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Appointments:
Professor
Department of Medicine
Department of Human Genetics
Committee on Cancer Biology
Committee on Genetics
Committee on Molecular Medicine/MPMM
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Education:
Ph.D. Yale University, 1982
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Contact:
Phone: (773) 843-1001
Fax:
(773) 702-2567
E-Mail:
ncox@bsd.uchicago.edu
Address:
The University of Chicago
AMB M265, (MC 6091)
5841 South Maryland Avenue
Chicago, Illinois 60637
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Related Research Interests:
Obesity
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Nancy Cox, Ph.D.
Research Summary
My
laboratory is a computational "dry" lab. Our research focus is on the
identification and characterization of genetic variation influencing
susceptibility to complex disorders. We work on both the localization
of the genetic variation, via linkage studies and linkage
disequilibrium mapping, as well as on the analytic component to
positional cloning of genes for complex disorders. There are ongoing
collaborations with a variety of groups at the University of Chicago
for which we contribute the genetic analysis, including both linkage
and linkage disequilibrium mapping, and these include projects on type
1 and type 2 diabetes, asthma and related phenotypes, attention deficit
hyperactivity disorder, schizophrenia, bipolar disorder, and autism. In
addition, we have a primary focus on developing and extending methods
for mapping genes for complex disorders. Currently, this research
includes an emphasis on developing robust methods for taking gene-gene
interaction into account in the context of linkage mapping, linkage
disequilibrium mapping and positional cloning. We are also developing,
extending and applying methods for linkage disequilibrium mapping using
the decay of haplotype sharing approaches pioneered by our colleague
and collaborator in the Dept. of Statistics, Mary Sara McPeek. We also
have a major emphasis on developing approaches for identifying the
genetic variation affecting susceptibility to complex disorders in the
context of positional cloning studies. These methods focus on
identifying the genetic variation associated with disease, as well as
showing significant ability to partition the evidence for linkage, and
seeks to distinguish the actual causal variation from genetic variation
that is merely in linkage disequilibrium. These methods are being
immediately applied in projects on type 1 and type 2 diabetes as well
as asthma. Our group is also taking a leadership role in a large
collaborative study on type 2 diabetes, in which we are attempting to
combine data from all existing genome scans for type 2 diabetes for
linkage mapping studies. This project has generated data on a scale
that has not been possible for any individual group to do, and this
massive data set has required development of some novel approaches for
analysis, as well as revision of standard software for mapping. We have
also recently initiated a research project designed to map and identify
genetic variation affecting susceptibility to stuttering. Finally,
because of a long-standing collaboration with a colleague in the Dept.
of Human Genetics, Carole Ober, we are interested in developing and
extending methods for genetic analysis of large, inbred geneologies
such as the Hutterites, which is a long-term, major focus of Dr. Ober's
laboratory.
A
recent focus of our research group is on developing a better
integration of disease gene mapping (largely linkage disequilibrium
mapping in the context of fine-scale mapping) and population genetics,
especially on approaches that would enable us to utilize the signature
of natural selection in fine-mapping of complex disorders. It has been
hypothesized that the genetic variation likely to influence
susceptibility to a number of common, complex disorders that we study
may have been subject to positive selection in the relatively recent
evolutionary past. For example, the same genetic variation that
influences susceptibility to asthma may also affect the ability to
fight and survive parasitic and other infections. The genetic variation
that affects susceptibility to type 2 diabetes has been hypothesized to
have increased the ability to survive famine and food deprivation. Our
colleague in the Dept. of Human Genetics, Anna Di Rienzo, is studying
the signature of natural selection at genes known to have been under
different forms of selection (balancing and directional), and we are
working with Dr. Di Rienzo as well as colleagues in Evolution and
Ecology to integrate the results of such studies into approaches for
disease gene mapping.
The
emphasis in my laboratory is on conducting an optimal analysis of
whatever genetic data is at hand. Sometimes, existing methods and
software are perfectly adequate for an optimal analysis, but often, an
optimal analysis requires modification of existing methods or
development of entirely new approaches. Our computational laboratory is
completely integrated into the Dept. of Human Genetics, and so we
interact on a regular basis with the molecular biologists and
population geneticists who have laboratories in the department. This
interaction, coupled with the stimulation of a tremendous amount of
genetic data available through our primary projects and collaborations,
insures that the theoretical work and methodology development is not
done in a vacuum. Moreover, because of our collaborations with
scientists in the Dept. of Statistics, the theoretical work and
methodology development is truly multidisciplinary, with a rigorous
statistical foundation. Our network of collaboration allows a great
deal of flexibility in designing and conducting research projects that
can range from purely theoretical, to largely analytical, to a mix of
analytic and molecular science.
Selected Papers
Journal Articles
Cox
NJ, Frigge M, Nicolae DL, Concannon P, Hanis CL, Bell GI and Kong A.
(1999). Loci on chromosomes 2 (NIDDM1) and 15 interact to increase
susceptibility to type 2 diabetes. Nature Genet 21:213-215.
Ober
C, Leavitt SA, Tsalenko A, Howard TD, Hoki DM, Daniel R, Newman DL, Wu
X, Parry R, Lester LA, Solway J, Blumenthal M, King RA, Xu J, Meyers
DA, Bleecker ER, Cox NJ. (2000). Variation in the interleukin
4-receptor
a gene confers suceptibility to asthma and atopy in ethnically diverse
populations. Am J Hum Genet 66:517-526.
Horikawa
Y, Oda N, Cox NJ et al. (2000). Genetic variation in the gene encoding
calpain-10 is associated with type 2 diabetes mellitus. Nature Genet
26:163-175.
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Faculty and Research
Programs
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