The long term objective of this research is to unravel the genetic mechanisms underlying human disease traits that have a multifactorial etiology. The project proposes to (1) extend the theoretical development of statistical methods for the genetic analysis of human pedigree data, with emphasis on linkage analysis, (2) develop standardized computer programs based on these theoretical methods (3) develop a more extensive map of the human genome, (4) analyze family and pedigree data, and (5) maintain a computer dedicated to genetic analysis. Both parametric and non-parametric methods of linkage analysis will be extended. Linkage parameters will be incorporated into regressive models for segregation analysis, with appropriate ascertainment corrections. The robust Haseman-Elston sibpair linkage test will be extended to other pairs of relatives, to multiple markers, and to multivariate traits. Modularized computer algorithms based on these new methods will be developed; all programs will be written in ANSI standard FORTRAN 77. To develop a more complete map of he human genome a polymorphism laboratory will be maintained and its capabilities extended to allow typing newer systems. In particular, an inexpensive method will be developed to determine DNA polymorphisms by using small oligonucleotide probes. Each such probe would detect 10-20 polymorphic fragments, making it possible to span the entire human genome with many fewer enzyme digestions that are currently necessary for determining restriction fragment length polymorphisms. Pedigrees that have previously been typed for 20-40 polymorphisms will be analyzed for linkage with the newer polymorphic markers (1) to obtain a virtually complete map of he human genome, and (2) to map specific genes involved in multifactorial diseases such as hypertension, hypertriglyceridemia and depression. Since it may confound linkage analysis, non-linkage allelic disequilibrium among the polymorphic markers will be investigated - as well as heterogeneity in the recombination fraction between linked genes due to parental age and sex. Finally, maintenance of a computer dedicated to genetic analysis will support not only the above aims, but also the analysis of family data collected by others over the next five years.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM028356-10A1
Application #
3275649
Study Section
(SSS)
Project Start
1980-03-01
Project End
1994-06-30
Budget Start
1989-07-01
Budget End
1990-06-30
Support Year
10
Fiscal Year
1989
Total Cost
Indirect Cost
Name
Louisiana State University Hsc New Orleans
Department
Type
Schools of Medicine
DUNS #
782627814
City
New Orleans
State
LA
Country
United States
Zip Code
70112
Martin, Lisa J; Lee, Seung-Yeon; Couch, Sarah C et al. (2011) Shared genetic contributions of fruit and vegetable consumption with BMI in families 20 y after sharing a household. Am J Clin Nutr 94:1138-43
Lu, Qing; Obuchowski, Nancy; Won, Sungho et al. (2010) Using the optimal robust receiver operating characteristic (ROC) curve for predictive genetic tests. Biometrics 66:586-93
Zhu, Xiaofeng; Feng, Tao; Li, Yali et al. (2010) Detecting rare variants for complex traits using family and unrelated data. Genet Epidemiol 34:171-87
Ochs-Balcom, Heather M; Guo, Xiuqing; Yonebayashi, Takashi et al. (2010) Program update and novel use of the DESPAIR program to design a genome-wide linkage study using relative pairs. Hum Hered 69:45-51
Larkin, Emma K; Patel, Sanjay R; Zhu, Xiaofeng et al. (2010) Study of the relationship between the interleukin-6 gene and obstructive sleep apnea. Clin Transl Sci 3:337-9
Kopplin, L J; Igo Jr, R P; Wang, Y et al. (2010) Genome-wide association identifies SKIV2L and MYRIP as protective factors for age-related macular degeneration. Genes Immun 11:609-21
Yang, Rong; Li, Lin; Seidelmann, Sara Bretschger et al. (2010) A genome-wide linkage scan identifies multiple quantitative trait loci for HDL-cholesterol levels in families with premature CAD and MI. J Lipid Res 51:1442-51
Gray-McGuire, Courtney; Guda, Kishore; Adrianto, Indra et al. (2010) Confirmation of linkage to and localization of familial colon cancer risk haplotype on chromosome 9q22. Cancer Res 70:5409-18
Martin, Lisa J; Woo, Jessica G; Morrison, John A (2010) Evidence of shared genetic effects between pre- and postobesity epidemic BMI levels. Obesity (Silver Spring) 18:1378-82
Lu, Qing; Cui, Yuehua; Ye, Chengyin et al. (2010) Bagging optimal ROC curve method for predictive genetic tests, with an application for rheumatoid arthritis. J Biopharm Stat 20:401-14

Showing the most recent 10 out of 257 publications