Genome-wide scan of obesity in Finnish sibpairs reveals linkage to chromosome Xq24

The Relevance of Genomic Signatures at Adhesion GPCR Loci in Humans

Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.

Long intergenic non-coding RNAs (LincRNAs) identified by RNA-seq in breast cancer

In an attempt to find the correlation of aberrant expression of long intergenic noncoding RNAs (lincRNAs) with cancer, twenty-five samples of breast cancer tissue and respective adjacent normal tissue were studied for the expression of lincRNAs by RNA-seq. Among the 538 lincRNAs studied, 124 lincRNAs were exclusively expressed in cancer adjacent tissues and 62 lincRNAs were exclusively expressed in the cancer tissues. Furthermore, the expression of 134 lincRNAs was higher while 272 lower in breast cancer tissue compared with adjacent tissue. The expression of four selected lincRNAs (BC2, BC4, BC5, and BC8) was validated by semi-quantitative and real-time PCR. It was revealed that expression of lincRNA-BC5 was positively correlated with patients' age, pathological stage, and progesterone receptor concentration, while lincRNA-BC8 was negatively correlated with progesterone receptor expression. Higher expression of lincRNA-BC4 was seen in advanced breast cancer grade. LincRNA-BC2 showed no specific changes in the pathological features studied. Interactions between selected lincRNAs and breast cancer associated proteins were highly suggested by RPIseq based on the specific secondary structure. The results demonstrated that this group of lincRNAs was aberrantly expressed in breast cancer. They might play important roles in the function of oncogenes or tumor suppressors affecting the development and progression of breast cancer.

X-linked genes and risk of orofacial clefts: evidence from two population-based studies in Scandinavia

BACKGROUND

Orofacial clefts are common birth defects of complex etiology, with an excess of males among babies with cleft lip and palate, and an excess of females among those with cleft palate only. Although genes on the X chromosome have been implicated in clefting, there has been no association analysis of X-linked markers.

METHODOLOGY/PRINCIPAL FINDINGS

We added new functionalities in the HAPLIN statistical software to enable association analysis of X-linked markers and an exploration of various causal scenarios relevant to orofacial clefts. Genotypes for 48 SNPs in 18 candidate genes on the X chromosome were analyzed in two population-based samples from Scandinavia (562 Norwegian and 235 Danish case-parent triads). For haplotype analysis, we used a sliding-window approach and assessed isolated cleft lip with or without cleft palate (iCL/P) separately from isolated cleft palate only (iCPO). We tested three statistical models in HAPLIN, allowing for: i) the same relative risk in males and females, ii) sex-specific relative risks, and iii) X-inactivation in females. We found weak but consistent associations with the oral-facial-digital syndrome 1 (OFD1) gene (formerly known as CXORF5) in the Danish iCL/P samples across all models, but not in the Norwegian iCL/P samples. In sex-specific analyses, the association with OFD1 was in male cases only. No analyses showed associations with iCPO in either the Norwegian or the Danish sample.

CONCLUSIONS

The association of OFD1 with iCL/P is plausible given the biological relevance of this gene. However, the lack of replication in the Norwegian samples highlights the need to verify these preliminary findings in other large datasets. More generally, the novel analytic methods presented here are widely applicable to investigations of the role of X-linked genes in complex traits.

Recent advances in obesity: genetics and beyond

The prevalence of obesity, which is a heritable trait that arises from the interactions of multiple genes and lifestyle factors, continues to increase worldwide, causing serious health problems and imposing a substantial economic burden on societies. For the past several years, various genetic epidemiological approaches have been utilized to identify genetic loci for obesity. Recent evidence suggests that development of obesity involves hormones and neurotransmitters (such as leptin, cocaine- and amphetamine-regulated transcript (CART), and ghrelin) that regulate appetite and energy expenditure. These hormones act on specific centers in the brain that regulate the sensations of satiety. Mutations in these hormones or their receptors can lead to obesity. Aberrant circadian rhythms and biochemical pathways in peripheral organs or tissues have also been implicated in the pathology of obesity. More interestingly, increasing evidence indicates a potential relation between obesity and central nervous system disorders (such as cognitive deficits). This paper discusses recent advances in the field of genetics of obesity with an emphasis on several established loci that influence obesity. These recently identified loci may hold the promise to substantially improve our insights into the pathophysiology of obesity and open up new therapeutic strategies to combat growing obesity epidemic facing the human population today.

Obstructive sleep apnea syndrome: from phenotype to genetic basis

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity.

Isolation and molecular characterization of the porcine SLC6A14 gene excludes it as a candidate gene for fat deposition and growth

The gene encoding solute carrier family 6 member 14 (SLC6A14) has been considered as a candidate gene affecting human obesity. In this study, full-length cDNA (2237 bp) and DNA sequence (24 541 bp) of the porcine SLC6A14 gene were isolated. The porcine SLC6A14 cDNA contains a 5&rsquo;-untranslated region of 57 bp, a 3&rsquo;-untranslated region of 254 bp, and an open reading frame of 1926 bp, encoding a deduced protein of 642 amino acids with a molecular mass of 72. 475 kDa and an isoelectric point of 7.82. The genomic structure of the porcine SLC6A14 gene is similar to mammalian orthologs, particularly in terms of exon size and exon/intron boundaries. It comprises 14 exons and 13 introns. A semi-quantitative RT-PCR showed that the porcine SLC6A14 mRNA expression was tissue-specific. Four SLC6A14 single-nucleotide polymorphisms (SNPs) were identified, and 3 informative SNPs were chosen for genotyping in a White Duroc &times; Erhualian resource population with phenotype data of growth and fatness traits. The association analysis showed that the c.1438 G>A nonsynonymous polymorphism was associated with birth weight and 21-day body weight (P < 0.05), while g.7944 A>T was associated with 46-day body weight. Linkage and radiation hybrid mapping assigned SLC6A14 to a region around SW1522 on SSCXp13, which did not fall in the confidence interval of the quantitative trait locus (QTL) for growth and fatness traits on SSCX in the resource population. These results indicate that SLC6A14 is not a positional candidate gene for the QTL affecting fatness and growth traits in pigs.

AMPK as Target for Intervention in Childhood and Adolescent Obesity

Childhood obesity is a major worldwide health problem. Intervention programs to ameliorate the rate of obesity have been designed and implemented; yet the epidemic has no end near in sight. AMP-activated protein kinase (AMPK) has become one of the most important key elements in energy control, appetite regulation, myogenesis, adipocyte differentiation, and cellular stress management. Obesity is a multifactorial disease, which has a very strong genetic component, especially epigenetic factors. The intrauterine milieu has a determinant impact on adult life, since the measures taken for survival are kept throughout life thanks to epigenetic modification. Nutrigenomics studies the influence of certain food molecules on the metabolome profile, raising the question of an individualized obesity therapy according to metabolic (and probably) genetic features. Metformin, an insulin sensitizing agent, its known to lower insulin resistance and enhance metabolic profile, with an additional weight reduction capacity, via activation of AMPK. Exercise is coadjutant for lifestyle modifications, which also activates AMPK in several ways contributing to glucose and fat oxidation. The following review examines AMPK's role in obesity, applying its use as a tool for childhood and adolescent obesity.

Evidence that multiple genetic variants of MC4R play a functional role in the regulation of energy expenditure and appetite in Hispanic children

BACKGROUND

Melanocortin-4-receptor (MC4R) haploinsufficiency is the most common form of monogenic obesity; however, the frequency of MC4R variants and their functional effects in general populations remain uncertain.

OBJECTIVE

The aim was to identify and characterize the effects of MC4R variants in Hispanic children.

DESIGN

MC4R was resequenced in 376 parents, and the identified single nucleotide polymorphisms (SNPs) were genotyped in 613 parents and 1016 children from the Viva la Familia cohort. Measured genotype analysis (MGA) tested associations between SNPs and phenotypes. Bayesian quantitative trait nucleotide (BQTN) analysis was used to infer the most likely functional polymorphisms influencing obesity-related traits.

RESULTS

Seven rare SNPs in coding and 18 SNPs in flanking regions of MC4R were identified. MGA showed suggestive associations between MC4R variants and body size, adiposity, glucose, insulin, leptin, ghrelin, energy expenditure, physical activity, and food intake. BQTN analysis identified SNP 1704 in a predicted micro-RNA target sequence in the downstream flanking region of MC4R as a strong, probable functional variant influencing total, sedentary, and moderate activities with posterior probabilities of 1.0. SNP 2132 was identified as a variant with a high probability (1.0) of exerting a functional effect on total energy expenditure and sleeping metabolic rate. SNP rs34114122 was selected as having likely functional effects on the appetite hormone ghrelin, with a posterior probability of 0.81.

CONCLUSION

This comprehensive investigation provides strong evidence that MC4R genetic variants are likely to play a functional role in the regulation of weight, not only through energy intake but through energy expenditure.

Admixture mapping of 15,280 African Americans identifies obesity susceptibility loci on chromosomes 5 and X

The prevalence of obesity (body mass index (BMI) > or =30 kg/m(2)) is higher in African Americans than in European Americans, even after adjustment for socioeconomic factors, suggesting that genetic factors may explain some of the difference. To identify genetic loci influencing BMI, we carried out a pooled analysis of genome-wide admixture mapping scans in 15,280 African Americans from 14 epidemiologic studies. Samples were genotyped at a median of 1,411 ancestry-informative markers. After adjusting for age, sex, and study, BMI was analyzed both as a dichotomized (top 20% versus bottom 20%) and a continuous trait. We found that a higher percentage of European ancestry was significantly correlated with lower BMI (rho = -0.042, P = 1.6x10(-7)). In the dichotomized analysis, we detected two loci on chromosome X as associated with increased African ancestry: the first at Xq25 (locus-specific LOD = 5.94; genome-wide score = 3.22; case-control Z = -3.94); and the second at Xq13.1 (locus-specific LOD = 2.22; case-control Z = -4.62). Quantitative analysis identified a third locus at 5q13.3 where higher BMI was highly significantly associated with greater European ancestry (locus-specific LOD = 6.27; genome-wide score = 3.46). Further mapping studies with dense sets of markers will be necessary to identify the alleles in these regions of chromosomes X and 5 that may be associated with variation in BMI.

Association test for X-linked QTL in family-based designs

Family-based association methods for detecting quantitative trait loci (QTL) have been developed primarily for autosomes, and comparable methods for X-linked QTL have received less attention. We have developed a family-based association test for quantitative traits, named XQTL, which uses X-linked markers in a nuclear family design. XQTL adopts the framework of the orthogonal model implemented in the QTDT program, modifying the sex-specific score for X-linked genotypes. XQTL also takes into account the dosage effect due to female X chromosome inactivation. Restricted maximum likelihood (REML) and Fisher's scoring method are used to estimate variance components of random effects. Fixed effects, derived from the phenotypic differences among and within families, are estimated by the least-squares method. Our proposed XQTL can perform allelic and two-locus haplotypic association tests and can provide estimates of additive genetic effects and variance components. Simulation studies show correct type I error rates under the null hypothesis and robust statistical power under alternative scenarios. The loss of power observed when parental genotypes are missing can be compensated by an increase of offspring number. By treating age at onset of Parkinson disease as a quantitative trait, we illustrate our method, using MAO polymorphisms in 780 families.

Genetics of obesity

Considerable attention is currently being paid to the secular changes in food intake and physical activity that underlie the increase in the prevalence of obesity that is apparent in many societies. While this is laudable it would be unwise to view these environmental factors in isolation from the biological factors that normally control body weight and composition and the compelling evidence that inter-individual differences in susceptibility to obesity have strong genetic determinants. This is particularly important, as it is only in the past decade that we have begun to obtain substantive information regarding the molecular constituents of pathways controlling mammalian energy balance and therefore, for the first time, are in a position to achieve a better mechanistic understanding of this disease. Population-based association and linkage studies have highlighted a number of loci at which genetic variation is associated with obesity and related phenotypes and the identification and characterization of monogenic obesity syndromes has been particularly fruitful. While there is widespread acceptance that hereditary factors might predispose to human obesity, it is frequently assumed that such factors would influence metabolic rate or the selective partitioning of excess calories into fat. However, it is notable that, thus far, all monogenic defects causing human obesity actually disrupt hypothalamic pathways and have a profound effect on satiety and food intake. To conclude, the evidence we have to date suggests that the major impact of genes on human obesity is just as likely (or perhaps more likely) to directly impact on hunger, satiety and food intake rather than metabolic rate or nutrient partitioning. At the risk of oversimplification, it seems that from an aetiological/genetic standpoint, human obesity appears less a metabolic than a neuro-behavioural disease.

Is a gene important for bone resorption a candidate for obesity? An association and linkage study on the RANK (receptor activator of nuclear factor-kappaB) gene in a large Caucasian sample

In light of findings that osteoporosis and obesity may share some common genetic determination and previous reports that RANK (receptor activator of nuclear factor-kappaB) is expressed in skeletal muscles which are important for energy metabolism, we hypothesize that RANK, a gene essential for osteoclastogenesis, is also important for obesity. In order to test the hypothesis with solid data we first performed a linkage analysis around the RANK gene in 4,102 Caucasian subjects from 434 pedigrees, then we genotyped 19 SNPs in or around the RANK gene. A family-based association test (FBAT) was performed with both a quantitative measure of obesity [fat mass, lean mass, body mass index (BMI), and percentage fat mass (PFM)] and a dichotomously defined obesity phenotype-OB (OB if BMI > or = 30 kg/m(2)). In the linkage analysis, an empirical P = 0.004 was achieved at the location of the RANK gene for BMI. Family-based association analysis revealed significant associations of eight SNPs with at least one obesity-related phenotype (P < 0.05). Evidence of association was obtained at SNP10 (P = 0.002) and SNP16 (P = 0.001) with OB; SNP1 with fat mass (P = 0.003); SNP1 (P = 0.003) and SNP7 (P = 0.003) with lean mass; SNP1 (P = 0.002) and SNP7 (P = 0.002) with BMI; SNP1 (P = 0.003), SNP4 (P = 0.007), and SNP7 (P = 0.002) with PFM. In order to deal with the complex multiple testing issues, we performed FBAT multi-marker test (FBAT-MM) to evaluate the association between all the 18 SNPs and each obesity phenotype. The P value is 0.126 for OB, 0.033 for fat mass, 0.021 for lean mass, 0.016 for BMI, and 0.006 for PFM. The haplotype data analyses provide further association evidence. In conclusion, for the first time, our results suggest that RANK is a novel candidate for determination of obesity.

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.

A large set of Finnish affected sibling pair families with type 2 diabetes suggests susceptibility loci on chromosomes 6, 11, and 14

The aim of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genes that predispose to type 2 diabetes or are responsible for variability in diabetes-related traits via a positional cloning and positional candidate gene approach. In a previously published genome-wide scan of 478 Finnish affected sibling pair (ASP) families (FUSION 1), the strongest linkage results were on chromosomes 20 and 11. We now report a second genome-wide scan using an independent set of 242 Finnish ASP families (FUSION 2), a detailed analysis of the combined set of 737 FUSION 1 + 2 families (495 updated FUSION 1 families), and fine mapping of the regions of chromosomes 11 and 20. The strongest FUSION 2 linkage results were on chromosomes 6 (maximum logarithm of odds score [MLS] = 2.30 at 95 cM) and 14 (MLS = 1.80 at 57 cM). For the combined FUSION 1 + 2 families, three results were particularly notable: chromosome 11 (MLS = 2.98 at 82 cM), chromosome 14 (MLS = 2.74 at 58 cM), and chromosome 6 (MLS = 2.66 at 96 cM). We obtained smaller FUSION 1 + 2 MLSs on chromosomes X (MLS = 1.27 at 152 cM) and 20p (MLS = 1.21 at 20 cM). Among the 10 regions that showed nominally significant evidence for linkage in FUSION 1, four (on chromosomes 6, 11, 14, and X) also showed evidence for linkage in FUSION 2 and stronger evidence for linkage in the combined FUSION 1 + 2 sample.

The SLC6A14 gene shows evidence of association with obesity

In our previous genome-wide scan of Finnish nuclear families, obesity was linked to chromosome Xq24. Here we analyzed this 15-Mb region by genotyping 9 microsatellite markers and 36 single nucleotide polymorphisms (SNPs) for 11 positional and functional candidate genes in an extended sample of 218 obese Finnish sibling pairs (sibpairs) (BMI > 30 kg/m2). Evidence of linkage emerged mainly from the obese male sibpairs, suggesting a gender-specific effect for the underlying gene. By constructing haplotypes among the obese male sibpairs, we restricted the region from 15 Mb to 4 Mb, between markers DXS8088 and DXS8067. Regional functional candidate genes were tested for association in an initial sample of 117 cases and 182 controls. Significant evidence was observed for association for an SNP in the 3'-untranslated region of the solute carrier family 6 member 14 (SLC6A14) gene (P = 0.0002) and for SNP haplotypes of the SLC6A14 gene (P = 0.0007-0.006). Furthermore, an independent replication study sample of 837 cases and 968 controls from Finland and Sweden also showed significant differences in allele frequencies between obese and non-obese individuals (P = 0.003). The SLC6A14 gene is an interesting novel candidate for obesity because it encodes an amino acid transporter, which potentially regulates tryptophan availability for serotonin synthesis and thus possibly affects appetite control.

Do allelic variants of SLC6A14 predispose to obesity?

Obesity is arguably the world's most prevalent nutritional disorder and is a substantial contributor to morbidity and early mortality. Obesity is known to have a strong genetic component, but the specific influential genes in humans are largely unknown. A new paper describes a genetic variant that appears as though it may cause some people to be fatter or thinner than others (see the related article beginning on page 1762). This commentary considers the strength of the evidence in support of this finding and discusses additional research questions that should be addressed in further evaluations of this genetic variant as a putative contributor to human obesity.

The human MC4R promoter: characterization and role in obesity

Heterozygous mutations in the coding sequence of the serpentine melanocortin 4 receptor (MC4R) are the most frequent genetic cause of severe human obesity. Since haploinsufficiency has been proposed as a causal mechanism of obesity associated with these mutations, reduction in gene transcription caused by mutations in the transcriptionally essential regions of the MC4R promoter may also be a cause of severe obesity in humans. To test this hypothesis we defined the minimal promoter region of the human MC4R and evaluated the extent of genetic variation in this region compared with the coding region in two cohorts of severely obese subjects. 5'RACE followed by functional promoter analysis in multiple cell lines indicates that an 80-bp region is essential for the transcriptional activity of the MC4R promoter. Systematic screening of 431 obese children and adults for mutations in the coding sequence and the minimal core promoter of MC4R reveals that genetic variation in the transcriptionally essential region of the MC4R promoter is not a significant cause of severe obesity in humans.

Linkage for BMI at 3q27 region confirmed in an African-American population

Significant and suggestive linkage for BMI on 3q27 has been reported by several groups, including our own study in African Americans. To further establish the linkage evidence on 3q27, we recruited an independent African-American sample comprising 545 individuals in 128 families. We genotyped 15 short tandem-repeat markers evenly spaced in the 112 cM region around the peak on 3q27 identified in our earlier study. Multipoint linkage analysis by GENEHUNTER2 gave the maximum logarithm of odds (LOD) score 2.4 at map position 188 cM in this sample. When we combined the two samples, linkage evidence was increased to a maximum LOD score (MLS) of 4.3 (point-wise P = 4.34 x 10(-6)) at 188 cM, with a 7 cM 1-LOD-drop interval around the peak. The multiple replications of linkage evidence in the region on 3q27 strongly confirm its potential importance as a candidate region in the search for obesity-related genes.

Genome scan for childhood and adolescent obesity in German families

OBJECTIVE

Several genome scans have been performed for adult obesity. Because single formal genetic studies suggest a higher heritability of body weight in adolescence and because genes that influence body weight in adulthood might not be the same as those that are relevant in childhood and adolescence, we performed a whole genome scan.

METHODS

The genome scan was based on 89 families with 2 or more obese children (sample 1). The mean age of the index patients was 13.63 +/- 2.75 years. A total of 369 individuals were initially genotyped for 437 microsatellite markers. A second sample of 76 families was genotyped using microsatellite markers that localize to regions for which maximum likelihood binomial logarithm of the odd (MLB LOD) scores on use of the concordant sibling pair approach exceeded 0.7 in sample 1.

RESULTS

The regions with MLB LOD scores >0.7 were on chromosomes 1p32.3-p33, 2q37.1-q37.3, 4q21, 8p22, 9p21.3, 10p11.23, 11q11-q13.1, 14q24-ter, and 19p13-q12 in sample 1; MLB LOD scores on chromosomes 8p and 19q exceeded 1.5. In sample 2, MLB LOD scores of 0.68 and 0.71 were observed for chromosomes 10p11.23 and 11q13, respectively.

CONCLUSION

We consider that several of the peaks identified in other scans also gave a signal in this scan as promising for ongoing pursuits to identify relevant genes. The genetic basis of childhood and adolescent obesity might not differ that much from adult obesity.

An X-chromosome scan reveals a locus for fat distribution in chromosome region Xp21-22

Several groups have completed autosomal genome scans for human obesity, but only two have examined the X chromosome. A French group reported linkage of BMI to Xp and Xq markers, and a Finnish group reported linkage of BMI to Xq. We scanned the X chromosome in two cohorts, 190 European-American families (940 members) and 43 African-American families (208 members). We examined five correlated obesity phenotypes, BMI, body fat percentage, hip and waist circumferences, and plasma leptin concentration. We also examined leptin resistance (leptin/BMI) and fat patterning (waist-to-hip ratio [WHR]). Variables were adjusted for age within generation, race, and sex. We genotyped 20 markers with average spacing of 10 cM and no interval >22 cM and conducted nonparametric analyses. Suggestive linkage was found for WHR only. Linkage was supported in both family sets, and support was especially strong for females. Z scores for analyses of female phenotypes were 2.69, 1.73, and 2.37 (P = 0.0036, 0.0418, and 0.0089) for African-Americans, European-Americans, and the combined sample, respectively. The peaks were 51-73 cM from the p terminus, 14-34 cM distal of the French report in Xp22. Our results suggest that a quantitative trait locus influencing fat distribution in women may lie in chromosome region Xp21-22; however, the linked interval is large and differs substantially from that of the French and Finnish groups. Given the positive but divergent results, it would be worthwhile for others to examine the X chromosome.

A combined analysis of genomewide linkage scans for body mass index from the National Heart, Lung, and Blood Institute Family Blood Pressure Program

A combined analysis of genome scans for obesity was undertaken using the interim results from the National Heart, Lung, and Blood Institute Family Blood Pressure Program. In this research project, four multicenter networks of investigators conducted eight individual studies. Data were available on 6,849 individuals from four ethnic groups (white, black, Mexican American, and Asian). The sample represents the largest single collection of genomewide scan data that has been analyzed for obesity and provides a test of the reproducibility of linkage analysis for a complex phenotype. Body mass index (BMI) was used as the measure of adiposity. Genomewide linkage analyses were first performed separately in each of the eight ethnic groups in the four networks, through use of the variance-component method. Only one region in the analyses of the individual studies showed significant linkage with BMI: 3q22.1 (LOD 3.45, for the GENOA network black sample). Six additional regions were found with an associated LOD >2, including 3p24.1, 7p15.2, 7q22.3, 14q24.3, 16q12.2, and 17p11.2. Among these findings, the linkage at 7p15.2, 7q22.3, and 17p11.2 has been reported elsewhere. A modified Fisher's omnibus procedure was then used to combine the P values from each of the eight genome scans. A complimentary approach to the meta-analysis was undertaken, combining the average allele-sharing identity by descent (pi) for whites, blacks, and Mexican Americans. Using this approach, we found strong linkage evidence for a quantitative-trait locus at 3q27 (marker D3S2427; LOD 3.40, P=.03). The same location has been shown to be linked with obesity-related traits and diabetes in at least two other studies. These results (1) confirm the previously reported obesity-susceptibility locus on chromosomes 3, 7, and 17 and (2) demonstrate that combining samples from different studies can increase the power to detect common genes with a small-to-moderate effect, so long as the same gene has an effect in all samples considered.

Quantitative-trait loci influencing body-mass index reside on chromosomes 7 and 13: the National Heart, Lung, and Blood Institute Family Heart Study

Obesity is a risk factor for many chronic diseases, including glucose intolerance, lipid disorders, hypertension, and coronary heart disease. Even though the body-mass index (BMI) is a heterogeneous phenotype reflecting the amount of fat, lean mass, and body build, several studies have provided evidence of one or two major loci contributing to the variation in this complex trait. We sought to identify loci with potential influence on BMI in the data obtained from National Heart, Lung, and Blood Institute Family Heart Study. Two complementary samples were studied: (a) 1,184 subjects in 317 sibships, with 243 markers typed by the Utah Molecular Genetics Laboratory (UMGL) and (b) 3,027 subjects distributed among 401 three-generation families, with 404 markers typed by the Mammalian Genotyping Service (MGS). A genome scan using a variance-components-based linkage approach was performed for each sample, as well as for the combined sample, in which the markers from each analysis were placed on a common genetic map. There was strong evidence for linkage on chromosome 7q32.3 in each sample: the maximum multipoint LOD scores were 4.7 (P<10-5) at marker GATA43C11 and 3.2 (P=.00007) at marker D7S1804, for the MGS and UMGL samples, respectively. The linkage result is replicated by the consistent evidence from these two complementary subsets. Furthermore, the evidence for linkage was maintained in the combined sample, with a LOD score of 4.9 (P<10-5) for both markers, which map to the same location. This signal is very near the published location for the leptin gene, which is the most prominent candidate gene in this region. For the combined-sample analysis, evidence of linkage was also found on chromosome 13q14, with D13S257 (LOD score 3.2, P=.00006), and other, weaker signals (LOD scores 1.5-1.9) were found on chromosomes 1, 2, 3, 5, 6, 14, and 15.

Genomewide scans of complex human diseases: true linkage is hard to find

Many "complex" human diseases, which involve multiple genetic and environmental determinants, have increased in incidence during the past 2 decades. During the same time period, considerable effort and expense have been expended in whole-genome screens aimed at detection of genetic loci contributing to the susceptibility to complex human diseases. However, the success of positional cloning attempts based on whole-genome screens has been limited, and many of the fundamental questions relating to the genetic epidemiology of complex human disease remain unanswered. Both to review the success of the positional cloning paradigm as applied to complex human disease and to investigate the characteristics of the whole-genome scans undertaken to date, we created a database of 101 studies of complex human disease, which were found by a systematic Medline search (current as of December 2000). We compared these studies, concerning 31 different human complex diseases, with regard to design, methods, and results. The "significance" categorizations proposed by Lander and Kruglyak were used as criteria for the "success" of a study. Most (66.3% [n=67]) of the studies did not show "significant" linkage when the criteria of Lander and Kruglyak (1995) were used, and the results of studies of the same disease were often inconsistent. Our analyses suggest that no single study design consistently produces more-significant results. Multivariate analysis suggests that the only factors independently associated with increased study success are (a) an increase in the number of individuals studied and (b) study of a sample drawn from only one ethnic group. Positional cloning based on whole-genome screens in complex human disease has proved more difficult than originally had been envisioned; detection of linkage and positional cloning of specific disease-susceptibility loci remains elusive.

Quantitative-trait-locus analysis of body-mass index and of stature, by combined analysis of genome scans of five Finnish study groups

In recent years, many genomewide screens have been performed, to identify novel loci predisposing to various complex diseases. Often, only a portion of the collected clinical data from the study subjects is used in the actual analysis of the trait, and much of the phenotypic data is ignored. With proper consent, these data could subsequently be used in studies of common quantitative traits influencing human biology, and such a reanalysis method would be further justified by the nonbiased ascertainment of study individuals. To make our point, we report here a quantitative-trait-locus (QTL) analysis of body-mass index (BMI) and stature (i.e., height), with genotypic data from genome scans of five Finnish study groups. The combined study group was composed of 614 individuals from 247 families. Five study groups were originally ascertained in genetic studies on hypertension, obesity, osteoarthritis, migraine, and familial combined hyperlipidemia. Most of the families are from the Finnish Twin Cohort, which represents a population-wide sample. In each of the five genome scans, approximately 350 evenly spaced markers were genotyped on 22 autosomes. In analyzing the genotype data by a variance-component method, we found, on chromosome 7pter (maximum multipoint LOD score of 2.91), evidence for QTLs affecting stature, and a second locus, with suggestive evidence for linkage to stature, was detected on chromosome 9q (maximum multipoint LOD score of 2.61). Encouragingly, the locus on chromosome 7 is supported by the data reported by Hirschhorn et al. (in this issue), who used a similar method. We found no evidence for QTLs affecting BMI.