The proposed research aims: to: a) Improve the understanding of the genetics of inherited diseases with unclear modes of transmission. Studies will evaluate the effectiveness of current methods of analysis, in particular linkage analysis and the use of measures of association, in understanding the underlying genetic mechanisms of such traits. Simulation studies will be used to generate data reflecting confounding factors thought to be a problem in linkage analysis of certain complex traits (for example psychiatric or behavioral disorders). Factors to be considered include assortative mating; genetic heterogeneity and trait determination by more than one locus. The ability of current methods to correctly analyze traits with these characteristics will be assessed and, where found lacking, alternative methods will be developed and tested. b) Carry out classical linkage analysis for specific genetic diseases. The diseases to be studied include tuberous sclerosis and Fanconi anemia, where evidence for genetic heterogeneity has already been detected. Methods to be tested in the simulation studies can be applied to these analyses in order to better understand the complete genetic picture, including identification of heterogeneity by detecting linkage of different disease forms to different marker loci. Such differentiation will help sharpen the clinical definition of various forms of the diseases. c) Refine strategies for ordering multiple linked loci on linkage maps using either pairwise recombination data or data generated from radiation hybrid experiments. d) Apply techniques of neural network pattern matching to problems of genetic systems. Applications include aid in phenotype definition for traits with multiple clinical characteristics, prediction of risk of disease based on phenotype, values of known risk factors and disease profiles in relatives and estimation of missing recombination data in multilocus data sets using information from other linkage relationships. As a result of advances from this work, better mathematical tools for the study of diseases with complex or ill-defined inheritance patterns will be available. Applications to specific diseases will increase understanding of interactions between clinical definition and predisposing genetic factors. This will increase the precision of genetic counseling and suggest useful approaches for studying the mechanisms involved in determining disease state.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM029177-13
Application #
3276698
Study Section
Mammalian Genetics Study Section (MGN)
Project Start
1981-04-01
Project End
1996-07-31
Budget Start
1993-08-01
Budget End
1994-07-31
Support Year
13
Fiscal Year
1993
Total Cost
Indirect Cost
Name
New York Blood Center
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10065
Falk, Catherine T (2005) Diagnosis of alcoholism based on neural network analysis of phenotypic risk factors. BMC Genet 6 Suppl 1:S131
Costello, Tracy J; Falk, Catherine T; Ye, Kenny Q (2003) Data mining and computationally intensive methods: summary of Group 7 contributions to Genetic Analysis Workshop 13. Genet Epidemiol 25 Suppl 1:S57-63
Falk, Catherine T (2003) Risk factors for coronary artery disease and the use of neural networks to predict the presence or absence of high blood pressure. BMC Genet 4 Suppl 1:S67
Falk, C T (2001) Locus ordering based on crossover information in family haplotypes: application of a ""minimum break"" algorithm. Genet Epidemiol 21 Suppl 1:S565-70
Falk, C T (2001) Introduction: halotype analysis of simulated Genetic Analysis Workshop12 data. Genet Epidemiol 21 Suppl 1:S552-3
Reynolds, D M; Falk, C T; Li, A et al. (2000) Identification of a locus for autosomal dominant polycystic liver disease, on chromosome 19p13.2-13.1. Am J Hum Genet 67:1598-604
Falk, C T (1999) Systematic search for disease loci for complex genetic traits: a study based on simulated population data. Genet Epidemiol 17 Suppl 1:S551-6
Li, W; Haghighi, F; Falk, C T (1999) Design of artificial neural network and its applications to the analysis of alcoholism data. Genet Epidemiol 17 Suppl 1:S223-8
Falk, C T; Gilchrist, J M; Pericak-Vance, M A et al. (1998) Using neural networks as an aid in the determination of disease status: comparison of clinical diagnosis to neural-network predictions in a pedigree with autosomal dominant limb-girdle muscular dystrophy. Am J Hum Genet 62:941-9
Falk, C T (1997) Effect of genetic heterogeneity and assortative mating on linkage analysis: a simulation study. Am J Hum Genet 61:1169-78

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