Biomedical subjects

Kari Rabe

Publications and source records attributed to Kari Rabe.

4 recordsLinked to original sources

PubMed2005

Lower cancer incidence in Amsterdam-I criteria families without mismatch repair deficiency: familial colorectal cancer type X.

CONTEXT: Approximately 60% of families that meet the Amsterdam-I criteria (AC-I) for hereditary nonpolyposis colorectal cancer (HNPCC) have a hereditary abnormality in a DNA mismatch repair (MMR) gene. Cancer incidence in AC-I families with MMR gene mutations is reported to be very high, but cancer incidence for individuals in AC-I families with no evidence of an MMR defect is unknown. OBJECTIVE: To determine if cancer risks in AC-I families with no apparent deficiency in DNA MMR are different from cancer risks in AC-I families with DNA MMR abnormalities. DESIGN, SETTING, AND PARTICIPANTS: Identification (1997-2001) of 161 AC-I pedigrees from multiple population- and clinic-based sources in North America and Germany, with families grouped into those with (group A) or without (group B) MMR deficiency by tumor testing. A total of 3422 relatives were included in the analyses. MAIN OUTCOME MEASURES: Cancer incidence in groups A and B (excluding the 3 affected members used to define each pedigree as AC-I) and computed age- and sex-adjusted standardized incidence ratios (SIRs) using Surveillance, Epidemiology, and End Results data. RESULTS: Group A families from both population- and clinic-based series showed increased incidence of the HNPCC-related cancers. Group B families showed increased incidence only for colorectal cancer (SIR, 2.3; 95% confidence interval, 1.7-3.0) and to a lesser extent than group A (SIR, 6.1; 95% confidence interval, 5.2-7.2) (P<.001). CONCLUSIONS: Families who fulfill AC-I criteria but who have no evidence of a DNA MMR defect do not share the same cancer incidence as families with HNPCC-Lynch syndrome (ie, hereditary MMR deficiency). Relatives in such families have a lower incidence of colorectal cancer than those in families with HNPCC-Lynch syndrome, and incidence may not be increased for other cancers. These families should not be described or counseled as having HNPCC-Lynch syndrome. To facilitate distinguishing these entities, the designation of "familial colorectal cancer type X" is suggested to describe this type of familial aggregation of colorectal cancer.

Adaptor Proteins, Signal Transducing↗

PubMed2005

Germ line Fanconi anemia complementation group C mutations and pancreatic cancer.

Biallelic mutations in Fanconi anemia complementation group genes disrupt DNA repair and result in the complex Fanconi anemia phenotype. In addition, germ line mutations in the BRCA2/FANCD1 Fanconi anemia complementation group gene have also been implicated in predisposition to a number of cancers including pancreatic cancer. The recent identification of FANCC and FANCG mutations in resected pancreatic tumors selected for loss of heterozygosity on chromosome 9, some of which were present in the germ line DNA, suggests that inactivation of these and other Fanconi complementation group genes may contribute to pancreatic cancer. To further assess the relevance of FANCC and FANCG mutations to pancreatic cancer we conducted a mutation screen of these genes in DNA from blood of 421 sequentially collected pancreatic cancer cases diagnosed at the Mayo Clinic. Two truncating FANCC mutations but no truncating FANCG mutations were identified in young onset (<55 years) pancreatic cancer cases with no family history of pancreatic cancer. Both mutations were associated with loss of heterozygosity of the wild-type allele in corresponding pancreatic tumors. In addition, no truncating mutations were identified in germ line DNA from blood of 658 control individuals undergoing routine colonoscopy. Taken together these data support the assertion that inherited mutations in FANCC can predispose to pancreatic cancer.

Adenocarcinoma↗

PubMed2004

MYH mutations in patients with attenuated and classic polyposis and with young-onset colorectal cancer without polyps.

BACKGROUND & AIMS: MYH-associated polyposis is a recently described disease that is characterized by multiple colorectal adenomas and a recessive pattern of inheritance. Individuals with MYH-associated polyposis have biallelic mutations in MYH, a base excision repair gene, and are negative for germline mutations in the APC gene. In this study, the 2 most prevalent MYH mutations in white persons, Y165C and G382D, were analyzed for their presence in 984 subjects selected from 3 groups: 400 undergoing screening colonoscopy and found to have 0-3 polyps, 444 with colorectal cancer (CRC), and 140 referred for APC mutation analysis in which a germline mutation was not identified. METHODS: Genotyping for Y165C and G382D was performed by Pyrosequencing. RESULTS: Biallelic mutations for Y165C and/or G382D were not found in any of those undergoing screening colonoscopy with 0-3 polyps (n = 400), in those APC-negative patients with <20 adenomatous polyps (n = 26), or in those with CRC who were older than 50 years (n = 328). Furthermore, these 2 MYH mutations were not found among patients whose tumors showed the presence of defective DNA mismatch repair (n = 62). However, the presence of biallelic germline MYH mutations correlated with the presence of >or=20 adenomatous polyps. Interestingly, 2 of the 116 individuals with CRC diagnosed at 50 years of age or younger also presented with biallelic germline mutations in MYH. CONCLUSIONS: These data suggest that screening of MYH should be considered not only in patients with multiple polyps but also in patients with early-onset CRC.

Adenomatous Polyposis Coli↗

PubMed2003

Imputation methods for missing data for polygenic models.

Methods to handle missing data have been an area of statistical research for many years. Little has been done within the context of pedigree analysis. In this paper we present two methods for imputing missing data for polygenic models using family data. The imputation schemes take into account familial relationships and use the observed familial information for the imputation. A traditional multiple imputation approach and multiple imputation or data augmentation approach within a Gibbs sampler for the handling of missing data for a polygenic model are presented.We used both the Genetic Analysis Workshop 13 simulated missing phenotype and the complete phenotype data sets as the means to illustrate the two methods. We looked at the phenotypic trait systolic blood pressure and the covariate gender at time point 11 (1970) for Cohort 1 and time point 1 (1971) for Cohort 2. Comparing the results for three replicates of complete and missing data incorporating multiple imputation, we find that multiple imputation via a Gibbs sampler produces more accurate results. Thus, we recommend the Gibbs sampler for imputation purposes because of the ease with which it can be extended to more complicated models, the consistency of the results, and the accountability of the variation due to imputation.

Adult Children↗