Human Molecular Genetics

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (44) Request Permissions Google Scholar Articles by Neuhausen, S. L. Articles by Cannon-Albright, L. A. Search for Related Content PubMed PubMed Citation Articles by Neuhausen, S. L. Articles by Cannon-Albright, L. A. Social Bookmarking          What's this?

Human Molecular Genetics

Pages 2437-2442

©1999 Oxford University Press

---

Prostate cancer susceptibility locus HPC1 in Utah high-risk pedigrees
Introduction
Results
Discussion
Materials And Methods
   Ascertainment of pedigrees
   Genotyping
   Linkage analysis
Acknowledgements
References

---

Prostate cancer susceptibility locus HPC1 in Utah high-risk pedigrees

Susan L. Neuhausen¹, James M. Farnham¹, Edward Kort², Sean V. Tavtigian³, Mark H. Skolnick^{1, 3}, Lisa A. Cannon-Albright^{1, 2, +}

¹Department of Medical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA, ²Genetic Research, Intermountain Health Care, Salt Lake City, UT, USA and ³Myriad Genetics, Inc., Salt Lake City, UT, USA

Received July 14, 1999; Revised and Accepted September 27, 1999

A prostate cancer susceptibility locus (HPC1) at 1q24-25 has been identified. Subsequent analysis showed that the majority of the evidence for localization was provided by families with relatively young (<65 years) average age at diagnosis. We examined evidence for linkage to this region in a set of 41 extended multi-case prostate cancer pedigrees containing 440 prostate cancer cases. Genotyping of five short tandem repeat markers in the region was performed on DNA from 1724 individuals, including 284 prostate cancer cases. In comparison with the families reported in the initial localization, the Utah pedigrees are generally much larger (average of 10.7 versus 5.1 cases) and have an older average age at diagnosis (69 versus 65 years). Two- and three-point linkage analyses were conducted using a previously reported model and provided replication for HPC1 (two-point: LOD = 1.73, P = 0.005 at D1S196; three-point: LOD = 2.06, P = 0.002 for the interval D1S196-D1S416). The youngest quartile (by median age at diagnosis) yielded a maximum LOD of 2.82, P = 0.0003 (at D1S215-D1S222), compared with a maximum LOD of 0.73, P = 0.07 for the oldest quartile pedigrees at the same locus. Further analysis with an age-dependent model, specifying higher sporadic rates for older cases, suggests that the linkage evidence may be lower than expected given the power of the resource due to a high sporadic rate in the large Utah pedigrees.

INTRODUCTION

Prostate cancer is a pervasive disease in the USA, with an estimated 184 500 cases diagnosed in 1998 (1). It is the most commonly diagnosed cancer in men in the USA and the second most common cause of cancer mortality, with an estimated 39 200 deaths in 1998 (1). Approximately one in five men will be diagnosed with prostate cancer over the course of his lifetime. The risk of prostate cancer is greatly increased after age 65 years, with 80% of the cases diagnosed in men after this age. Risk factors for prostate cancer include age, ethnicity, country of origin and family history (2).

Woolf (3) described a relative risk of 3.0 of developing prostate cancer among first-degree relatives of prostate cancer cases in Utah using death certificate data. More recently, relative risks ranging from 3 to 11 for first-degree relatives of prostate cancer cases have been reported (4-9). Relative risks rise markedly with decreasing age of the index case (10,11) and with increasing number of prostate cancer cases within the family (12).

The familiality of prostate cancer cases in the Utah population has been well studied. When the familiality of major cancer sites was reviewed, prostate cancer was one of the most familial of the common cancers, ranking above both breast and colon cancers (4,10). An excess of both close and distant relationships was observed, suggesting that not only shared environmental factors, but a genetic predisposition may contribute to prostate cancer incidence in these pedigrees.

Carter et al. (12) performed segregation analysis on Caucasian families ascertained through a single prostate cancer proband. The analysis suggested Mendelian inheritance in a subset of families through autosomal dominant inheritance of a rare (q = 0.003), high-risk allele with estimated cumulative risk of prostate cancer for carriers of 88% by age 85 years. Inherited prostate cancer susceptibility accounted for a significant proportion of early-onset disease, and overall was responsible for 9% of prostate occurrence by age 85 years. Schaid et al. (13) replicated those results and, in addition, concluded that because the parameter estimates varied across the different age groups, genetic heterogeneity is present. In segregation analysis of a Swedish population-based sample of families (14), the clustering of prostate cancer was also explained by a dominant model, but with allele frequency of 0.0167 and lifetime penetrance of 63%. The strong evidence for a familial effect on risk of prostate cancer, coupled with the evidence for Mendelian segregation, has long suggested that inherited susceptibilities play a role in the etiology of the disease.

Smith et al. (15) reported the first localization of a putative prostate cancer susceptibility gene, HPC1, to chromosome 1q24-25. They examined 91 families with an average number of 4.9 prostate cancer cases per family and an average age at diagnosis of 65 years. Accounting for genetic heterogeneity, they reported a maximum multipoint LOD score of 5.43, P = 0.00000059 and estimated that one-third of their families were linked to the region. In a further analysis, Grönberg et al. (16) reported that the evidence for linkage was primarily from families with at least five prostate cancer cases and an early average age at diagnosis.

Four replication studies have been published, with mixed results. Lander and Kruglyak (17) have recommended a P < 0.000049 (LOD > 3.3) to declare significant linkage initially, and a P < 0.01 for replication of significant linkage. This threshold is reasonable for replication of significant linkage because it reflects a nominal P-value of 0.05 with correction for a modest number of multiple tests (~5). Two replication studies, by McIndoe et al. (18) and Eeles et al. (19), found negative overall evidence for linkage. On the other hand, Cooney et al. (20) and Hsieh et al. (21) provided supportive evidence (P-values between 0.03 and 0.045), but did not exceed the threshold recommended by Lander and Kruglyak (17) and, thus, did not replicate the linkage at HPC1.

We present an examination of linkage to 1q24-25 in a set of 41 high-risk prostate cancer pedigrees from Utah that were ascertained on the basis of familial clustering of the disease.

RESULTS

We examined evidence for linkage to HPC1 in 41 informative high-risk prostate cancer pedigrees using five short tandem repeat (STR) markers in the 1q24-25 region examined by Smith et al. (15) (Table 1). Results from analyses employing the model used by Smith et al. (15) and an age-dependent model were similar. LOD scores for both models are shown in Tables 2-4. Two-point LOD scores for the 41 pedigrees replicated the HPC1 localization. The maximum LOD was 1.73, P = 0.005 (Smith) and 1.92, P = 0.003 (Age) at D1S196 (Table 2). Ott's admixture test (22) was unable to detect heterogeneity, so the proportion of linked pedigrees (alpha) could not be estimated. A series of three-point analyses produced a maximum LOD of 2.06, P = 0.002 (Smith) and 2.43, P = 0.0008 (Age) at D1S196-D1S416, providing stronger evidence for replication of linkage (Table 2). Again, the admixture test failed to distinguish linked and unlinked pedigrees.

Table 1. Map order and distance of markers at 1q24-25

Markers used in analysis	Markers used by Smith et al. (15)	Marshfield map location (35)
D1S196		181.49
	D1S452	188.85
D1S416		192.76
	D1S212	193.76
D1S215		194.98
	D1S2883	194.98
D1S222		201.58
	D1S158	N/A
D1S422	D1S422	205.4

N/A, not available.

Table 2. LOD scores ([theta]) for two- and three-point linkage analysis for all 41 pedigrees

	Smith model		Age model
	Two-point	Three-point	Two-point	Three-point
D1S196	1.73 (0.20)		1.92 (0.20)
		2.06 (0.30)		2.43 (0.20)
D1S416	1.05 (0.30)		1.20 (0.20)
		0.39 (0.30)		0.40 (0.30)
D1S215	0.69 (0.30)		0.83 (0.30)
a		1.50 (0.30)		1.59 (0.30)
D1S222	1.07 (0.20)		1.54 (0.20)
b		0.58 (0.40)		0.76 (0.30)
D1S422	0.21 (0.40)		0.00 (0.50)

Position of maximum ^atwo-point and ^bmultipoint LOD in Smith et al. (15).

Table 3. Two-point LOD score ([theta]) comparison of pedigrees with early versus late median age at diagnosis

	Smith model		Age model
	Youngest quartile	Oldest quartile	Youngest quartile	Oldest quartile
D1S196	0.03 (0.30)	0.16 (0.30)	0.12 (0.30)	0.18 (0.30)
D1S416	0.02 (0.30)	0.00 (0.50)	0.21 (0.20)	0.18 (0.30)
D1S215	0.42 (0.20)	0.35 (0.30)	0.63 (0.10)	0.21 (0.30)
a
D1S222	2.44 (0.10)	0.11 (0.40)	1.94 (0.00)	0.27 (0.30)
D1S422	0.43 (0.20)	0.04 (0.40)	0.56 (0.10)	0.00 (0.50)

^aPosition of maximum two-point LOD in Smith et al. (15).

Table 4. Three-point LOD score ([theta]) comparison of pedigrees with early versus late median age at diagnosis

	Smith model		Age model
	Youngest quartile	Oldest quartile	Youngest quartile	Oldest quartile
D1S196
	0.17 (-0.30)	0.09 (+0.40)	0.43 (+0.20)	0.20 (+0.30)
D1S416
	0.11 (+0.40)	0.11 (+0.30)	0.15 (+0.30)	0.25 (+0.30)
D1S215
	2.82 (+0.10)	0.73 (-0.30)	2.59 (+0.00)	0.49 (-0.30)
D1S222
*	1.91 (-0.20)	0.21 (-0.40)	1.87 (-0.00)	0.26 (-0.30)
D1S422

*Position of maximum multipoint LOD in Smith et al. (15).
-, [theta] values to the left of the pair of markers; +, [theta] values to the right.

In order to investigate the finding of Grönberg et al. (16) that HPC1 is associated most strongly with prostate cancer diagnosed at an early age, the 41 pedigrees were divided into quartiles by ascending median age at diagnosis for all prostate cancer cases (Table 5), and LOD scores for the youngest and oldest quartiles were calculated (Table 3). Two-point LOD scores were higher in the youngest group (n = 9) than the oldest group (n = 10) for all but D1S196, and were much higher for D1S222 [LOD = 2.44, P = 0.0008 (Smith), LOD = 1.94, P = 0.003 (Age) versus LOD = 0.11, P = 0.48 (Smith), LOD = 0.27, P = 0.27 (Age)]. Marker D1S222 is positioned very close to the multipoint peak of LOD published by Smith et al. (15). Three-point LOD scores also were generally higher for the youngest group (Table 4), with a maximum LOD of 2.82, P = 0.0003 (Smith) and 2.59, P = 0.0006 (Age) at D1S215-D1S222, and 1.91, P = 0.003 (Smith) and 1.87, P = 0.003 (Age) at D1S222-D1S422.

Table 5. Characteristics of prostate cancer pedigrees

Group	No. of pedigrees	Mean no. of total cases (range)	Mean no. of genotyped cases (range)	Mean median age (in years) at Dx (range)	Mean age (in years) at Dx (range)	Age (in years) of cases	Mean ELOD +1 STD (range)
Youngest 25%	9	6.9	4.0	64.5	65.5	41-88	0.6
		(4-11)	(3-8)	(62.0-65.8)	(61.3-68.5)		(0.4-0.8)
Middle 50%	22	10.7	5.5	69.2	69.5	43-89	1.1
		(5-22)	(1-19)	(67.0-72.0)	(66.6-72.9)		(0.4-2.1)
Oldest 25%	10	14.2	7.3	73.7	71.2	35-88	1.1
		(6-26)	(3-15)	(73.0-77.0)	(65.2-73.9)		(0.4-2.4)

DISCUSSION

Smith et al. (15) presented evidence for a major prostate cancer susceptibility locus on chromosome 1, suggesting that it may explain as much as one-third of familial prostate cancer. We have investigated this hypothesis in a set of extended, high-risk prostate cancer pedigrees collected in Utah over the past 9 years. We report the first replication of linkage to HPC1 with both two- and three-point analyses, and provide stronger evidence among our younger age at diagnosis pedigrees. Although the highest LOD scores in the overall analyses were obtained with markers located some 15 cM proximal to the most likely locus reported by Smith et al. (15), the LOD score maximized at a recombination fraction of 0.30 (Smith) and 0.20 (Age), indicating linkage to a disease gene at some genetic distance away. Stronger linkage evidence is provided by the two- and three-point LOD scores of youngest quartile kindreds, maximizing close to the position indicated by Smith et al. (15).

Although the LOD scores resulting from our analyses are adequate to replicate linkage to HPC1 at 1q24-25 as a familial prostate cancer locus, they fail the LOD >3.0 or 3.3 criterion traditionally used to support a new localization. We estimated the power of our resource to detect linkage by calculating expected LOD scores (ELODs) and found that several pedigrees are able, by themselves, to generate LOD scores >2.0 under the condition of no model misspecification. We hypothesize that the lower than might be expected HPC1 evidence, given the power of the resource, is due to several factors related to model misspecification.

Some pedigrees in our resource may, in fact, be linked to HPC1, but we are unable to detect linkage in them due to non-HPC1 cases not accounted for by the genetic model. Because prostate cancer is a common disease and these kindreds were selected for an excess of prostate cancer, non-genetic and non-HPC1 cases are more likely to be observed in these large kindreds. The presence of sporadic (non-carrier) cases in a linked kindred results in suppressed LOD scores for that family, as well as LOD scores maximizing at different [theta] values in different pedigrees, resulting in lower LOD scores overall. This intra-familial heterogeneity is not detectable by the admixture test, which can only address inter-familial hetero-geneity.

This model misspecification hypothesis is supported by two observations. First, LOD scores in nearly all analyses maximized at large [theta] values for two-point analyses and outside the pairs of markers for three-point analyses. Second, LOD scores using the Age model generally maximized at [theta] values closer to 0.0 than the Smith model (Tables 2-4). The Age model specifies higher sporadic rates than the Smith model, in particular for prostate cancer cases diagnosed at older ages, suggesting that sporadics are modeled more appropriately by the Age model. On the other hand, the LOD scores under the Age model are not always larger than LOD scores under the Smith model, indicating that although sporadics may be accounted for better in the Age model, the power to detect linkage is decreased.

Some research groups have had only marginal success in replicating the HPC1 locus (20,21). Other groups observed negative evidence for linkage (18,19). It is unclear whether these mixed results (Table 6) are due to HPC1 accounting for a much smaller proportion of prostate cancer than Smith et al.'s (15) estimate of 35%, or due to the inability to identify sporadics or model them appropriately. This is especially true given that locus or allelic heterogeneity has an effect on LOD scores similar to that of genuine sporadics. The estimate of the true proportion of families with prostate cancer due to HPC1 will require cloning of the gene and identification of mutations within the families.

Table 6. A comparison of family size, age at diagnosis and linkage evidence for published HPC1 studies

Group	No. of pedigrees studied	Average no. of cases (range)	Best linkage statistic	Best P-value
Smith et al.	91	4.9 (3-15)	HETLOD = 5.43	0.0000006
McIndoe et al.	49	4.4 (3-9)	LOD = 1.09	0.29
Eeles et al.	136	<3 (NA)	NPL = 0.72	0.22
Cooney et al.	59	3.1 (2-15)	NPL = 1.58	0.057
HPC1 criteria	20	4.4 (3-15)	NPL = 1.72	0.045
Hsieh et al.	92	2.6 (2-6)	NPL = 1.90	0.030
Present study	41	10.7 (4-26)	LOD = 2.43	0.0008
young pedigrees	9	6.9 (4-11)	LOD = 2.82	0.0003

Grönberg et al. (16) suggest that families with a younger age at diagnosis and with a higher density of cases are more likely to be linked to HPC1. In the four previous replication studies, regardless of the overall evidence of linkage, when the data sets were stratified and analyzed, families with either a larger number of cases or an earlier age at diagnosis produced better evidence for linkage than did pedigrees with older average age at diagnosis or with fewer cases. However, even with stratification, they were unable to replicate the HPC1 localization (Table 6). In large Utah pedigrees, we were able to replicate the HPC1 localization and to replicate the finding that stronger evidence is found in those pedigrees with younger ages at diagnosis (Table 6).

Other prostate cancer susceptibility loci probably exist and may be responsible for a higher proportion of older age at diagnosis familial prostate cancer. Three prostate cancer linkages have been published at 1q42-43 (23), Xq24 (24) and 1p36 (25), suggesting three additional prostate cancer susceptibility genes. Analyses of these loci are underway. Most of the Utah pedigrees with the greatest power to detect linkage showed little to no evidence of HPC1 linkage and are being tested for linkage to these other putative loci. These pedigrees will provide an excellent resource for the replication of these localizations and possible new linkages as well.

MATERIALS AND METHODS

Ascertainment of pedigrees

High-risk prostate cancer pedigrees were ascertained from the Utah Population Database, which combines about eight generations of genealogical data from Utah pioneers and their descendants, and ~30 years of complete cancer registration for the state of Utah (26,27). All of the Utah pedigrees studied represent the descendants of a single founder for whom a significant excess of prostate cancer cases was observed among all descendants. A total of 3502 such independent clusters of prostate cancer have been identified, ranging in size from two to 62 prostate cancer cases per cluster. In 1990, we began collecting blood samples in 298 of these clusters. Because these clusters are defined only by an excess of prostate cancer, there is no bias towards early age at diagnosis or number of affected first-degree relatives. Furthermore, because all affected descendants are studied, the resulting pedigrees represent a collection of both closely and distantly related prostate cancer cases.

Genotyping for the set of markers at 1q24-25 has been completed in 54 pedigrees. A subset of these 54 pedigrees was selected for inclusion in linkage analysis based on power to detect linkage as evidenced by ELOD. For each family, a single marker was simulated for genotyped individuals. An age-dependent model (Table 7) with a rare disease allele (frequency = 0.003), a marker with six equally frequent alleles and a penetrance function dependent on age and affection status was used for simulation. The disease-marker linkage was simulated with [theta] = 0.05. This model was also used for analysis of the simulated data. The software programs SLINK and MSIM (28) were used for simulation and analysis, respectively. The minimum criterion for inclusion of a family for linkage analysis was that the average ELOD + 1 SD was >0.3. This metric ranged from 0.31 to 2.42 for the selected pedigrees. Maximum ELOD values ranged from 0.40 to 3.66.

Table 7. Penetrance^a values used in linkage analyses

Age (years)	Smith model			Age model
	dd	Dd	DDb	dd	Dd	DD
Unaffected penetrance
<25	0.01	0.01	0.01	0.00001	0.00025	0.00025
25-34	0.01	0.01	0.01	0.00001	0.00037	0.00037
35-44	0.01	0.01	0.01	0.00002	0.00037	0.00037
45-54	0.01	0.01	0.01	0.00028	0.00698	0.00698
55-64	0.01	0.01	0.01	0.00374	0.08938	0.08938
65-74	0.01	0.01	0.01	0.02138	0.41740	0.41740
75-84	0.16	0.63	0.63	0.05823	0.77684	0.77684
85+	0.16	0.63	0.63	0.10137	0.93090	0.93090
Affected penetrance
<25	0.0005	0.50	0.50	0.00000	0.00000	0.00000
25-34	0.0005	0.50	0.50	0.00000	0.00012	0.00012
35-44	0.0005	0.50	0.50	0.00006	0.00162	0.00162
45-54	0.0005	0.50	0.50	0.00096	0.02408	0.02408
55-64	0.0005	0.50	0.50	0.00872	0.19920	0.19920
65-74	0.0005	0.50	0.50	0.02840	0.42275	0.42275
75-84	0.0005	0.50	0.50	0.04231	0.25066	0.25066
85+	0.0005	0.50	0.50	0.04158	0.07993	0.07993

^aFemales were in the youngest unaffected penetrance class in both models.
^bD, disease susceptibility-conferring allele for prostate cancer; d, normal allele. Frequency of D allele = 0.003.

The 41 Utah pedigrees that met this criterion are typical of the larger set of Utah pedigrees studied. They are 3-7 generations deep and contain between four and 26 prostate cancer cases in the branches of the pedigrees that were genotyped (Table 5). All are Caucasian of Northern European ancestry. The median age at diagnosis for each family ranged from 62 to 77 years, with an average median of ~69 years, similar to that estimated for the general Utah population. The mean age at diagnosis of prostate cancer in these pedigrees is generally older (69.0 versus 64.9 years) than the resource studied by Smith et al. (15). Only 29 prostate cancer cases (4.5%) were diagnosed before age 55 years in the 41 pedigrees.

All participants signed informed consent documents. This research project has the approval of the University of Utah School of Medicine Institutional Review Board. Blood samples were gathered from all available males with prostate cancer and all of their available connecting ancestors. Ninety-seven percent of cancer cases have been confirmed through medical record (and/or through the Utah Cancer Registry for prostate cancer cases diagnosed in Utah). Where prostate cancer cases were deceased, spouse and offspring were sampled to infer the genotype of the case. Because parents of cases were seldom available, multiple siblings or a single offspring were sampled to improve phase inference.

Genotyping

Nuclear pellets were extracted from 16 ml of blood, and DNA extracted with phenol and chloroform, precipitated with ethanol and resuspended in Tris-EDTA. PCR amplification was performed with fluorescently labeled primers. Sizing of the PCR products was performed on the automated ABI377 (Applied Biosystems, Foster City, CA), using modifications of the programs GENESCAN and GENOTYPER. Size standards were included in every lane, and one common control individual was included on each gel.

The markers used for genotyping were STR loci at 1q24-25 that flanked the most likely HPC1 location as indicated in Smith et al. (15). The markers included in our analyses were selected for completeness of genotyping and informativeness and are, for the most part, different from those utilized by Smith et al. (15). A map containing both sets of markers is presented in Table 1.

Linkage analysis

Two-point linkage analysis was performed with the package LINKAGE (29) using the FASTLINK implementation (30,31). The statistical analysis for the inheritance of susceptibility to prostate cancer used a model, referred to here as the Smith model (15), that assumes a phenocopy rate of 15%, regardless of age, and treats unaffected men under the age of 75 years, as well as women, as having unknown phenotype. In men over age 75 years, the lifetime penetrance of gene carriers according to this model is 63%. A second model, referred to here as the Age model, was developed using age-specific incidence rates from the Utah Cancer Registry, assuming a relative risk of 2.5 for first-degree relatives. In both models, susceptibility to prostate cancer was assumed to be due to a dominant allele with a population frequency of 0.003. The Age model is thought to represent better the risk of prostate cancer in the Utah population. The liability classes for the two models are shown in Table 6. Females are classified in the lowest unaffected class. Marker allele frequencies were estimated from unrelated individuals present in the pedigrees.

Linkage in the presence of heterogeneity was assessed by the admixture test (A-test) of Ott (22), using HOMOG, which postulates two family types, linked and unlinked. Three-point linkage analysis was performed using VITESSE (32). The size of our pedigrees, as well as the number of individuals not genotyped in upper generations, made simultaneous analysis of more than two markers and the disease impossible. Non-parametric multipoint linkage analyses with GENEHUNTER (33) required such extensive reduction of the kindreds as to render the results uninformative.

It has been demonstrated that model misspecification in a multipoint context results in disease localization being `pushed outside' the set of markers analyzed (34). Therefore, a three-point analysis for each adjacent pair of markers was performed, rather than a `walking' three-point analysis that only calculates LOD scores in intervals between pairs of interior markers. This strategy allows for LOD scores to maximize outside all pairs of markers and improves the chance of finding evidence for linkage, even in the presence of model misspecification. Because the purpose of our analysis was to provide replication of the linkage, rather than to map the location of the HPC1 gene within the region, this strategy seemed appropriate.

ACKNOWLEDGEMENTS

We would like to thank Vicki Abtin, Michelle Anderson, Morgan Boyack, Chris Hansen, Maggie Higbee (deceased), Margo Jost, Lina Moses, Reed Nelson, Kim Nguyen, Tory Peterson, Linda Steele, Thao Tran and Anne Zeller for technical assistance. This work was supported by grants CA62154 and CA64477 from the National Institutes of Health, and by funding from Myriad Genetics, Inc. The research was also supported by the Utah Cancer Registry, which is funded by Contract no. N01-CN-6700 from the National Cancer Institute with additional support from the Utah Department of Health and the University of Utah.

REFERENCES

1. American Cancer Society (1998) Cancer Facts and Figures-1998. ACS, Atlanta, GA.

2. Pienta, K.J. and Esper, P.S. (1993) Risk factors for prostate cancer. Am. Coll. Phys., 118, 793-803.

3. Woolf, C.M. (1960) An investigation of the familial aspects of carcinoma of the prostate. Cancer, 13, 739-744.

4. Cannon, L., Bishop, D.T., Skolnick, M., Hunt, S., Lyon, J.L. and Smart, C.R. (1982) Genetic epidemiology of prostate cancer in the Utah Mormon genealogy. Cancer Surv., 1, 47-69.

5. Fincham, S.M., Hill, G.B., Hanson, J. and Wijayasinghe, C. (1990) Epidemiology of prostate cancer: a case control study. Prostate, 17, 189-206. MEDLINE Abstract

6. Meikle, A.W., Smith, A.J. and West, D.W. (1985) Familial factors affecting prostatic cancer risk and plasma sex-steroid levels. Prostate, 6, 121. MEDLINE Abstract

7. Krain, L.S. (1974) Some epidemiologic variables in prostatic cancer. Prev. Med., 3, 154-159. MEDLINE Abstract

8. Morganti, G., Gianferrari, L., Cresseri, A., Arrigona, G. and Lovati, G. (1956) Recherches clinico-statiques et genetiques sur les neoplasies de la prostate. Acta Genet. Med. Gemellol., 6, 304-305.

9. Goldgar, D.E., Easton, D.F., Cannon-Albright, L.A. and Skolnick, M.H. (1994) A systematic population-based assessment of cancer risk in first-degree relatives of cancer probands. J. Natl Cancer Inst., 86, 1600-1608. MEDLINE Abstract

10. Cannon-Albright, L.A., Thomas, A., Goldgar, D.E., Gholami, K., Rowe, K., Jacobsen, M., McWhorter, W.P. and Skolnick, M.H. (1994) Familiality of cancer in Utah. Cancer Res., 54, 2378-2385. MEDLINE Abstract

11. Steinberg, G.D., Carter, B.S., Beaty, T.H., Childs, B. and Walsh, P.C. (1990) Family history and the risk of prostate cancer. Prostate, 17, 337-347. MEDLINE Abstract

12. Carter, B.S., Beaty, T.H., Steinberg, G.D., Childs, B. and Walsh, P.C. (1992) Mendelian inheritance of familial prostate cancer. Proc. Natl Acad. Sci. USA, 89, 3367-3371. MEDLINE Abstract

13. Schaid, D.J., McDonnell, S.K., Blute, M.L. and Thibodeau, S.N. (1998) Evidence for autosomal dominant inheritance of prostate cancer. Am. J. Hum. Genet., 62, 1425-1438. MEDLINE Abstract

14. Grönberg, H., Isaacs, S.D., Smith J.R., Carpten, J.D., Bova, G.S., Freije, D., Xu, J., Meyers, D.A., Collins, F.S., Trent, J.M., Walsh, P.C. and Isaacs, W.B. (1997) Characteristics of prostate cancer in families potentially linked to the hereditary prostate cancer 1 (HPC1)locus. J. Am. Med. Assoc., 15, 1251-1255.

15. Smith, J.R., Freije, D., Carpten, J.D., Grönberg, H., Xu, J., Isaacs, S.D, Brownstein, J.F., Bova, G.S., Guo, H., Bujnovsky, P., Nusskern, D.R., Damber, J.M. and Isaacs, W.B. (1996) Major susceptibility locus for prostate cancer on chromosome 1 suggested by a genome-wide search. Science, 274, 1371. MEDLINE Abstract

16. Grönberg, H.K., Xu, J., Smith, J.R., Carpten, J.D., Isaacs, S.D, Freije, D., Bova, G.S., Walsh, P.C., Collins, F.S., Trent, J.M., Meyers, D.A. and Isaacs, W.B. (1997) Early age at diagnosis in families providing evidence of linkage to the hereditary prostate cancer locus (HPC1)on chromosome 1. Cancer Res., 57, 4707-4709. MEDLINE Abstract

17. Lander, E. and Kruglyak, L. (1995) Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nature Genet., 11, 241-247. MEDLINE Abstract

18. McIndoe, R.A., Stanford, J.L., Gibbs, M., Jarvik, G.P., Brandzel, S., Neal, C.L., Li, S., Gammack, J.T., Gay, A.A., Goode, E.L., Hood, L. and Ostrander, E.A. (1997) Linkage analysis of 49 high-risk families does not support a common familial prostate cancer-susceptibility gene at 1q24-25. Am. J. Hum. Genet., 61, 347-353. MEDLINE Abstract

19. Eeles, R.A., Durocher, F., Edwards, S., Teare, D., Badzioch, M., Hamoudi, R., Gill, S., Biggs, P., Dearnaley, D., Ardern-Jones, A., Dowe, A., Shearer, R., McLennan, D.L., Norman, R.L., Ghardirian, P., Aprikian, A., Ford, D., Amons, C., King, T.M. and The Cancer Research Campaign/British Prostate Group UK Familial Prostate Cancer Study Collaborators, Labrie, F., Simard, J., Narod, S.A., Easton, D. and Foulkes, W.D. (1998) Linkage analysis of chromosome 1q markers in 136 prostate cancer families. Am. J. Hum. Genet., 62, 653-658. MEDLINE Abstract

20. Cooney, K.A., McCarthy, J.D., Lange, E., Huang, L., Miesfeldt, S., Montie, J.E., Oesterling, J.E., Sandler, H.M. and Lange, K. (1997) Prostate cancer susceptibility locus on chromosome 1q: a confirmatory study. J. Natl Cancer Inst., 89, 955-959. MEDLINE Abstract

21. Hsieh, C.-L., Oakley-Girvan, I., Gallagher, R.P., Wu, A.H., Kolonel, L.N., The, C.-Z., Halpern, J., West, D.W., Paffenbarger, R.S. and Whittemore, A.S. (1997) Re: Prostate cancer susceptibility locus on chromosme 1q: a confirmatory study. J. Natl Cancer Inst., 89, 1893-1894. MEDLINE Abstract

22. Ott, J. (1986) Linkage probability and its approximate confidence interval under possible heterogeneity. Genet. Epidemiol., 1 (suppl.), 251-257.

23. Berthon, P., Valeri, A., Cohen-Akenine, A., Drelon, E., Paiss, T., Woohr, G., Latil, A., Millasseau, P., Mellah, I., Cohen, N., Blanche, H., Bellane-Chantelot, C., Demenais, F., Teillac, P., LeDuc, A., Petriconi, R., Hautmann, R., Chumakov, I., Bachner, L., Maitland, N.J., Lidereau, R., Vogel, W., Gournier, G., Mangin, P., Cohen, D. and Cussenot, O. (1998) Predisposing gene for early-onset prostate cancer, localized on chromosome 1q42.2-43. Am. J. Hum. Genet., 62, 1416-1424. MEDLINE Abstract

24. Xu, J., Meyers, D., Freije, D., Isaacs, S., Wiley, K., Nusskern, D., Ewing, C., Wilkens, E., Bujnovsky, P., Bova, G.S., Walsh, P., Isaacs, W., Schleutker, J., Matikainen, M., Tammela, M., Viosakorpi, T., Lallionieni, O., Berry, R., Schaid, D., French, A., McDonnell, S., Schroeder, J., Bluet, M., Thibodeau, S., Grönberg, H., Emanuelsson, M., Danber, J., Bergh, A., Jonsson, B., Smith, J., Bailey-Wilson, J., Carpten, J., Stephen, D., Gillanders, E., Amundson, I., Kainu, T., Freas-Lutz, D., Baffoe-Bonnie, A., Van Auken, A., Sood, R., Collins, F., Brounstein, M. and Trent, J. (1998) Evidence for a prostate cancer susceptibility locus on the X chromosome. Nature Genet., 20, 175-179. MEDLINE Abstract

25. Gibbs, M., Stanford, J.L., McIndoe, R.A., Jarvik, G.P., Kolb, S., Goode, E.L., Chakrabarti, L., Schuster, E.F., Buckley, V.A., Miller, E.L., Brandzel, S., Li, S., Hood, L. and Ostrander, E.A. (1999) Evidence for a rare prostate cancer-susceptibility locus at chromosome 1p36. Am. J. Hum. Genet., 64, 776-787. MEDLINE Abstract

26. Skolnick, M., Bean, L., Dintelman, S.M. and Mineau, G. (1979) A computerized family history data base system. Sociol. Soc. Res., 63, 506-523.

27. Skolnick, M. (1980) The Utah Genealogical database: a resource for genetic epidemiology. In Banbury Report 4: Cancer Incidence in Defined Populations.Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY.

28. Weeks, D.E. and Lathrop, G.M. (1990) SLINK: a general simulation program for linkage analysis. Am. J. Hum. Genet., 47, A204.

29. Lathrop, G.M., Lalouel, J.M, Julier, C. and Ott, J. (1984) Strategies for multilocus analysis in humans. Proc. Natl Acad. Sci. USA, 81, 3443-3446. MEDLINE Abstract

30. Cottingham, R.W., Idury, R.M. and Schaffer, A.A. (1993) Faster sequential genetic linkage computations. Am. J. Hum. Genet., 53, 252-260. MEDLINE Abstract

31. Schaffer, A.A., Gupta, S.K., Shriram, K. and Cottingham, R.W. (1994) Avoiding recomputation in linkage analysis. Hum. Hered., 44, 225-237. MEDLINE Abstract

32. O'Connell, J.R. and Weeks, D.E. (1995) The VITESSE algorithm for rapid exact multilocus linkage analysis via genotype set-recoding and fuzzy inheritance. Nature Genet., 11, 402-408. MEDLINE Abstract

33. Kruglyak, L., Daly, M.J., Reeve-Daly, M.P. and Lander, E.S. (1996) Parametric and nonparametric linkage analysis: a unified multipoint approach. Am. J. Hum. Genet., 58, 1347-1363. MEDLINE Abstract

34. Risch, N. and Giuffra, L. (1992) Model misspecification and multipoint linkage analysis. Hum. Hered., 42, 77-92. MEDLINE Abstract

35. Broman, K.W., Murray, J.C., Sheffield, V.C., White, R.L. and Weber, J.L. (1998) Comprehensive human genetic maps: individual and sex-specific variation in recombination. Am. J. Hum. Genet., 63, 861-689. MEDLINE Abstract

---

+To whom correspondence should be addressed at: Division of Genetic Epidemiology, 391 Chipeta Way, Suite D2, Salt Lake City, UT 84108, USA. Tel: +1 801 581 5070; Fax: +1 801 581 6052; Email: lisa{at}episun6.med.utah.edu

---

This page is run by Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, as part of the OUP Journals
Comments and feedback: jnl.info{at}oup.co.uk
Last modification:
Copyright© Oxford University Press, 1999.
CiteULike    Connotea    Del.icio.us    What's this?

This article has been cited by other articles:

				S. J. Shook, J. Beuten, K. C. Torkko, T. L. Johnson-Pais, D. A. Troyer, I. M. Thompson, and R. J. Leach Association of RNASEL Variants with Prostate Cancer Risk in Hispanic Caucasians and African Americans Clin. Cancer Res., October 1, 2007; 13(19): 5959 - 5964. [Abstract] [Full Text] [PDF]

				N. J. Camp, J. M. Farnham, and L. A. Cannon-Albright Localization of a Prostate Cancer Predisposition Gene to an 880-kb Region on Chromosome 22q12.3 in Utah High-Risk Pedigrees. Cancer Res., October 15, 2006; 66(20): 10205 - 10212. [Abstract] [Full Text] [PDF]

				F. Wiklund, B.-A. Jonsson, A. J. Brookes, L. Stromqvist, J. Adolfsson, M. Emanuelsson, H.-O. Adami, K. Augustsson-Balter, and H. Gronberg Genetic Analysis of the RNASEL Gene in Hereditary, Familial, and Sporadic Prostate Cancer Clin. Cancer Res., November 1, 2004; 10(21): 7150 - 7156. [Abstract] [Full Text] [PDF]

				D. J. Schaid The complex genetic epidemiology of prostate cancer Hum. Mol. Genet., April 1, 2004; 13(90001): R103 - 121. [Abstract] [Full Text] [PDF]

				D. M. Friedrichsen, J. L. Stanford, S. D. Isaacs, M. Janer, B.-l. Chang, K. Deutsch, E. Gillanders, S. Kolb, K. E. Wiley, M. D. Badzioch, et al. Identification of a prostate cancer susceptibility locus on chromosome 7q11-21 in Jewish families PNAS, February 17, 2004; 101(7): 1939 - 1944. [Abstract] [Full Text] [PDF]

				J. Simard, M. Dumont, P. Soucy, and F. Labrie Perspective: Prostate Cancer Susceptibility Genes Endocrinology, June 1, 2002; 143(6): 2029 - 2040. [Full Text] [PDF]

				V. Nwosu, J. Carpten, J. M. Trent, and R. Sheridan Heterogeneity of genetic alterations in prostate cancer: evidence of the complex nature of the disease Hum. Mol. Genet., October 1, 2001; 10(20): 2313 - 2318. [Abstract] [Full Text] [PDF]

				E. L. Goode, J. L. Stanford, M. A. Peters, M. Janer, M. Gibbs, S. Kolb, M. D. Badzioch, L. Hood, E. A. Ostrander, and G. P. Jarvik Clinical Characteristics of Prostate Cancer in an Analysis of Linkage to Four Putative Susceptibility Loci Clin. Cancer Res., September 1, 2001; 7(9): 2739 - 2749. [Abstract] [Full Text] [PDF]

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (44) Request Permissions Google Scholar Articles by Neuhausen, S. L. Articles by Cannon-Albright, L. A. Search for Related Content PubMed PubMed Citation Articles by Neuhausen, S. L. Articles by Cannon-Albright, L. A. Social Bookmarking          What's this?

Online ISSN 1460-2083 - Print ISSN 0964-6906

Copyright © 2009 Oxford University Press

Oxford Journals Oxford University Press

• Site Map
• Privacy Policy
• Frequently Asked Questions

Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan American National Biography Booksellers' Information Service Children's Fiction and Poetry Children's Reference Corporate & Special Sales Dictionaries Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks Humanities International Education Unit Law Medicine Music Online Products Oxford English Dictionary Reference Rights and Permissions Science School Books Social Sciences Very Short Introductions World's Classics