It is now possible to examine at a genome-scale level how genetic variation in human alters risk of disease, either directly or through secondary risk factors such as obesity. The high resolution of the genomic approaches allows particular chromosomal regions to be identified for further study so that the pathways involved can be defined and drugable components identified. We have just completed a whole genome scan of families from a community-based population in Framingham, Massachusetts, that involved typing 100,000 single nucleotide polymorphisms per individual and identified a common variant that increases risk of obesity. The closest gene INSIG2 is involved in the regulation of fatty acid synthesis. Another variant affecting a gene in the same pathway, ACACA is associated with leanness. Both genes are potential therapeutic targets and we are in the process of initiating a high-throughput screen of candidate drugs using a chemical library available through the NIH/NIGMS -funded Center for Methodologies and Library Development at Boston University.
Analysis of other traits is also underway - data is available for many phenotypes, ranging from hypertension to dyslipidemias (http://gmed.bu.edu). Behavioral data relating to alcohol and cigarette smoking as well as mini-mental status is also being analyzed, potentially providing insight into pathways of addition and also genes that predict successful neurological aging.
The success of our project has encouraged NHLBI to perform a higher density SNP scan in all Framingham Heart Study participants and develop a resource, based at NIH that will allow all qualified investigators access to all the data from the study and thus accelerate the pace of discovery.
We are also applying these approaches to the study of other human populations. We have collaborations with the Howard University Family Study and the Black Women's Health Study. The Delaware Valley Personalized Medicine Project will extend this work directly to the clinic.
These approaches represent the first time that human genetics can be approached in a normal population. One of the hopes is that we will be able to identify not only proteins that affect phenotype, but also instances where non-coding RNAs regulate the read-out of genetic information. Our laboratory is also active in performing experiments to elucidate these molecular pathways.
Representative Publications
Herbert A, Lenburg ME, Ulrich D, Gerry NP, Schlauch K, Christman MF. Open-access database of candidate associations from a genome-wide SNP scan of the Framingham Heart Study.Nat Genet 2007;39:135-6.
Herbert A, Gerry NP, McQueen MB, et al. A common genetic variant is associated with adult and childhood obesity. Science 2006;312:279-83.
Herbert A, Liu C, Karamohamed S, et al. BMI modifies associations of IL-6 genotypes with insulin resistance: the Framingham Study. Obesity (Silver Spring) 2006;14:1454-61.
Herbert A, Liu C, Karamohamed S, et al. The -174 IL-6 GG genotype is associated with a reduced risk of type 2 diabetes mellitus in a family sample from the National Heart, Lung and Blood Institute's Framingham Heart Study. Diabetologia 2005.
Herbert A. The four Rs of RNA-directed evolution. Nat Genet 2004;36:19-25.
Herbert A. Roles for Z-DNA and double-stranded RNA in transcription: Encoding Genetic Information by Shape rather than by Sequence. 2004. In: DNA conformation and transcription. Ohyama T, ed.; Landes Bioscience: Georgetown, TX
Herbert A, Wagner S, Nickerson JA. Induction of protein translation by ADAR1 within living cell nuclei is not dependent on RNA editing. Mol Cell 2002;10:1235-46.
Herbert A, Rich A. The role of binding domains for dsRNA and Z-DNA in the in vivo editing of minimal substrates by ADAR1. Proc Natl Acad Sci U S A 2001;98:12132-7.
Herbert A, Rich A. RNA processing and the evolution of eukaryotes. Nat Genet 1999;21:265-9.
Herbert A, Rich A. RNA processing in evolution. The logic of soft-wired genomes. Ann N Y Acad Sci 1999;870:119-32.
Herbert A, Rich A. RNA processing and the evolution of eukaryotes. Nat Genet 1999;21:265-9.
Herbert A, Rich A. Left handed Z-DNA: structure and function. 1999. In: Structural Biology and Functional Genomics. E.M. B, S. P, eds.; Kluwer Academic Publishers: Netherlands: 53-72.
Herbert A, Schade M, Lowenhaupt K, et al. The Za domain from human ADAR1 binds to the Z-DNA conformer of many different sequences. Nucleic Acids Research 1998;26:3486-93.
Herbert A, Kim Y-G, Alfken J, Nishikura K, Rich A. A Z-DNA binding domain from the human editing enzyme dsRNA adenosine deaminase. Proceedings of the National Academy of Science, USA 1997;94:12875-9.
Herbert A, Rich A. The biology of left-handed Z-DNA. J Biol Chem 1996;271:11595-8.
Herbert A, Lowenhaupt K, Spitzner J, Berger I, Rich A. A biological role for Z-DNA. 1996. In: Biological Structure and Dynamics. Proceedings of the Ninth Conversation. H SR, Sarma MH, eds.; Adenine Press: Albany, NY: 189-97.
Herbert A. RNA editing, introns and evolution. Trends in Genetics 1996;12:6-9.
Herbert A, Lowenhaupt K, Spitzner J, Rich A. Double-stranded RNA adenosine deaminase binds Z-DNA in vitro. Nucleic Acids Symp Ser 1995:16-9.
Herbert A, Lowenhaupt K, Spitzner J, Rich A. Chicken double-stranded RNA adenosine deaminase has apparent specificity for Z-DNA. Proc Natl Acad Sci U S A 1995;92:7550-4.
Herbert AG, Spitzner JR, Lowenhaupt K, Rich A. Z-DNA binding protein from chicken blood nuclei. Proc Natl Acad Sci U S A 1993;90:3339-42.
Herbert AG, Rich A. A method to identify and characterize Z-DNA binding proteins using a linear oligodeoxynucleotide. Nucleic Acids Res 1993;21:2669-72.
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