Multiple Genes Influence BMI on Chromosome 7q31–34: The NHLBI Family Heart Study

The National Heart, Lung, and Blood Institute Family Heart Study (FHS) genome‐wide linkage scan identified a region of chromosome 7q31–34 with a lod score of 4.9 for BMI at D7S1804 (131.9 Mb). We report the results of linkage and association to BMI in this region for two independent FHS samples. The first sample includes 225 FHS pedigrees with evidence of linkage to 7q31–34, using 1,132 single‐nucleotide polymorphisms (SNPs) and 7 microsatellites. The second represents a case–control sample (318 cases; BMI >25 and 325 controls; BMI <25) derived from unrelated FHS participants who were not part of the genome scan. The latter set was genotyped for 606 SNPs, including 37 SNPs with prior evidence for association in the linked families. Although variance components linkage analysis using only SNPs generated a peak lod score that coincided with the original linkage scan at 131.9 Mb, a conditional linkage analysis showed evidence of a second quantitative trait locus (QTL) near 143 cM influencing BMI. Three SNPs (rs161339, rs12673281, and rs1993068) located near the three genes pleiotrophin (PTN), diacylglycerol (DAG) kinase iota (DGKι), and cholinergic receptor, muscarinic 2 (CHRM2) demonstrated significant association in both linked families (P = 0.0005, 0.002, and 0.03, respectively) and the case–control sample (P = 0.01, 0.0003, and 0.03, respectively), regardless of the genetic model tested. These findings suggest that several genes may be associated with BMI in the 7q31–34 region.     

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

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

A QTL for genotype by sex interaction for anthropometric measurements in Alaskan Eskimos (GOCADAN Study) on chromosome 19q12-13

Variation in anthropometric measurements due to sexual dimorphism can be the result of genotype by sex interactions (G×S). The purpose of this study was to examine the sex-specific genetic architecture in anthropometric measurements in Alaskan Eskimos from the Genetics of Coronary Artery Disease in Alaska Natives (GOCADAN) study. Maximum likelihood-based variance components decomposition methods, implemented in SOLAR, were used for G×S analyses. Anthropometric measurements included BMI, waist circumference (WC), waist/height ratio, percent body fat (%BF), and subscapular and triceps skinfolds. Except for WC, mean values of all phenotypes were significantly different in men and women (P < 0.05). All anthropometric measures were significantly heritable (P < 0.001). In a preliminary analysis not allowing for G×S interaction, evidence of linkage was detected between markers D19S414 and D19S220 on chromosome 19 for WC (logarithm of odds (lod) = 3.5), %BF (lod = 1.7), BMI (lod = 2.4), waist/height ratio (lod = 2.5), subscapular (lod = 2.1), and triceps skinfolds (lod = 1.9). In subsequent analyses which allowed for G×S interaction, linkage was again found between these traits and the same two markers on chromosome 19 with significantly improved lod scores for: WC (lod = 4.5), %BF (lod = 3.8), BMI (lod = 3.5), waist/height ratio (lod = 3.2), subscapular (lod = 3.0), and triceps skinfolds (lod = 2.9). These results support the evidence of a G×S interaction in the expression of genetic effects resulting in sexual dimorphism in anthropometric phenotypes and identify the chromosome 19q12-13 region as important for adiposity-related traits in Alaskan Eskimos.     

Susceptibility Loci for Adiposity Phenotypes on 8p, 9p,and 16q in American Samoa and Samoa

Obesity is a complex phenotype affected by genetic and environmental influences such as sociocultural factors and individual behaviors. Previously, we performed two separate genome‐wide investigations for adiposity‐related traits (BMI, percentage body fat (%BF), abdominal circumference (ABDCIR), and serum leptin and serum adiponectin levels) in families from American Samoa and in families from Samoa. The two polities have a common evolutionary history but have lately been influenced by variations in economic development, leading to differences in income and wealth and in dietary and physical activity patterns. We now present a genome‐wide linkage scan of the combined samples from the two polities. We adjust for environmental covariates, including polity of residence, education, cigarette smoking, and farm work, and use variance component methods to calculate univariate and bivariate multipoint lod scores. We identified a region on 9p22 with genome‐wide significant linkage for the bivariate phenotypes ABDCIR–%BF (1‐d.f. lod 3.30) and BMI–%BF (1‐d.f. lod 3.31) and two regions with genome‐wide suggestive linkage on 8p12 and 16q23 for adiponectin (lod 2.74) and the bivariate phenotype leptin‐ABDCIR (1‐d.f. lod 3.17), respectively. These three regions have previously been reported to be linked to adiposity‐related phenotypes in independent studies. However, the differences in results between this study and our previous polity‐specific studies suggest that environmental effects are of different importance in the samples. These results strongly encourage further genetic studies of adiposity‐related phenotypes where extended sets of carefully measured environmental factors are taken into account.     

家蚕茧质性状的QTL定位研究

采用QTLMapper 2．0 QTL作图软件,对F2群体的家蚕全茧量、茧层量、茧层率和蛹体重等性状进行了QTL定位分析,分别检测出7个、6个、2个、8个有显著效应分量的QTLs,分布于7个、5个、2个、7个不同的连锁群。控制全茧量、茧层量的QTLs一般存在复杂的上位性效应。对全茧量性状,有3对QTLs存在显著的加加上位性效应,其中1对还存在加显、显显互作;共有3个QTLs存在显著的显性效应,1个存在显著的加性效应。对茧层量QTLs,发现1对QTLs存在极显著的各项遗传效应,包括上位性效应;1对QTLs被检测到显著的显显互作,1个QTL具有显著的显性效应,并与另一个QTL存在显著的加加互作。茧层率、蛹体重主要受加性或显性的QTLs作用,没有发现茧层率QTLs的上位性效应,蛹体重的有效QTL大都呈现显著的负向显性效应,只有一对QTLs存在显著的加加上位性效应。第2、3、4、11、13、24、34、37、40连锁群是两个或多个性状QTLs分布的共同连锁群。全茧量和茧层量存在共同的QTL或染色体区域,育种上可通过适当选配,利用基因的互作效应,同步改良这两个性状。     

The genetic basis of flowering time and photoperiod sensitivity in rapeseed (Brassica napus L.)

The objective of this study was to dissect the genetic control of days to flowering (DTF) and photoperiod sensitivity (PS) into the various components including the main-effect quantitative trait loci (QTLs), epistatic QTLs and QTL-by-environment interactions (QEs). Doubled haploid (DH) fines were produced from an F1 between two spring Brassica napus cultivars Hyola 401 and Q2. DTF of the DH lines and parents were investigated in two locations, one location with a short and the other with a long photoperiod regime over two years. PS was calculated by the delay in DTF under long day as compared to that under short day. A genetic linkage map was constructed that comprised 248 marker loci including SSR, SRAP and AFLP markers. Further QTL analysis resolved the genetic components of flowering time and PS into the main-effect QTLs, epistatic QTLs and QEs. A total of 7 main-effect QTLs and 11 digenic interactions involving 21 loci located on 13 out of the 19 linkage groups were detected for the two traits. 3 main-effect QTLs and 4 pairs of epistatic QTLs were involved in QEs conferring DTF. One QTL on linkage group (LG) 18 was revealed to simultaneously affect DTF and PS and explain for the highest percentage of the phenotypic variation. The implications of the results for B. napus breeding have been discussed.     

Identification of quantitative trait loci for bruchid (Caryedon serratus Olivier) resistance components in cultivated groundnut (Arachis hypogaea L.)

Groundnut bruchid (Caryedon serratus Olivier) is a major storage insect pest that significantly lowers the quality and market acceptance of the produce. Screening for resistance against groundnut bruchid in field conditions is difficult due to the variation in environmental factors and possible occurrence of biotypes. Hence, identification of tightly linked markers or quantitative trait loci (QTLs) is needed for selection and pyramiding of resistance genes for durable resistance. A population of recombinant inbred lines derived from a cross between VG 9514 (resistant) and TAG 24 (susceptible) was screened for five component traits of bruchid resistance in 2 years. The same population was genotyped with 221 polymorphic marker loci. A genetic linkage map covering 1,796.7 cM map distance was constructed with 190 marker loci in cultivated groundnut. QTL analysis detected thirteen main QTLs for four components of bruchid resistance in nine linkage groups and 31 epistatic QTLs for total developmental period (TDP). Screening in 2 years for bruchid resistance identified two common main QTLs. The common QTL for TDP, qTDP-b08, explained 57–82 % of phenotypic variation, while the other common QTL for adult emergence, qAE2010/11-a02, explained 13–21 % of phenotypic variation. Additionally, three QTLs for TDP, adult emergence and number of holes and one QTL for pod weight loss were identified which explained 14–39 % of phenotypic variation. This is the first report on identification of multiple main and epistatic loci for bruchid resistance in groundnut.     

A genomewide linkage scan for quantitative-trait loci for obesity phenotypes

Obesity is an increasingly serious health problem in the world. Body mass index (BMI), percentage fat mass, and body fat mass are important indices of obesity. For a sample of pedigrees that contains >10,000 relative pairs (including 1,249 sib pairs) that are useful for linkage analyses, we performed a whole-genome linkage scan, using 380 microsatellite markers to identify genomic regions that may contain quantitative-trait loci (QTLs) for obesity. Each pedigree was ascertained through a proband who has extremely low bone mass, which translates into a low BMI. A major QTL for BMI was identified on 2q14 near the marker D2S347 with a LOD score of 4.04 in two-point analysis and a maximum LOD score (MLS) of 4.44 in multipoint analysis. The genomic region near 2q14 also achieved an MLS >2.0 for percentage of fat mass and body fat mass. For the putative QTL on 2q14, as much as 28.2% of BMI variation (after adjustment for age and sex) may be attributable to this locus. In addition, several other genomic regions that may contain obesity-related QTLs are suggested. For example, 1p36 near the marker D1S468 may contain a QTL for BMI variation, with a LOD score of 2.75 in two-point analysis and an MLS of 2.09 in multipoint analysis. The genomic regions identified in this and earlier reports are compared for further exploration in extension studies that use larger samples and/or denser markers for confirmation and fine-mapping studies, to eventually identify major functional genes involved in obesity.     

Common genetic determinants of uveitis shared with other autoimmune disorders

Uveitis is a complex multifactorial autoimmune disease of the eye characterized by inflammation of the uvea and retina, degeneration of the retina, and blindness in genetically predisposed patients. Using the rat model of experimental autoimmune uveitis (EAU), we previously identified three quantitative trait loci (QTL) associated with EAU on rat chromosomes 4, 12, and 10 (Eau1, Eau2, and Eau3). The primary goal of the current study is to delineate additional non-MHC chromosomal regions that control susceptibility to EAU, and to identify any QTLs that overlap with the QTLs of other autoimmune diseases. Using a set of informative microsatellite markers and F(2) generations of resistant and susceptible MHC class II-matched rat strains (F344 and LEW), we have identified several new significant or suggestive QTLs on rat chromosomes 2, 3, 7, 10, and 19 that control susceptibility to EAU. A protective allele was identified in the susceptible LEW strain in the Eau5 locus at D7Wox18, and epistatic interactions between QTLs were found to influence the severity of disease. The newly identified regions (Eau4 through Eau9) colocalize with the genetic determinants of other autoimmune disease models, and to disease-regulating syntenic regions identified in autoimmune patients on human chromosomes 4q21-31, 5q31-33, 16q22-24, 17p11-q12, 20q11-13, and 22q12-13. Our results suggest that uveitis shares some of the pathogenic mechanisms associated with other autoimmune diseases, and lends support to the "common gene, common pathway" hypothesis for autoimmune disorders.     

A genome scan for Loci associated with aerobic running capacity in rats

Aerobic capacity is a complex trait that defines the efficiency to use atmospheric oxygen as an electron acceptor in energy transfer. Copenhagen (COP) and DA inbred rat strains show a wide difference in a test for aerobic treadmill running and serve as contrasting genetic models for aerobic capacity. A genome scan was carried out on an F(2)(COP x DA) segregating population (n=224) to detect quantitative trait loci (QTLs) associated with aerobic running capacity. Linkage analysis revealed a significant QTL on chromosome 16 (lod score, 4.0). A suggestive linkage was found near the p-terminus of chromosome 3 (lod score, 2.2) with evidence of an interaction with another QTL on chromosome 16 (lod score, 2.9). All three QTLs showed a dominant mode of inheritance in which the presence of at least one DA allele was associated with a greater distance run. These results represent the first aerobic capacity QTLs identified in genetic models.     

Linkage and association of phospholipid transfer protein activity to LASS4

Phospholipid transfer protein activity (PLTPa) is associated with insulin levels and has been implicated in atherosclerotic disease in both mice and humans. Variation at the PLTP structural locus on chromosome 20 explains some, but not all, heritable variation in PLTPa. In order to detect quantitative trait loci (QTLs) elsewhere in the genome that affect PLTPa, we performed both oligogenic and single QTL linkage analysis on four large families (n = 227 with phenotype, n = 330 with genotype, n = 462 total), ascertained for familial combined hyperlipidemia. We detected evidence of linkage between PLTPa and chromosome 19p (lod = 3.2) for a single family and chromosome 2q (lod = 2.8) for all families. Inclusion of additional marker and exome sequence data in the analysis refined the linkage signal on chromosome 19 and implicated coding variation in LASS4, a gene regulated by leptin that is involved in ceramide synthesis. Association between PLTPa and LASS4 variation was replicated in the other three families (P = 0.02), adjusting for pedigree structure. To our knowledge, this is the first example for which exome data was used in families to identify a complex QTL that is not the structural locus.     

The genetic basis of flowering time and photoperiod sensitivity in rapeseed <Emphasis Type="Italic">Brassica napus</Emphasis> L.

The objective of this study was to dissect the genetic control of days to flowering (DTF) and photoperiod sensitivity (PS) into the various components including the main-effect quantitative trait loci (QTLs), epistatic QTLs and QTL-by-environment interactions (QEs). Doubled haploid (DH) lines were produced from an F₁ between two spring Brassica napus cultivars Hyola 401 and Q2. DTF of the DH lines and parents were investigated in two locations, one location with a short and the other with a long photoperiod regime over two years. PS was calculated by the delay in DTF under long day as compared to that under short day. A genetic linkage map was constructed that comprised 248 marker loci including SSR, SRAP, and AFLP markers. Further QTL analysis resolved the genetic components of flowering time and PS into the main-effect QTLs, epistatic QTLs, and QEs. A total of 7 main-effect QTLs and 11 digenic interactions involving 21 loci located on 13 out of the 19 linkage groups were detected for the two traits. Three main-effect QTLs and four pairs of epistatic QTLs were involved in QEs conferring DTF. One QTL on linkage group (LG) 18 was revealed to simultaneously affect DTF and PS and explain for the highest percentage of the phenotypic variation. The implications of the results for B. napus breeding have been discussed. The text was submitted by the authors in English.     

Genome-wide linkage scan reveals multiple susceptibility loci influencing lipid and lipoprotein levels in the Quebec Family Study

A genome-wide linkage study was performed to identify chromosomal regions harboring genes influencing lipid and lipoprotein levels. Linkage analyses were conducted for four quantitative lipoprotein/lipid traits, i.e., total cholesterol, triglyceride, HDL-cholesterol (HDL-C), and LDL-C concentrations, in 930 subjects enrolled in the Québec Family Study. A maximum of 534 pairs of siblings from 292 nuclear families were available. Linkage was tested using both allele-sharing and variance-component linkage methods. The strongest evidence of linkage was found on chromosome 12q14.1 at marker D12S334 for HDL-C, with a logarithm of the odds (LOD) score of 4.06. Chromosomal regions harboring quantitative trait loci (QTLs) for LDL-C included 1q43 (LOD = 2.50), 11q23.2 (LOD = 3.22), 15q26.1 (LOD = 3.11), and 19q13.32 (LOD = 3.59). In the case of triglycerides, three markers located on 2p14, 11p13, and 11q24.1 provided suggestive evidence of linkage (LOD > 1.75). Tests for total cholesterol levels yielded significant evidence of linkage at 15q26.1 and 18q22.3 with the allele-sharing linkage method, but the results were nonsignificant with the variance-component method. In conclusion, this genome scan provides evidence for several QTLs influencing lipid and lipoprotein levels. Promising candidate genes were located in the vicinity of the genomic regions showing evidence of linkage.     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai’an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTL×environment interactions (QEs). Two major QTLs, Qph4B and Qph4D, which accounted for 14.51% and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rht1 and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL effects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

Meta-analysis of genome-wide linkage studies in BMI and obesity

Objective: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI‐defined obesity using a nonparametric genome scan meta‐analysis. Research Methods and Procedures: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome‐wide logarithm of the odds (LOD) scores, non‐parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI‐defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. Results: Bins at chromosome 13q13.2‐ q33.1, 12q23‐q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3‐22.3 were also observed for BMI‐defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1‐qter and 12p11.21‐q23 (p < 0.01). Conclusion: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.     

Genetic architecture of adiposity and organ weight using combined generation QTL analysis

We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.     

A quantitative trait locus for body fat on chromosome 1q43 in French Canadians: linkage and association studies

Objective: To explore a quantitative trait locus (QTL) on human chromosome 1q affecting BMI, adiposity, and fat‐free mass phenotypes in the Quebec Family Study cohort. Research Methods and Procedures: Non‐parametric sibpair and variance component linkage analyses and family‐based association studies were performed with a dense set of chromosome 1q43 microsatellites and single‐nucleotide polymorphism markers in 885 adult individuals. Results: Linkage was observed between marker D1S184 and BMI (p = 0.0004) and with body fat mass or percentage body fat (p ≤ 0.0003), but no linkage was detected with fat‐free mass. Furthermore, significant linkages (p < 0.0001) were achieved with subsamples of sibpairs at both ends of phenotype distributions. Association studies with quantitative transmission disequilibrium tests refined the linkage to a region overlapping the regulator of G‐protein signaling 7 (RGS7) gene and extending to immediate upstream gene loci. Discussion: The present study indicates that the QTL on chromosome 1q43 specifically affects total adiposity and provides a genetic mapping framework for the dissection of this adiposity locus.     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai'an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTLxenvironment interactions (QEs). Two major QTLs, QphAB and Qph4D, which accounted for 14.51 % and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rhtl and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL ef fects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

Linkage of prostate cancer susceptibility loci to chromosome 1

Three prostate cancer susceptibility genes have been reported to be linked to different regions on chromosome 1: HPC1 at 1q24-25, PCAP at 1q42-43, and CAPB at 1p36. Replication studies analyzing each of these regions have yielded inconsistent results. To evaluate linkage across this chromosome systematically, we performed multipoint linkage analyses with 50 microsatellite markers spanning chromosome 1 in 159 hereditary prostate cancer families (HPC), including 79 families analyzed in the original report describing HPC1 linkage. The highest lod scores for the complete dataset of 159 families were observed at 1q24-25 at which the parametric lod score assuming heterogeneity (hlod) was 2.54 (P=0.0006) with an allele sharing lod of 2.34 (P=0.001) at marker D1S413, although only weak evidence was observed in the 80 families not previously analyzed for this region (hlod=0.44, P=0.14, and allele sharing lod=0.67, P=0.08). In the complete data set, the evidence for linkage across this region was very broad, with allele sharing lod scores greater than 0.5 extending approximately 100 cM from 1p13 to 1q32, possibly indicating the presence of multiple susceptibility genes. Elsewhere on chromosome 1, some evidence of linkage was observed at 1q42-43, with a peak allele sharing lod of 0.56 (P=0.11) and hlod of 0.24 (P=0.25) at D1S235. For analysis of the CAPB locus at 1p36, we focused on six HPC families in our collection with a history of primary brain cancer; four of these families had positive linkage results at 1p36, with a peak allele sharing lod of 0.61 (P=0.09) and hlod of 0.39 (P=0.16) at D1S407 in all six families. These results are consistent with the heterogeneous nature of hereditary prostate cancer, and the existence of multiple loci on chromosome 1 for this disease.