Dr. Ott’s laboratory focuses on the interpretation of genomic data, such as results from microarrays and single nucleotide polymorphisms (SNPs). Dr. Ott develops new mathematical-statistical methods for human gene mapping and builds computer programs to implement them. He uses the resulting information to study the interactions among multiple disease loci that underlie complex traits, as well as to study how environmental risk factors modify disease loci effects.
Dr. Ott’s work falls into three broad categories: improving existing statistical analysis methods and developing new ones; creating computer programs to implement these methods and
offering them for download on his lab’s Web site; and applying the techniques to genetic data, most of which is generally collected by outside investigators.
In recent years, emphasis in disease gene mapping has shifted from linkage analysis to case-control association analysis. Academic and industry researchers are most interested in heritable complex traits — such as heart disease and schizophrenia — that are believed to be under the control of multiple interacting susceptibility loci, each with relatively small effect. One of the challenges is in identifying sets of such disease loci: Dr. Ott has done substantial work in this area, carrying out data analysis with collaborating drug companies. In one case, he developed a set association analysis to jointly investigate multiple SNP genotypes in heart disease patients, identifying nine SNP markers associated with post-angioplasty artery narrowing. In another instance, his lab used SNPs to determine which gene was associated with a small number of patients’ adverse reactions to a well-established drug.
Dr. Ott is also interested in improving analysis techniques that were developed in the lab. His set-association analysis method, for example, is currently designed for case-control data or binary outcome variables. But because researchers are often interested in the effects of genes on quantitative observations, Dr. Ott is working to extend his methods so that he can analyze these kinds of data. He is also pursuing additional methods to analyze DNA sequences, and recently developed and published an algorithm that predicts transcription factor binding sites.
The set-association approach developed by Dr. Ott’s lab grew out of scientists’ increasing need to work with a quantity of genes that can far outnumber the quantity of observations, such as that found in genomic screens for disease loci or in microarray experiments. He is currently working on the first phase of a two-step approach, which consists of first selecting a suitable small number of genes out of the large pool and then jointly analyzing the selected set with a suitable multivariate method. Much of the lab’s work in the immediate future will be devoted to making this approach more efficient and generally applicable to different data types.
Dr. Ott is a pioneer in the field of genetic linkage, and authored the first publicly accessible computer program on human linkage analysis (dubbed LIPED). His work led to some of the first methods for computer simulation in family pedigrees and provided the statistical framework underlying the newer approaches to haplotype relative risk methods that have become important tools in the search for disease-marker associations. He has analyzed gene linkages for a number of disorders, including hypertension, macular degeneration, Creutzfeldt-Jacob disease, multiple sclerosis and retinitis pigmentosa.
CAREER
Dr. Ott earned his Ph.D. in zoology from the
University of Zürich in 1967, taught physics at
a state college in Switzerland and then worked
as a biostatistician until 1970. He earned his
master’s degree in biomathematics from the
University of Washington, Seattle in 1972, then
stayed on at the university as a research assistant,
postdoc, assistant professor and associate
professor. Dr. Ott returned to Zürich in 1979
as the assistant director for the city’s statistics
office. In 1986, he accepted two positions in
New York City: professor of genetics and development
at Columbia University and research
scientist and director of the department of
statistics at the New York State Psychiatric Institute.
Dr. Ott came to Rockefeller in 1996 as
professor and head of the Laboratory of Statistical
Genetics. He remains an adjunct professor
at Columbia University and maintains an office
at the Beijing Institute of Genomics, Chinese
Academy of Sciences.
In 2007, Dr. Ott received the Medal of
Honor from the German Society for Human
Genetics (GfH). He received a Merit award
from the National Institutes of Mental Health
in 2001 and is a member of the American Association
for the Advancement of Science and the
Human Genome Organization.
