The age-dependent association of risk factors with pancreatic cancer.

BACKGROUND: Pancreatic cancer presents as advanced disease in >80% of patients; yet, appropriate ages to consider prevention and early detection strategies are poorly defined. We investigated age-specific associations and attributable risks of pancreatic cancer for established modifiable and non-modifiable risk factors. PATIENTS AND METHODS: We included 167 483 participants from two prospective US cohort studies with 1190 incident cases of pancreatic cancer during >30 years of follow-up; 5107 pancreatic cancer cases and 8845 control participants of European ancestry from a completed multicenter genome-wide association study (GWAS); and 248 893 pancreatic cancer cases documented in the US Surveillance, Epidemiology, and End Results (SEER) Program. Across different age categories, we investigated cigarette smoking, obesity, diabetes, height, and non-O blood group in the prospective cohorts; weighted polygenic risk score of 22 previously identified single nucleotide polymorphisms in the GWAS; and male sex and black race in the SEER Program. RESULTS: In the prospective cohorts, all five risk factors were more strongly associated with pancreatic cancer risk among younger participants, with associations attenuated among those aged >70 years. The hazard ratios comparing participants with three to five risk factors with those with no risk factors were 9.24 [95% confidence interval (CI) 4.11-20.77] among those aged ≤60 years, 3.00 (95% CI 1.85-4.86) among those aged 61-70 years, and 1.46 (95% CI 1.10-1.94) among those aged >70 years (Pheterogeneity = 3×10-5). These factors together were related to 65.6%, 49.7%, and 17.2% of incident pancreatic cancers in these age groups, respectively. In the GWAS and the SEER Program, the associations with the polygenic risk score, male sex, and black race were all stronger among younger individuals (Pheterogeneity ≤0.01). CONCLUSIONS: Established risk factors are more strongly associated with earlier-onset pancreatic cancer, emphasizing the importance of age at initiation for cancer prevention and control programs targeting this highly lethal malignancy.

Increased Notching of the Corpus Callosum in Fetal Alcohol Spectrum Disorder: A Callosal Misunderstanding?

BACKGROUND AND PURPOSE: In the medicolegal literature, notching of the corpus callosum has been reported to be associated with fetal alcohol spectrum disorders. Our purpose was to analyze the prevalence of notching of the corpus callosum in a fetal alcohol spectrum disorders group and a healthy population to determine whether notching occurs with increased frequency in the fetal alcohol spectrum disorders population. MATERIALS AND METHODS: We performed a multicenter search for cases of fetal alcohol spectrum disorders and included all patients who had a sagittal T1-weighted brain MR imaging. Patients with concomitant intracranial pathology were excluded. The corpus callosum was examined for notches using previously published methods. A χ2 test was used to compare the fetal alcohol spectrum disorders and healthy groups. RESULTS: Thirty-three of 59 patients with fetal alcohol spectrum disorders (0-44 years of age) identified across all centers had corpus callosum notching. Of these, 8 had an anterior corpus callosum notch (prevalence, 13.6%), 23 had a posterior corpus callosum notch (prevalence, 39%), and 2 patients demonstrated undulated morphology (prevalence, 3.4%). In the healthy population, the anterior notch prevalence was 139/875 (15.8%), posterior notch prevalence was 378/875 (43.2%), and undulating prevalence was 37/875 (4.2%). There was no significant difference among the anterior (P = .635), posterior (P = .526), and undulating (P = .755) notch prevalence in the fetal alcohol spectrum disorders and healthy groups. CONCLUSIONS: There was no significant difference in notching of the corpus callosum between patients with fetal alcohol spectrum disorders and the healthy population. Although reported to be a marker of fetal alcohol spectrum disorders, notching of the corpus callosum should not be viewed as a specific finding associated with fetal alcohol spectrum disorders.

Familial pancreatic cancer.

Pancreatic cancer is the fourth leading cause of cancer death in both men and women in the United States and will be responsible for an estimated 28,900 deaths in 2001. Relatively little is known of its etiology, and the only well-established risk factor is cigarette smoking. Studies over the past 3 decades have shown that 4%-16% of patients with pancreatic cancer have a family history of the disease. A small fraction of this aggregation can be accounted for in inherited cancer syndromes, including familial atypical multiple-mole melanoma, Peutz-Jeghers syndrome, hereditary breast-ovarian cancer, hereditary pancreatitis, and hereditary nonpolyposis colorectal cancer. These syndromes arise as a result of germline mutations in the BRCA2, pl6 (familial atypical multiple-mole melanoma), mismatch repair (hereditary nonpolyposis colorectal cancer), and STK11 (Peutz-Jeghers syndrome) genes. In addition, hereditary plays a role in predisposing certain patients with apparently sporadic pancreatic cancer. Many patients with pancreatic cancers caused by a germline mutation in a cancer-causing gene do not have a pedigree that is suggestive of a familial cancer syndrome. A recent prospective analysis of the pedigrees in the National Familial Pancreatic Tumor Registry found that individuals with a family history of pancreatic cancer in multiple first-degree relatives have a high risk of pancreatic cancer themselves. The identification of such high-risk individuals will help clinicians target screening programs and develop preventive interventions with the hope of reducing the mortality of pancreatic cancer in these families.

Multipoint linkage analysis under heterogeneity: incorporation of parametric and nonparametric approaches.

Using a recently developed multipoint parametric method, which tests for linkage in the presence of heterogeneity, we performed a genome-wide search for linkage using the German asthma data. Both dominant and recessive models were assumed in this parametric approach. Identity-by-descent (IBD) sharing for affected sibs was also calculated to help identify an appropriate genetic model and localize the trait locus. The strongest evidence for linkage was on chromosome 6 (p-value = 0.00006) under the dominant model with heterogeneity. Using both linkage and IBD sharing information for D6S422 (36.55 cM) on chromosome 6, we conducted exploratory analyses to locate additional trait loci that might explain the linkage heterogeneity. We found evidence of heterogeneity between D6S422 and D11S4111 based on a test of association (p-value = 0.0015).

Possible linkage of alcoholism, monoamine oxidase activity and P300 amplitude to markers on chromosome 12q24.

Multipoint linkage analysis was used to screen for evidence of linkage between alcoholism and five alcoholism-related quantitative traits. The results suggest that a susceptibility locus that influences monoamine oxidase activity and P300 amplitude at the Pz lead, and increases the risk of alcohol dependence may be linked to markers in the 12q24 region. Furthermore, the susceptibility for alcoholism may be associated with allele 3 (allele size 144) of D12S392.

Environmental covariates: effects on the power of sib-pair linkage methods.

The effect of inclusion of environmental risk factors on the power of sib-pair linkage methods was tested for a qualitative trait. It was found that inclusion of an environmental variable did not increase the power of the Haseman-Elston (H-E) sib-pair nonparametric linkage analysis test. However, a significant increase in power was observed for both the H-E and affected-sib-pair tests, even in small samples, when persons unexposed to the environmental risk factor were coded as unknown.

Multilocus linkage analysis of the German asthma data.

We analyzed data from the German Asthma Genetics Group with three methods that utilize pedigree-specific nonparametric linkage scores to facilitate the search for multiple independent and interacting susceptibility loci. The three methods included a conditional analysis, logistic regression, and neural networks. Although there were differences, the three methods identified many of the same susceptibility loci. The most consistent evidence was provided for loci on chromosomes 1, 2, 6, 9, and 15. Both the conditional and the logistic regression analyses suggested an epistatic relationship between loci on chromosomes 2 and 9. The logistic regression analysis further revealed evidence for locus heterogeneity between loci on chromosomes 6 and 15. Finally, the neural network analysis identified a potential locus on chromosome 17 that was not identified in the other analyses.