and 7p22 (LOD = 2.18). This study provided evidence supporting several previously identified linkage regions for obesity (e.g., 1p36, 6p23 and 7q34). In addition, our approach by linear combination of highly correlated obesity phenotypes identified several novel QTLs which were not found in genome linkage scans for individual phenotypes.     

Major quantitative trait locus for eosinophil count is located on chromosome 2q

BACKGROUND: Eosinophils are granulocytic white blood cells implicated in asthma and atopic disease. The degree of eosinophilia in the blood of patients with asthma correlates with the severity of asthmatic symptoms. Quantitative trait loci (QTL) linkage analysis of eosinophil count may be a more powerful strategy of mapping genes involved in asthma than linkage analysis using affected relative pairs. OBJECTIVE: To identify QTLs responsible for variation in eosinophil count in adolescent twins. METHODS: We measured eosinophil count longitudinally in 738 pairs of twins at 12, 14, and 16 years of age. We typed 757 highly polymorphic microsatellite markers at an average spacing of approximately 5 centimorgans across the genome. We then used multipoint variance components linkage analysis to test for linkage between marker loci and eosinophil concentrations at each age across the genome. RESULTS: We found highly significant linkage on chromosome 2q33 in 12-year-old twins (logarithm of the odds=4.6; P=.000002) and suggestive evidence of linkage in the same region in 14-year-olds (logarithm of the odds=1.0; P=.016). We also found suggestive evidence of linkage at other areas of the genome, including regions on chromosomes 2, 3, 4, 8, 9, 11, 12, 17, 20, and 22. CONCLUSION: A QTL for eosinophil count is present on chromosome 2q33. This QTL might represent a gene involved in asthma pathophysiology.     

Linkage analysis of left ventricular outflow tract malformations (aortic valve stenosis, coarctation of the aorta, and hypoplastic left heart syndrome)

The left ventricular outflow tract (LVOT) malformations aortic valve stenosis (AVS), coarctation of the aorta (CoA), and hypoplastic left heart syndrome (HLHS) are significant causes of infant mortality. These three malformations are thought to share developmental pathogenetic mechanisms. A strong genetic component has been demonstrated earlier, but the underlying genetic etiologies are unknown. Our objective was to identify genetic susceptibility loci for the broad phenotype of LVOT malformations. We genotyped 411 microsatellites spaced at an average of 10 cM in 43 families constituting 289 individuals, with an additional 5 cM spaced markers for fine mapping. A non-parametric linkage (NPL) analysis of the combined LVOT malformations gave three suggestive linkage peaks on chromosomes 16p12 (NPL score (NPLS)=2.52), 2p23 (NPLS=2.41), and 10q21 (NPLS=2.14). Individually, suggestive peaks for AVS families occurred on chromosomes 16p12 (NPLS=2.64), 7q36 (NPLS=2.31), and 2p25 (NPLS=2.14); and for CoA families on chromosome 1q24 (NPLS=2.61), 6p23 (NPLS=2.29), 7p14 (NPLS=2.27), 10q11 (NPLS=1.98), and 2p15 (NPLS=2.02). Significant NPLS in HLHS families were noted for chromosome 2p15 (NPLS=3.23), with additional suggestive peaks on 19q13 (NPLS=2.16) and 10q21 (NPLS=2.07). Overlapping linkage signals on 10q11 (AVS and CoA) and 16p12 (AVS, CoA, and HLHS) led to higher NPL scores when all malformations were analyzed together. In conclusion, we report suggestive evidence for linkage to chromosomes 2p23, 10q21, and 16p12 for the LVOT malformations of AVS, CoA, and HLHS individually and in a combined analysis, with a significant peak on 2p15 for HLHS. Overlapping linkage peaks provide evidence for a common genetic etiology.     

Linkage analysis of candidate regions for coeliac disease genes

A strong HLA association is seen in coeliac disease [specifically to the DQ(alpha1*0501,beta1*0201 heterodimer], but this cannot entirely account for the increased risk seen in relatives of affected cases. One or more genes at HLA-unlinked loci also predispose to coeliac disease and are probably stronger determinants of disease susceptibility than HLA. A recent study has proposed a number of candidate regions on chromosomes 6p23 (distinct from HLA), 6p12, 3q27, 5q33.3, 7q31.3, 11p11, 15q26, 19p13.3, 19q13.1, 19q13.4 and 22cen for the location of a non-HLA linked susceptibility gene. We have examined these regions in 28 coeliac disease families by linkage analysis. There was excess sharing of chromosome 6p markers, but no support for a predisposition locus telomeric to HLA. No significant evidence in favour of linkage to coeliac disease was obtained for chromosomes 3q27, 5q33.3, 7q31.3, 11p11, 19p13.3, 19q13.1, 19q13.4 or 22cen. There was, however, excess sharing close to D15S642. The maximum non-parametric linkage score was 1.99 (P = 0.03). Although the evidence for linkage of coeliac disease to chromosome 15q26 is not strong, the well established association between coeliac disease and insulin dependent diabetes mellitus, together with the mapping of an IDDM susceptibility locus (IDDM3) to chromosome 15q26, provide indirect support for this as a candidate locus conferring susceptibility to coeliac disease in some families.      

Genomic imbalances in Schistosoma-associated and non-Schistosoma-associated bladder carcinoma. An array comparative genomic hybridization analysis

Carcinoma of the urinary bladder is the most common malignancy in many tropical and subtropical countries due to endemic infection by Schistosoma hematobium (bilharzia). In the current study, we performed a high-resolution analysis of gene copy number amplifications using array comparative genomic hybridization to compare DNA copy number changes in pools of Schistosoma-associated (SA) and non-Schistosoma-associated (NSA) bladder cancer (BC). Many DNA copy number changes were detected in all studies, with multiple gains and losses of genetic material. The most frequent alterations were gains on 5p15.2 approximately p15.33, 8q13.1, and 11q13, and losses on 8p21.3 approximately p22 and 22q13. Even when SA pools showed no Schistosoma-specific gene copy number profiling as compared to NSA pools, some genes seemed to be gained (ELN on 7q11.23) and some lost (PRKAG3 on 2q35 and PRDM6 on 5q23.2) in SA-SCC. The following genes were gained in all histopathologic categories: SRC (20q11.23), CEBPB (20q13.13), and GPR9 (Xq13.1). Our study did not provide clear evidence of differences in carcinogenesis of SA-BC and NSA-BC.     

Genome-wide search for sarcoidosis susceptibility genes in African Americans

Sarcoidosis, a systemic granulomatous disease of unknown etiology, likely results from an environmental insult in a genetically susceptible host. In the US, African Americans are more commonly affected with sarcoidosis and suffer greater morbidity than Caucasians. We searched for sarcoidosis susceptibility loci by conducting a genome-wide, sib pair multipoint linkage analysis in 229 African-American families ascertained through two or more sibs with a history of sarcoidosis. Using the Haseman-Elston regression technique, linkage peaks with P-values less than 0.05 were identified on chromosomes 1p22, 2p25, 5p15-13, 5q11, 5q35, 9q34, 11p15 and 20q13 with the most prominent peak at D5S2500 on chromosome 5q11 (P=0.0005). We found agreement for linkage with the previously reported genome scan of a German population at chromosomes 1p and 9q. Based on the multiple suggestive regions for linkage found in our study population, it is likely that more than one gene influences sarcoidosis susceptibility in African Americans. Fine mapping of the linked regions, particularly on chromosome 5q, should help to refine linkage signals and guide further sarcoidosis candidate gene investigation.     

Combined Genome-Wide Linkage and Association Analyses of Fasting Glucose Level in Healthy Twins and Families of Korea

This study was undertaken to identify genetic polymorphisms that are associated with the risk of an elevated fasting glucose (FG) level using genome-wide analyses. We explored a quantitative trait locus (QTL) for FG level in a genome-wide study from a Korean twin-family cohort (the Healthy Twin Study) using a combined linkage and family-based association analysis approach. We investigated 1,754 individuals, which included 432 families and 219 pairs of monozygotic twins. Regions of chromosomes 2q23.3-2q31.1, 15q26.1-15q26.3, 16p12.1, and 20p13-20p12.2, were found to show evidence of linkage with FG level, and several markers in these regions were found to be significantly associated with FG level using family-based or general association tests. In particular, a single-nucleotide polymorphism (rs6138953) on the PTPRA gene in the 20p13 region (combined P = 1.8 × 10^-6) was found to be associated with FG level, and the PRKCB1 gene (in 16p12.1) to be possibly associated with FG level. In conclusion, multiple regions of chromosomes 2q23.3-2q31.1, 15q26.1-15q26.3, 16p12.1, and 20p13-20p12.2 are associated with FG level in our Korean twin-family cohort. The combined approach of genome-wide linkage and family-based association analysis is useful to identify novel or known genetic regions concerning FG level in a family cohort study.     

Linkage analysis of anorexia nervosa incorporating behavioral covariates

Eating disorders, such as anorexia nervosa (AN) and bulimia nervosa (BN), have genetic and environmental underpinnings. To explore genetic contributions to AN, we measured psychiatric, personality and temperament phenotypes of individuals diagnosed with eating disorders from 196 multiplex families, all accessed through an AN proband, as well as genotyping a battery of 387 short tandem repeat (STR) markers distributed across the genome. On these data we performed a multipoint affected sibling pair (ASP) linkage analysis using a novel method that incorporates covariates. By exploring seven attributes thought to typify individuals with eating disorders, we identified two variables, drive-for-thinness and obsessionality, which delimit populations among the ASPs. For both of these traits, or covariates, there were a cluster of ASPs who have high and concordant values for these traits, in keeping with our expectations for individuals with AN, and other clusters of ASPs who did not meet those expectations. When we incorporated these covariates into the ASP linkage analysis, both jointly and separately, we found several regions of suggestive linkage: one close to genome-wide significance on chromosome 1 (at 210 cM, D1S1660; LOD = 3.46, P = 0.00003), another on chromosome 2 (at 114 cM, D2S1790; LOD = 2.22, P = 0.00070) and a third region on chromosome 13 (at 26 cM, D13S894; LOD = 2.50, P = 0.00035). By comparing our results to those implemented using more standard linkage methods, we find the covariates convey substantial information for the linkage analysis.     

Quantitative trait locus for reading disability on chromosome 6p is pleiotropic for attention-deficit/hyperactivity disorder

Comorbidity is pervasive among both adult and child psychiatric disorders; however, the etiological mechanisms underlying the majority of comorbidities are unknown. This study used genetic linkage analysis to assess the etiology of comorbidity between reading disability (RD) and attention-deficit hyperactivity disorder (ADHD), two common childhood disorders that frequently co-occur. Sibling pairs (N = 85) were ascertained initially because at least one individual in each pair exhibited a history of reading difficulties. Univariate linkage analyses in sibling pairs selected for ADHD from within this RD-ascertained sample suggested that a quantitative trait locus (QTL) on chromosome 6p is a susceptibility locus for ADHD. Because this QTL is in the same region as a well-replicated QTL for reading disability, subsequent bivariate analyses were conducted to test if this QTL contributed to comorbidity between the two disorders. Analyses of data from sib pairs selected for reading deficits revealed suggestive bivariate linkage for ADHD and three measures of reading difficulty, indicating that comorbidity between RD and ADHD may be due at least in part to pleiotropic effects of a QTL on chromosome 6p.     

Using Linkage Analysis to Identify Quantitative Trait Loci for Sleep Apnea in Relationship to Body Mass Index

To understand the genetics of sleep apnea, we evaluated the relationship between the apnea hypopnea index (AHI) and body mass index (BMI) through linkage analysis to identify genetic loci that may influence AHI and BMI jointly and AHI independent of BMI. Haseman‐Elston sibling regression was conducted on AHI, AHI adjusted for BMI and BMI in African‐American and European‐American pedigrees. A comparison of the magnitude of linkage peaks was used to assess the relationship between AHI and BMI. In EAs, the strongest evidence for linkage to AHI was on 6q23‐25 and 10q24‐q25, both decreasing after BMI adjustment, suggesting loci with pleiotropic effects. Also, a promising area of linkage to AHI but not BMI was observed on 6p11‐q11 near the orexin‐2 receptor, suggesting BMI independent pathways. In AAs the strongest evidence of linkage for AHI after adjusting for BMI was on chromosome 8p21.3 with linkage increasing after BMI adjustment and on 8q24.1 with linkage decreasing after BMI adjustment. Novel linkage peaks were also observed in AAs to both BMI and AHI on chromosome 13 near the serotonin‐2a receptor. These analyses suggest genetic loci for sleep apnea that operate both independently of BMI and through BMI‐related pathways.