Research Interests and Teaching Activities
Human organism is a complex system with multiple levels of organization, regulated by intrinsic factors and profoundly modified by external influences. This complex system undergoes a profound change with an advanced age. Therefore, the overall research focus of Dr. Karasik's group is in the area of interpersonal variability of aging, ranging from morphological changes in ossified tissues with age to the genetics of osteoporosis, sarcopenia (muscle wasting), and menopause to the pleiotropic genetic factors governing multiple age-related conditions.
Musculoskeletal Genetics: We perform statistical genetic analyses of bone mass, bone geometry, and lean mass, using data from the well-known Framingham Heart Study (FHS) cohorts. We are performing genome-wide linkage and genome-wide association analyses (GWAS), using whole-genome data from the SNP Health Association Resource (SHARe). We expect that our studies will help to elucidate the genetic contribution to quantitative traits such as bone mass and geometry and muscle mass, and to the qualitative and age-of-onset phenotypes, such as osteoporotic fractures. Identification of genes governing bone mass, bone geometry, and ultimately bone strength is an important first step for understanding the underlying mechanisms of bone formation and resorption. Ultimately, they may provide molecular targets for future osteoporosis therapies.
Our search for genes suggested by the GWAS and linkage studies in humans is reinforced by a parallel search in mouse syntenic regions, based on homology between the species (via ongoing collaboration with the colleagues from the Jackson Laboratories). It is expected that differences between the mouse sublines in bone mass, geometry and bone quality are reflected in differentially expressed genes, as well as in genome sequence differences between the mouse strains. This allows us to expedite the identification of new gene candidates and appropriate polymorphic markers for association studies in our human sample, in parallel with functional experiments in mouse models.
We also work on determining the association between polymorphisms in several biological candidate genes and osteoporosis-related phenotypes. We continue to engage in genetic association studies with biological candidate genes for complex musculoskeletal diseases in a large sample of the Framingham cohort participants. We realized early on that even with a sample of several thousand participants, as in FHS, a genetic study is underpowered to provide a definite result, especially for a rare variant. Therefore, we participated in a meta-analysis of genome-wide scans of bone mass and joined the GENOMOS consortium in 2006. Currently, we are part of the new initiatives - GEFOS and CHARGE consortia - dedicated to a large-sample GWAS of musculoskeletal aging related phenotypes, as well as SUNLIGHT consortium, for Vitamin D.
Biological Aging: We are actively participating in the international genetic consortia in the field of aging, such as Longevity Consortium and CHARGE, performing large-scale meta-analyses of GWAS of age at death and successful aging (aging free of diseases and disabilities), as well as reproductive aging phenotypes (REPROGEN consortium).
Teaching: Dr. Karasik have acquired more than ten years of teaching experience in Human Gross Anatomy, from several schools (Sackler School of Medicine, Tel Aviv University; Department of Anatomy and Neurobiology, Boston University Medical School). Currently, he is serving as an Instructor in Human Body Course at Harvard Medical School, with an overall yearly commitment of 6-7 hours of lab a week for 8-9 weeks.
Keywords:
genetic epidemiology; osteoporosis; genome-wide analyses; candidate genes; biological aging
Selected Publications
1. Kiel D.P., Demissie S, Cupples L.A., Dupuis J, Lunetta K.L., Murabito J.M., Karasik D. Genome-wide Association with Bone Mass and Geometry in the Framingham Heart Study. BMC Medical Genetics (2007) 8(Suppl 1):S14
2. Lunetta K.L., D'Agostino RB, Sr., Karasik D., Benjamin EJ, Guo CY, Govindaraju R, Kiel D.P. et al. Genetic Correlates of Longevity and Selected Age-related Phenotypes: A Genome-wide Association Study in the Framingham Study. BMC Medical Genetics (2007) 8(Suppl 1):S13
3. van Meurs JBJ, Trikalinos TA, Ralston SH, Balcells S, et al. Large scale analysis of the association between polymorphisms in the LRP-5 and LRP-6 genes and osteoporosis. JAMA 2008; 299:1277-1290.
4. Perry J.R.B., Stolk L, Franceschini L, Lunetta KL, Zhai G et al. Loci on Chromosome 6 and 9 are associated with age at menarche: a meta-analysis of genome wide association data from 17,510 women. Nature Genetics 2009, 41:648-650
5. Richards JB, Kavvoura FK, Rivadeneira F, Styrkársdóttir U, Estrada K, et al. for the GEnetic Factors For Osteoporosis (GEFOS) Consortium. A systematic evaluation of 147 candidate genes for their association with osteoporosis and osteoporotic fracture in a meta-analysis of genome-wide association data. Annals of Internal Medicine 2009, 151:528-537.
6. Karasik D, Hsu, YH, Zhou Y, Cupples LA, Kiel DP, Demissie S. Genome-wide pleiotropy of osteoporosis-related phenotypes: The Framingham Study. J Bone Miner Res 2010, 25(7): 1555-1563.
7. Ackert-Bicknell, CL; Karasik, D; Li, Q; Smith, RV; Hsu, YH; Churchill, GA et al. Mouse BMD Quantitative Trait Loci Show Improved Concordance with Human Genome Wide Association Loci when Recalculated on a New, Common Mouse Genetic Map. J Bone Miner Res 2010, 25(8): 1808-1820
8. Hsu Y-H, Zillikens MC, Wilson SG, Farber CR, Demissie S et al. An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits. PLoS Genet 2010; 6(6): e1000977.
9. Wang TJ, Zhang F, Richards JB, Kestenbaum B, van Meurs JB et al. Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet 2010;376(9736):180-8
10. Elks CE, Perry J.R.B., Sulem P., Chasman D. I., Franceschini N., He C., Lunetta KL et al. Thirty two new loci for age at menarche identified by a meta-analysis of genome-wide association studies. Nature Genetics 2010; 42 (12) :1077-1087
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