Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation.

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).

CYP2D6 genotype and adjuvant tamoxifen: meta-analysis of heterogeneous study populations.

The International Tamoxifen Pharmacogenomics Consortium was established to address the controversy regarding cytochrome P450 2D6 (CYP2D6) status and clinical outcomes in tamoxifen therapy. We performed a meta-analysis on data from 4,973 tamoxifen-treated patients (12 globally distributed sites). Using strict eligibility requirements (postmenopausal women with estrogen receptor-positive breast cancer, receiving 20 mg/day tamoxifen for 5 years, criterion 1); CYP2D6 poor metabolizer status was associated with poorer invasive disease-free survival (IDFS: hazard ratio = 1.25; 95% confidence interval = 1.06, 1.47; P = 0.009). However, CYP2D6 status was not statistically significant when tamoxifen duration, menopausal status, and annual follow-up were not specified (criterion 2, n = 2,443; P = 0.25) or when no exclusions were applied (criterion 3, n = 4,935; P = 0.38). Although CYP2D6 is a strong predictor of IDFS using strict inclusion criteria, because the results are not robust to inclusion criteria (these were not defined a priori), prospective studies are necessary to fully establish the value of CYP2D6 genotyping in tamoxifen therapy.

NYD-SP18 is associated with obesity in the NHLBI Family Heart Study.

OBJECTIVE: The NHLBI Family Heart Study (FHS) genome-wide linkage scan identified a region of chromosome 7q with a logarithm of odds score of 4.9 for body mass index (BMI). DESIGN: We report the results of fine mapping the linkage peak using 1020 single nucleotide polymorphisms (SNPs) to test for association to obesity in families exhibiting linkage to chromosome 7. Association observed in linked families (284 obese cases/381 controls) was examined in an independent set of unrelated FHS participants (172 obese cases/308 controls) to validate the observed association. Two dichotomous obesity phenotypes were studied based on clinical BMI cutoffs and the sex-specific distribution of both BMI and leptin levels. RESULTS: Using a P-value of 0.01 as criteria for association in the linked families, a P-value of 0.05 as criteria for association in the unrelated sample, and requiring consistency in the direction of the effect of the minor allele between the two samples, we identified two coding SNPs in the NYD-SP18 gene with minor alleles increasing the risk of obesity. Adjustment for exercise, smoking and FTO genotype did not influence the result in linked families, but improved the result in the unrelated sample. Carrying a minor allele of the nonsynonymous SNP rs6971091 conferred an odds ratio of at least 2 for obesity defined by both BMI and leptin levels. CONCLUSION: The effect of the NYD-SP18 SNP on obesity was larger than the effect of FTO in FHS families. Publicly available results from genome-wide association studies support the association between NYD-SP18 and BMI. The NYD-SP18 gene is described as testes development related, but little is known about the gene's function or the mechanism by which it may influence risk for obesity.

Adrenergic receptor polymorphisms associated with resting heart rate: the HyperGEN Study.

The association between polymorphisms in the beta1, beta2 and alpha2B adrenergic receptor (ADR) genes (ADRB1, ADRB2 and ADRA2B) and resting heart rate was examined in white and African-American participants of the HyperGEN Study. All analyses were adjusted for age, sex, body mass index, alcohol use, smoking status and daily exercise within strata of race, hypertension status and beta-blocker use. The Ser49Gly polymorphism of the beta1 ADR was associated with resting heart rate in hypertensive African-Americans and hypertensive whites taking beta-blockers, with carriers of the Gly allele having a higher mean resting heart rate by 2.7 and 4.4 beats per minute (bpm), respectively. The Arg389Gly polymorphism of the beta1 ADR was associated with lower heart rate in the normotensive African-American sample. A beta1 haplotype (Ser49Gly-Arg389Gly) was modestly associated with resting heart rate in the hypertensive African-Americans. The alpha2B C/A polymorphism was associated with heart rate in hypertensive whites, and both whites and African-Americans taking beta-blockers, with carriers of the A allele having a higher mean resting heart rate. In summary, each of the ADR gene polymorphisms was associated with heart rate in at least one stratum studied, but there was no consistent association from which one would infer a large genetic contribution to heart rate.

Sex-specific findings from a genome-wide linkage analysis of human fatness in non-Hispanic whites and African Americans: the HyperGEN study.

OBJECTIVE: To conduct a full genome search for genes potentially influencing two related phenotypes: body mass index (BMI, kg/m2) and percent body fat (PBF) from bioelectric impedance in men and women. DESIGN: A total of 3383 participants, 1348 men and 2035 women; recruitment was initiated with hypertensive sibpairs and expanded to first-degree relatives in a multicenter study of hypertension genetics. MEASUREMENTS: Genotypes for 387 highly polymorphic markers spaced to provide a 10 cM map (CHLC-8) were generated by the NHLBI Mammalian Genotyping Service (Marshfield, WI, USA). Quantitative trait loci for obesity phenotypes, BMI and PBF, were examined with a variance components method using SOLAR, adjusting for hypertensive status, ethnicity, center, age, age2, sex, and age2 x sex. As we detected a significant genotype-by-sex interaction in initial models and because of the importance of sex effects in the expression of these phenotypes, models thereafter were stratified by sex. No genotype-by-ethnicity interactions were found. RESULTS: A QTL influencing PBF in women was detected on chromosome12q (12q24.3-12q24.32, maximum empirical LOD score=3.8); a QTL influencing this phenotype in men was found on chromosome 15q (15q25.3, maximum empirical LOD score=3.0). These QTLs were detected in African-American and white women (12q) and men (15q). QTLs influencing both BMI and PBF were found over a broad region on chromosome 3 in men. QTLs on chromosomes 3 and 12 were found in the combined sample of men and women, but with weaker significance. CONCLUSION: The locations with highest LOD scores have been previously reported for obesity phenotypes, indicating that at least two genomic regions influence obesity-related traits. Furthermore, our results indicate the importance of considering context-dependent effects in the search for obesity QTLs.

Genome-wide scans for heritability of fasting serum insulin and glucose concentrations in hypertensive families.

AIMS/HYPOTHESIS: The heritability of fasting serum insulin and glucose concentrations in non-diabetic members of multiplex hypertensive families is unknown. METHODS: We calculated the familial aggregation of fasting serum glucose and insulin concentrations and performed a genome-wide scan to assess whether quantitative trait loci contribute to these phenotypes in 2,412 non-diabetic individuals from 1,030 families enrolled in the Hypertension Genetic Epidemiology Network (HyperGEN) in the Family Blood Pressure Program. RESULTS: The heritability (+/-SE) of fasting serum insulin was 0.47+/-0.085 in European Americans and 0.28+/-0.08 in African Americans (p<0.0001 for both), after adjusting for age, sex, and BMI. A genome-wide scan for fasting serum insulin yielded a maximum log of the odds (LOD) score of 2.36 on chromosome 5 at 20 cM (p=0.0004) in European Americans, and an LOD score of 2.28 on chromosome 19 at 11 cM (p=0.0004) in African Americans. The heritability of fasting serum glucose was 0.5109+/-0.08 in the former and 0.29+/-0.09 in the latter (p<0.0003 for both) after adjusting for age, sex and BMI. A genome-wide scan for fasting serum glucose revealed a maximum LOD score of 2.07 on chromosome 5 at 26 cM (p=0.0009) in European Americans. CONCLUSIONS/INTERPRETATION: These analyses demonstrate the marked heritability of fasting serum insulin and glucose concentrations in families enriched for the presence of members with hypertension. They suggest that genes associated with fasting serum insulin concentration are present on chromosomes 19 and 5, and that genes associated with fasting serum glucose concentration are on chromosome 5, in families enriched for hypertension.

The agouti-related protein and body fatness in humans.

OBJECTIVE: The objective of this study was to examine the impact of a single nucleotide polymorphism (SNP) (-38C>T) in the promoter of the human agouti-related protein (hAgRP) gene on promoter affinity for transcription factors (TFs) and its possible association with body composition phenotypes. DESIGN: Electrophoretic mobility shift assays for the functional studies and association analyses for the population studies. SUBJECTS AND METHODS: Nuclear extracts were isolated from the mouse hypothalamus cell line GT1-7 and subjected to binding assays using oligonucleotide probes corresponding to the -38C>T region and an antibody for the E12/E47 TFs. Individuals (n = 259) from the HERITAGE Family Study were genotyped for the -38C>T SNP and used in the association studies. RESULTS: Electrophoretic mobility shift and supershift assays confirmed binding of the E12/E47 TF to the -38C>T site in a genotype-dependent manner. The T allele was found exclusively in the black subjects while the genotype with the higher binding affinity, CC, was significantly associated with high BMI, fat mass, and percent body fat in the black subjects of the HERITAGE Family Study. CONCLUSIONS: The E12/E47 TF could play a role in the regulation of hAgRP expression while the population studies suggest that the TT genotype of the -38C>T SNP could play a protective role against the development of obesity in the black population of the HERITAGE Family Study.

Multivariate and multilocus variance components method, based on structural relationships to assess quantitative trait linkage via SEGPATH.

A general-purpose modeling framework for performing path and segregation analysis jointly, called SEGPATH (Province and Rao [1995] Stat. Med. 7:185-198), has been extended to cover "model-free" robust, variance-components linkage analysis, based on identity-by-descent (IBD) sharing. These extended models can be used to analyze linkage to a single marker or to perform multipoint linkage analysis, with a single phenotype or multivariate vector of phenotypes, in pedigrees. Within a single, consistent approach, SEGPATH models can perform segregation analysis, path analysis, linkage analysis, or combinations thereof. SEGPATH models can incorporate environmental or other measured covariate fixed effects (including measured genotypes), genotype-specific covariate effects, population heterogeneity models, repeated-measures models, longitudinal models, autoregressive models, developmental models, gene-by-environment interaction models, etc., with or without linkage components. The data analyzed can have any missing value structure (assumed missing at random), with entire individuals missing, or missing on one or more measurements. Corrections for ascertainment can be made on a vector of phenotypes and/or other measures. Because of the flexibility of the class of models, the SEGPATH approach can also be used in nongenetic applications where there is a hierarchical structure, such as longitudinal, repeated-measures, time series, or nested models. A variety of specific models are provided, as well as some comparisons with other linkage analysis models. Particular applications demonstrate the importance of correctly accounting for the extraneous sources of familial resemblance, as can be done easily with these SEGPATH models, so as to give added power to detect linkage as well as to protect against spuriously inferring linkage.

Genome-wide linkage analysis of lipids in the Hypertension Genetic Epidemiology Network (HyperGEN) Blood Pressure Study.

Full genome scans were performed for quantitative lipid measurements in 622 African American and 649 white sibling pairs not taking lipid-lowering medications who were ascertained through the Hypertension Genetic Epidemiology Network (HyperGEN) of the National Heart, Lung, and Blood Institute (NHLBI) Family Blood Pressure Program. Genotypes for 391 markers spaced roughly equally throughout the genome were typed by the NHLBI Mammalian Genotyping Service. Each of the phenotypes was adjusted for covariates within sex and race and then subjected to variance components linkage analysis, which was performed separately within race by using race-specific marker allele frequencies from additional random samples. The highest lod score detected was 2.77 for logarithmically transformed triglyceride (TG) on chromosome 20 (at 28.6 cM) in the African American sibling pairs. The highest score detected in the white sibling pairs was 2.74 for high density lipoprotein cholesterol on chromosome 5 (at 48.2 cM). Although no scores >3.0 were obtained, positive scores were found in several regions that have been reported in other genome scans in the literature. For example, a score of 1.91 for TG was found on chromosome 15 (at 28.8 cM) in white sibling pairs. This score overlaps the positive findings for TG in 2 other genome scans.

Genome scan for quantitative trait loci linked to high-density lipoprotein cholesterol: The NHLBI Family Heart Study.

We conducted a genome-wide linkage scan for quantitative trait loci influencing total HDL-cholesterol (HDL-C) concentration in a sample of 1027 whites from 101 families participating in the NHLBI Family Heart Study. To maximize the relative contribution of genetic components of variance to the total variance of HDL-C, the HDL-C phenotype was adjusted for age, age(2), body mass index, and Family Heart Study field center, and standardized HDL-C residuals were created separately for men and women. All analyses were completed by the variance components method, as implemented in the program GENEHUNTER using 383 anonymous markers typed at the NHLBI Mammalian Genotyping Service in Marshfield, Wis. Evidence for linkage of residual HDL-C was detected near marker D5S1470 at location 39.9 cM from the p-terminal of chromosome 5 (LOD=3.64). Suggestive linkage was detected near marker D13S1493 at location 27.5 cM on chromosome 13 (LOD=2.36). We conclude that at least 1 genomic region is likely to harbor a gene that influences interindividual variation in HDL cholesterol.

Relation of various degrees of body mass index in patients with systemic hypertension to left ventricular mass, cardiac output, and peripheral resistance (The Hypertension Genetic Epidemiology Network Study).

The impact of different methods of indexation of left ventricular (LV) mass and systemic hemodynamic variables on prevalences and correlates of cardiovascular abnormalities in relation to level of obesity in populations remains unclear. We evaluated 1,672 participants in the Hypertension Genetic Epidemiology Network Study to investigate the relations of overweight and level of obesity to LV mass and prevalences of LV hypertrophy, abnormal cardiac output, and peripheral resistance detected using different indexations for body size. In our study population, 1,577 subjects were clinically healthy nondiabetic hypertensive and 95 were normotensive normal-weight nondiabetic reference subjects. Fat-free mass (FFM) did not differ between the reference group and the normal-weight hypertensive subjects, and increased with overweight. In hypertensive subjects, LV mass and cardiac output increased and total peripheral resistance decreased with overweight. Indexation of LV mass for FFM or body surface area (BSA) resulted in no difference or even lower prevalence of LV hypertrophy in severely obese compared with normal-weight hypertensive subjects. In contrast, indexation of LV mass for height(2.7) identified an increased prevalence of LV hypertrophy with overweight and obesity. Absolute cardiac output increased and total peripheral resistance decreased with overweight. Prevalence of elevated cardiac output indexed for height(1.83) increased and for elevated total peripheral resistance-height(1.83) index decreased with greater overweight, whereas opposite trends were seen when cardiac output and total peripheral resistance were indexed for BSA or FFM. Thus, in hypertensive subjects, FFM increases with overweight and is directly related to LV mass, stroke volume, and cardiac output, and inversely related to total peripheral resistance. Indexations of LV mass and systemic hemodynamics for FFM or BSA obscured associations of LV hypertrophy and abnormal cardiac and total peripheral resistance indexes with overweight, whereas LV mass/height(2,7), cardiac output/height(1.83), and total peripheral resistance-height(1.83) detected significant preclinical cardiovascular abnormalities with obesity.

Linkage analysis of alpha 1-antitrypsin deficiency: lessons for complex diseases.

OBJECTIVES: Severe alpha 1-antitrypsin (A1AT) deficiency is the one proven genetic risk factor for chronic obstructive pulmonary disease (COPD). Familial aggregation has been demonstrated for COPD among individuals who do not have A1AT deficiency, but linkage analysis of COPD has not been reported. To investigate the optimal phenotype definitions and analytical methods for the linkage analysis of COPD, we examined a set of 28 A1AT- deficient families containing 155 individuals. We have used the protease inhibitor (PI) type as a genetic marker rather than a disease gene, and we have performed linkage analysis between PI type and serum A1AT level and spirometry-related phenotypes. METHODS: Linkage analysis was performed on the quantitative phenotypes forced expiratory volume at 1 s (FEV(1) as % predicted), the ratio of FEV(1) to forced vital capacity (FEV(1)/FVC as % predicted), and serum A1AT level using the variance component approach in SOLAR, the generalized estimating equation approach in RELPAL, and the model-based classical lod score method in LINKAGE. Linkage analysis with qualitative A1AT and spirometry phenotypes was performed using a model-based method (LINKAGE) and a model-free method (GENEHUNTER). Adjustments for smoking effects were investigated under each method. RESULTS: All of the methods demonstrated linkage of PI type to serum A1AT level. Interestingly, however, the other quantitative phenotypes provided only weak evidence for linkage of PI type to lung disease. Better evidence for linkage of lung disease to PI type was found using a moderate or a mild threshold for the definition of airflow obstruction. CONCLUSIONS: For linkage analysis of spirometry phenotypes in A1AT deficiency, qualitative phenotypes provided stronger evidence for linkage than quantitative phenotypes. Possible contributors to the stronger evidence for linkage to qualitative spirometry phenotypes include the ascertainment scheme and the nonnormality of the pulmonary function data in PI Z subjects. This study provides guidelines for studies of the genetics of COPD unrelated to A1AT deficiency.

Relation between dietary linolenic acid and coronary artery disease in the National Heart, Lung, and Blood Institute Family Heart Study.

BACKGROUND: Epidemiologic studies suggest that a higher consumption of eicosapentaenoic acid and docosahexaenoic acid is associated with a reduced risk of cardiovascular disease. Studies in humans and animals also reported an inverse association between alpha-linolenic acid and cardiovascular disease morbidity and mortality. OBJECTIVE: We examined the relation between dietary linolenic acid and prevalent coronary artery disease (CAD). DESIGN: We studied 4584 participants with a mean (+/-SD) age of 52.1 +/- 13.7 y in the National Heart, Lung, and Blood Institute Family Heart Study in a cross-sectional design. Participants' diets were assessed with a semiquantitative food-frequency questionnaire. For each sex, we created age- and energy-adjusted quintiles of linolenic acid, and we used logistic regression to estimate prevalent odds ratios for CAD. RESULTS: From the lowest to the highest quintile of linolenic acid, the prevalence odds ratios of CAD were 1.0, 0.77, 0.61, 0.58, and 0.60 for the men (P for trend = 0.012) and 1.0, 0.57, 0.52, 0.30, and 0.42 for the women (P for trend = 0.014) after adjustment for age, linoleic acid, and anthropometric, lifestyle, and metabolic factors. Linoleic acid was also inversely related to the prevalence odds ratios of CAD in the multivariate model (0.60 and 0.61 in the second and third tertiles, respectively) after adjustment for linolenic acid. The combined effect of linoleic and linolenic acids was stronger than the individual effects of either fatty acid. CONCLUSIONS: A higher intake of either linolenic or linoleic acid was inversely related to the prevalence odds ratio of CAD. The 2 fatty acids had synergistic effects on the prevalence odds ratio of CAD.

International Genetic Epidemiology Society: commentary on Darkness in El Dorado by Patrick Tierney.

The International Genetic Epidemiology Society (IGES) has examined the charges against James V. Neel and his colleagues contained in the recently published book by Patrick Tierney entitled Darkness in El Dorado: How Scientists and Journalists Devastated the Amazon (W.W. Norton, 2000). The book implicates Neel in causing or promoting an epidemic of measles among the Yanomamö Indians of Venezuela in 1968 leading to "hundreds if not thousands" of deaths by using a "dinosaur" vaccine (Edmonston B) as a deliberate "experiment" to test his "eugenic" theories. Tierney also attempts to link this research, funded by the Atomic Energy Commission (AEC), with a broader tapestry of human radiation experiments. To investigate these serious charges, the IGES undertook a thorough examination of most source documents referenced in Tierney's book, Neel's field logs, notes, first-hand reports, contemporary writings, film sound tracks, etc., and conducted interviews with many relevant persons. The IGES finds that these allegations are false. Neel was not a eugenicist and was in fact highly critical of both the scientific basis of eugenics and its coercive social policies. In this regard, Tierney has grossly misrepresented Neel's views on a wide range of social implications of modern civilization for the long-term health of the gene pool. Far from causing an epidemic of measles, Neel did his utmost to protect the Yanomamö from the ravages of the impending epidemic by a vaccination program using a vaccine that was widely used at the time and administered in an appropriate manner. There was nothing experimental about the vaccination program, which in fact severely hindered the primary scientific objectives of the expedition. Although the research was funded in large part by the AEC, there was no element of radiation research and the work had no connection with the ethical abuses that have been reported from AEC-sponsored radiation research, such as studies of heavy isotopes. Neel's seminal contributions to a broad range of topics in human genetics have been extensively chronicled elsewhere. His research on the Yanomamö in particular has provided unique insights into the evolutionary biology of our species, the role of sociocultural practices, such as kinship relationships and selective pressures in shaping the genetic diversity of primitive population isolates, as well as the general picture of health in such populations. The IGES decries the damage done to the reputation of one of its founders and its first President and the misperception this book may have caused about the conduct of research in genetic epidemiology. Ethical issues about scientific research in primitive populations deserve serious and wide discussion, but the IGES condemns the gross misrepresentation of the facts and demonization of the principal characters in this book.

The significance of not finding a gene.

As more investigators conduct extensive whole-genome linkage scans for complex traits, interest is growing in meta-analysis as a way of integrating the weak or conflicting evidence from multiple studies. However, there is a bias in the most commonly used meta-analysis linkage technique (i.e., Fisher's [1925] method of combining of P values) when it is applied to many nonparametric (i.e., model free) linkage results. The bias arises in those methods (e.g., variance components, affected sib pair, extremely discordant sib pairs, etc.) that truncate all "negative evidence against linkage" into the single value of LOD = 0. If incorrectly handled, this bias can artificially inflate or deflate the combined meta-analysis linkage results for any given locus. This is an especially troublesome problem in the context of a genome scan, since LOD = 0 is expected to occur over half the unlinked genome. The bias can be overcome (nearly) completely by simply interpreting LOD = 0 as a P value of 1divided by 2ln(2) is approximately equal to .72 in Fisher's formula.

Familial aggregation of submaximal aerobic performance in the HERITAGE Family study.

PURPOSE: This study examines the contribution of genetic factors to submaximal aerobic performance phenotypes measured before and after 20 wk of endurance training. METHODS: Submaximal oxygen consumption (VO(2)) at three power outputs, 50 W (VO(2)50W), 60% (VO(2)60%) and 80% (VO(2)80%) of VO(2max) and power outputs at 60% (PO60%) and 80% (PO80%) of VO(2max) were measured during cycle ergometer exercise tests in 483 subjects from 99 white families participating in the HERITAGE Family study. The baseline phenotypes were adjusted for the effects of age, sex, and body mass using stepwise multiple regression procedures. The response phenotypes, computed as the difference (Delta) between the posttraining and baseline measures, were adjusted for age, sex, and the baseline value. RESULTS: All submaximal exercise phenotypes measured at baseline and in response to training were characterized by a significant familial resemblance. Maximal heritabilities of the baseline phenotypes range from 48% to 74% with significant spouse, sibling, and parent-offspring correlations. The hypothesis of maternal inheritance where mother-offspring and sibling correlations were forced to be equal was found to fit the data for VO(2)60%, VO(2)80% and PO80%. For the response phenotypes, the maximal heritabilities tended to be lower (23--57%) with a significant maternal inheritance for Delta VO(2)60%, Delta PO60%, and Delta PO80%. CONCLUSION: These results suggest that the submaximal working capacities of sedentary subjects and their responses to endurance training are influenced by familial/genetic factors with a significant contribution of maternal inheritance.

Tree-based recursive partitioning methods for subdividing sibpairs into relatively more homogeneous subgroups.

We propose a new splitting rule for recursively partitioning sibpair data into relatively more homogeneous subgroups. This strategy is designed to identify subgroups of sibpairs such that within-subgroup analyses result in increased power to detect linkage using Haseman-Elston regression. We assume that the subgroups can be defined by patterns of non-genetic binary covariates measured on each sibpair. The data we consider consists of the squared difference of a quantitative trait measurement on each sibpair, estimates of identity-by-descent (IBD) values at each genetic marker, and binary covariate data describing characteristics of the sibpair (e.g., race, sex, family history of disease). To test the efficacy of this method in linkage analysis, we performed two simulation experiments. In the first, we simulated a mixture consisting of 66.6% of the sibpairs with no linkage and 33.3% of the sibpairs with genetic linkage to one marker. The two groups were distinguished by the value of a single binary covariate. We also simulated one unlinked marker and one random covariate to include as noise in the data. In the second experiment, we simulated a mixture consisting of 55% of the sibpairs with no genetic linkage, 22.5% of the sibpairs with genetic linkage to one marker, and 22.5% of the sibpairs with linkage to a different marker. Each subgroup was defined by a distinct pattern of two binary covariates. We also simulated one unlinked marker and two random covariates to include as noise in the data. Our simulation studies found that we can significantly increase the overall power to detect linkage by fitting Haseman-Elston regression models to homogeneous subgroups with only a small increase in the false-positive rate. Second, the splitting rule can correctly identify important covariates and linked markers. Third, recursive partitioning of sibpair data using this splitting rule can correctly identify sibpair subgroups. These results indicate that partitioning sibpairs into homogeneous subgroups is feasible and significantly increases the power to detect linkage, thus demonstrating the practical utility and potential this new methodology holds.

A genome-wide scan for abdominal fat assessed by computed tomography in the Québec Family Study.

To identify chromosomal regions harboring genes influencing the propensity to store fat in the abdominal area, a genome-wide scan for abdominal fat was performed in the Quebec Family Study. Cross-sectional areas of the amount of abdominal total fat (ATF) and abdominal visceral fat (AVF) were assessed from a computed tomography scan taken at L4-L5 in 521 adult subjects. Abdominal subcutaneous fat (ASF) was obtained by computing the difference between ATF and AVF. The abdominal fat phenotypes were adjusted for age and sex effects as well as for total amount of body fat (kilogram of fat mass) measured by underwater weighing, and the adjusted phenotypes were used in linkage analyses. A total of 293 microsatellite markers spanning the 22 autosomal chromosomes were typed. The average intermarker distance was 11.9 cM. A maximum of 271 sib-pairs were available for single-point (SIBPAL) and 156 families for multipoint variance components (SEGPATH) linkage analyses. The strongest evidence of linkage was found on chromosome 12q24.3 between marker D12S2078 and ASF (logarithm of odds [LOD] = 2.88). Another marker (D12S1045) located within 2 cM of D12S2078 also provided evidence of sib-pair linkage with ASF (P = 0.019), ATF (P = 0.015), and AVF (P = 0.0007). Other regions with highly suggestive evidence (P < 0.0023 or LOD > or =1.75) of multipoint linkage and evidence (P < 0.05) of single-point linkage, all for ASF, included chromosomes 1p11.2, 4q32.1, 9q22.1, 12q22-q23, and 17q21.1. Three of these loci (1p11.2, 9q22.1, and 17q21.1) are close to genes involved in the regulation of sex steroid levels, whereas two others (4q32.1 and 17q21.1) are in the proximity of genes involved in the regulation of food intake. This first genome-wide scan for abdominal fat assessed by computed tomography indicates that there may be several loci determining the propensity to store fat in the abdominal depot and that some of these loci may influence the development of diabetes in obese subjects.

Familial aggregation of QT-interval variability in a general population: results from the NHLBI Family Heart Study.

QT-interval prolongation is associated with increased risk of cardiac death. Although information on genetics and molecular mechanisms of the congenital long QT syndrome is mounting, limited data are available on the genetics of QT interval in the general population. Heart rate adjusted QT intervals (Bazett's QTc, and QT index (QTI)) were assessed by electrocardiography in 2399 members aged 25-91 years of 468 randomly selected families participating in the NHLBI Family Heart Study. Familial correlation and segregation analyses were performed to evaluate the genetics of the variability of QT interval in this population. The parent-offspring (0.14+/-0.03) and sibling (0.18+/-0.03) correlations for age and sex-adjusted QTc were moderate, while the spouse correlation was close to zero (0.09+/-0.06). This suggests that there are familial/genetic influences on QT-interval variability. Segregation analysis results suggest that there is a major effect in addition to heritable multifactorial effects (h2=0.34), but the major effect did not follow Mendelian inheritance. Further adjustments of QTc for other major cardiovascular risk factors did not significantly change the results. Similar results were found for QTI. The QT-interval variation in the general population is influenced by moderate heritable multifactorial effects in addition to a major effect. A major gene effect is not directly supported.