Yi (Sherry) Zhang, PhD

Yi (Sherry) Zhang, PhD

Assistant Professor
Department of Medicine
Genomic Sciences and Precision Medicine Center

TOPS Obesity and Metabolic Research Center
Medical College of Wisconsin
8701 Watertown Plank Road
Milwaukee, WI 53226

(414) 955-4013 | Fax: (414) 955-6386


PhD, Molecular Biology (Marquette University, Milwaukee, USA)
Post-doctoral Fellowship in Genetics of Human Dyslipidemia (Medical College of Wisconsin, Milwaukee, USA)

Previous Positions

Research Scientist, Genetics and Epigenetics of the Metabolic Syndrome (MCW, Milwaukee, USA)

Investigative Interests

Metabolic Syndrome (MetS), Obesity, Epigenetics of adult and adolescent MetS, Gene-environment interactions in MetS etiology.

Ongoing Research

Metabolic syndrome (MetS) affects one of every three Americans and dramatically increases their risk for cardiovascular disease. Individual phenotypic components of MetS such as skewed body fat distribution and insulin resistance are consequences of the dynamic interaction between nature (the genome) and nurture (the environment). Genomic CpG methylation status, an epigenetic regulator of gene expression, is one of the prominent mechanistic links between the genome and the environment. Studying the quantitative relationship of MetS traits and genomic methylation status is therefore likely to unravel genetic elements and pathways that have not been identified by previous genomic studies focusing on primary sequence variants.

The TOPS Obesity and Metabolic Research Center possess a unique study population that consists of multi-generational extended families of Northern European origin that have been phenotyped for 42 clinical and biological components of the MetS. These large pedigrees also contain children undergoing puberty, a crucial stage in the development of MetS in adults. I am interested in applying state-of-the-art high throughput genomic technologies to the investigation of pathogenesis of MetS using this unique population. We have recently proposed to study the relationship between regional and global DNA methylation and these 42 MetS phenotypes in these families. By combining genome-wide SNP genotype data as well as genome-wide gene expression data of the most informative pedigrees, we will be able to prioritize our candidate genes for the detailed CpG methylation study.

We hope to create a new map of MetS epigenetic markers by using our unique suite of expertise in human and animal systems. By using related human subjects and inbred mouse strains, we aim to assess heritability of CpG methylation as well as diet-, age- and sex- effects on this epigenetic feature. This will enable us to identify the epigenetic loci that can integrate environmental cues in triggering pathophysiological pathways leading to MetS, a cluster of high-risk factors for type 2 diabetes, CV disease and cancer.

Selected Peer Review Publications (*= co-first author; **= corresponding author):

  1. Ali, O., Cerjak, D., Kent J. W., James R., Blangero J. and Zhang Y.*, ** (2014). Obesity, central adiposity and cardiometabolic risk factors in children and adolescents: a family-based study. Pediatric Obesity (Epub ahead of print).PMID: 24677702.
  2. Zhang Y.**, Kent Jr. J.W., Olivier M., Ali O., Broeckel U., Abdou R.M., Dyer T., Comuzzie A., Curran J.E., Carless M.A., Rainwater D.L., Göring H.H.H., Blangero J. and Kissebah A.H. (2013) QTL-based association analyses reveal novel genes influencing pleiotropy of Metabolic Syndrome (MetS). Obesity 21(10):2099-111.PMID: 23628382; PMC3643849.
  3. Zhang Y.**, Kent Jr. J.W., Lee A., Cerjak D., Ali O., Diasio R. Olivier M.,Blangero J., Carless M.A., and Kissebah A.H. (2013) Fatty acid binding protein 3 (fabp3)is associated with insulin, lipids and cardiovascular phenotypes of the metabolic syndrome through epigenetic modifications in a Northern European family population. BMC Medical Genomics6:9-23.PMID: 23510163; PMC3608249.
  4. Zhang Y.**, Kent J., Olivier M., Ali O., Cerjak D., Broeckel U., Abdou R., Dyer Anthony T., Comuzzie A.,Curran J., Carless M., Rainwater D., Göring H., Blangero J. and Kissebah A.H. (2013). A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation. BMC Medical Genomics6:14-29. PMID: 23628382; PMC3643849.
  5. Smith E.M.*, Zhang Y.*, Baye T.M., Gawrieh S., Cole R., Blangero J., Carless M.A., Curran J.E., Dyer T.D., Abraham L.J., Moses E.K., Kissebah A.H., Martin L.J., and Olivier M. (2010) INSIG1 influences obesity-related hypertriglyceridemia in humans. Journal of Lipid Research51: 701-708. PMID:19965593 PMCID:PMC2838707.
  6. Zhang Y.*, Smith E.M.*, Baye T.M., Kissebah A.H., Martin L.J., and Olivier M. (2010) Serotonin (5-HT) receptor 5A sequence variants affect human plasma triglyceride levels. Physiological Genomics42: 168-176.PMID:20388841 PMCID:PMC3032280.
  7. Baye T.M.*, Zhang Y.* Smith E., Hillard C.J., Gunnell J., Myklebust J., James R., Kissebah A.H., Olivier M. * and Wilke R.A. * (2008) Genetic variation in cannabinoid receptor 1 (CNR1) is associated with derangements in lipid homeostasis, independent of body mass index. Pharmacogenomics9 (11):1647-1656.PMID:19018721 PMCID:PMC2784739.
  8. Zhang Y.*, Sonnenberg G.E.*, Baye T.M.*, Littrell J., Gunnell J., DeLaForest A., MacKinney E., Hillard C.J., Kissebah A.H., Olivier M. and Wilke R.A. (2010) Obesity-related dyslipidemia associated with FAAH, independent of insulin response, in multigenerational families of Northern European descent. Pharmacogenomics10 (12): 1929-1939.PMID:19958092 PMCID:PMC3003434.
  9. Zhang Y. and Schläppi M. (2007) Cold responsive EARLI1 type HyPRPs improve freezing survival of yeast cells and form higher order complexes in plants. Planta227: 233-243.PMID:17786468.
  10. Wu C., Chen S., Shortreed M.R., Kreitinger G. M., Yuan Y., Frey B. L., Zhang Y., Mirza S., Cirillo L. A., Olivier M., and Smith L. M.. Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification. (2011) PLoS One 6: e26217. PMID:22028835 PMCID:PMC3197616.

Book Chapters

Zhang Y. *, Smith E. *, and Olivier M. (2008).  Putting the Invader® Assay to Work: Lab Application and Data Management. In: Single Nucleotide Polymorphisms: Methods and Protocols (the Methods in Molecular Biology series), 2nd edition. Vol: 578: page 363-377. Humana Press, Totowa, NJ