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Agnes Baffoe-Bonnie

Publications and source records attributed to Agnes Baffoe-Bonnie.

7 recordsLinked to original sources

Pooled genome linkage scan of aggressive prostate cancer: results from the International Consortium for Prostate Cancer Genetics.

While it is widely appreciated that prostate cancers vary substantially in their propensity to progress to a life-threatening stage, the molecular events responsible for this progression have not been identified. Understanding these molecular mechanisms could provide important prognostic information relevant to more effective clinical management of this heterogeneous cancer. Hence, through genetic linkage analyses, we examined the hypothesis that the tendency to develop aggressive prostate cancer may have an important genetic component. Starting with 1,233 familial prostate cancer families with genome scan data available from the International Consortium for Prostate Cancer Genetics, we selected those that had at least three members with the phenotype of clinically aggressive prostate cancer, as defined by either high tumor grade and/or stage, resulting in 166 pedigrees (13%). Genome-wide linkage data were then pooled to perform a combined linkage analysis for these families. Linkage signals reaching a suggestive level of significance were found on chromosomes 6p22.3 (LOD = 3.0), 11q14.1-14.3 (LOD = 2.4), and 20p11.21-q11.21 (LOD = 2.5). For chromosome 11, stronger evidence of linkage (LOD = 3.3) was observed among pedigrees with an average at diagnosis of 65 years or younger. Other chromosomes that showed evidence for heterogeneity in linkage across strata were chromosome 7, with the strongest linkage signal among pedigrees without male-to-male disease transmission (7q21.11, LOD = 4.1), and chromosome 21, with the strongest linkage signal among pedigrees that had African American ancestry (21q22.13-22.3; LOD = 3.2). Our findings suggest several regions that may contain genes which, when mutated, predispose men to develop a more aggressive prostate cancer phenotype. This provides a basis for attempts to identify these genes, with potential clinical utility for men with aggressive prostate cancer and their relatives.

Black or African American↗

Segregation analysis of urothelial cell carcinoma.

A family history of urothelial cell carcinoma (UCC) confers an almost two-fold increased risk of developing UCC. It is unknown whether (part of) this aggregation of UCC has a Mendelian background. We performed complex segregation analyses on 1193 families ascertained through a proband with UCC of the bladder, ureter, renal pelvis or urethra, who were newly diagnosed between January 1, 1995 and December 31, 1997 and registered by two population-based cancer registries in the southeastern part of the Netherlands. Data were reported on 10 738 first-degree relatives by postal questionnaire; 101 of these relatives had UCC. All reported occurrences of UCC were verified (if possible) using medical records. Analyses were performed with the S.A.G.E. segregation package. Five restricted models (Mendelian dominant, Mendelian recessive, Mendelian co-dominant, 'no major gene' model and environmental model) were tested against the general unrestricted model. Sex and smoking status were incorporated as covariates. Strong evidence of Mendelian inheritance of UCC through a single major gene was not found in these 1 193 families. However, since none of the Mendelian models could be rejected, an inherited subtype of UCC cannot be excluded. A major gene may segregate in some families but this effect may have been masked in a background of high sporadic incidence. The 'no major gene' (or sporadic) model appeared to be the most parsimonious one to describe the occurrence of UCC in these families.

Female↗

Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect.

Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P< or =0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.

Aged↗

A combined genomewide linkage scan of 1,233 families for prostate cancer-susceptibility genes conducted by the international consortium for prostate cancer genetics.

Evidence of the existence of major prostate cancer (PC)-susceptibility genes has been provided by multiple segregation analyses. Although genomewide screens have been performed in over a dozen independent studies, few chromosomal regions have been consistently identified as regions of interest. One of the major difficulties is genetic heterogeneity, possibly due to multiple, incompletely penetrant PC-susceptibility genes. In this study, we explored two approaches to overcome this difficulty, in an analysis of a large number of families with PC in the International Consortium for Prostate Cancer Genetics (ICPCG). One approach was to combine linkage data from a total of 1,233 families to increase the statistical power for detecting linkage. Using parametric (dominant and recessive) and nonparametric analyses, we identified five regions with "suggestive" linkage (LOD score >1.86): 5q12, 8p21, 15q11, 17q21, and 22q12. The second approach was to focus on subsets of families that are more likely to segregate highly penetrant mutations, including families with large numbers of affected individuals or early age at diagnosis. Stronger evidence of linkage in several regions was identified, including a "significant" linkage at 22q12, with a LOD score of 3.57, and five suggestive linkages (1q25, 8q13, 13q14, 16p13, and 17q21) in 269 families with at least five affected members. In addition, four additional suggestive linkages (3p24, 5q35, 11q22, and Xq12) were found in 606 families with mean age at diagnosis of < or = 65 years. Although it is difficult to determine the true statistical significance of these findings, a conservative interpretation of these results would be that if major PC-susceptibility genes do exist, they are most likely located in the regions generating suggestive or significant linkage signals in this large study.

Aged↗

Combined genome-wide scan for prostate cancer susceptibility genes.

BACKGROUND: Prostate cancer represents a substantial public health burden worldwide. It is the second leading cause of cancer death among men in the United States. A family history of the disease is among the most well-established risk factors for prostate cancer. Efforts to localize prostate cancer susceptibility alleles by using genetic linkage analysis methods have been hindered by genetic heterogeneity, incomplete penetrance, disease phenocopies, and the lack of DNA samples from parents of individuals with late-onset prostate cancer. METHODS: We performed a combined genome-wide linkage analysis among 426 families from four existing hereditary prostate cancer (HPC) study populations to systematically search for prostate cancer susceptibility genes. To decrease the degree of locus heterogeneity, we analyzed subsets of families with similar clinical and demographic characteristics. Nonparametric multipoint linkage was the primary method of analysis. Results are presented as allele-sharing logarithm of the odds (LOD) scores, and all reported P values are two-sided. RESULTS: The strongest evidence for prostate cancer linkage was found at chromosome region 17q22 (nonparametric multipoint Kong and Cox allele-sharing LOD score = 3.16 at marker D17S787; P =.00007). Stratified analyses revealed several additional chromosomal regions that are likely to segregate prostate cancer susceptibility genes among specific subsets of HPC families, including 15q11 among families with late-onset disease (allele-sharing LOD = 5.57 at marker D15S128; P<.00001) and 4q35 among families with four or more affected family members (allele-sharing LOD = 3.10 at marker D4S1615; P =.00008). CONCLUSION: Fine mapping studies to facilitate identification of prostate cancer susceptibility genes in these linked regions are warranted.

Biomarkers, Tumor↗

Importance sampling method of correction for multiple testing in affected sib-pair linkage analysis.

Using the Genetic Analysis Workshop 13 simulated data set, we compared the technique of importance sampling to several other methods designed to adjust p-values for multiple testing: the Bonferroni correction, the method proposed by Feingold et al., and naïve Monte Carlo simulation. We performed affected sib-pair linkage analysis for each of the 100 replicates for each of five binary traits and adjusted the derived p-values using each of the correction methods. The type I error rates for each correction method and the ability of each of the methods to detect loci known to influence trait values were compared. All of the methods considered were conservative with respect to type I error, especially the Bonferroni method. The ability of these methods to detect trait loci was also low. However, this may be partially due to a limitation inherent in our binary trait definitions.

Computer Simulation↗

Physical and transcript map of the hereditary prostate cancer region at xq27.

We have recently mapped a locus for hereditary prostate cancer (termed HPCX) to the long arm of the X chromosome (Xq25-q27) through a genome-wide linkage study. Here we report the construction of an approximately 9-Mb sequence-ready bacterial clone contig map of Xq26.3-q27.3. The contig was constructed by screening BAC/PAC libraries with markers spaced at approximately 85-kb intervals. We identified overlapping clones by end-sequencing framework clones to generate 407 new sequence-tagged sites, followed by PCR verification of overlaps. Contig assembly was based on clone restriction fingerprinting and the landmark information. We identified a minimal overlap contig for genomic sequencing, which has yielded 7.7 Mb of finished sequence and 1.5 Mb of draft sequence. The transcriptional mapping effort localized 57 known and predicted genes by database searching, STS content mapping, and sequencing, followed by sequence annotation. These transcriptional units represent candidate genes for HPCX and multiple other hereditary diseases at Xq26.3-q27.3.

Chromosome Mapping↗