Research Interests

Key words: human genetics and genomics, diabetes, obesity, lipids, complex diseases

Identify new genetic loci associated with complex diseases and traits

To identify genetic variants that confer disease susceptibility or influence variability in related traits, we conduct genome-wide association studies (GWAS) in human population studies. In recent years, we and our collaborators have used the GWAS approach to identify hundreds of new genetic loci associated with type 2 diabetes, obesity, cholesterol levels, metabolic traits, and cardiovascular risk factors. Large-scale meta-analyses and other multidisciplinary collaborations are key to many of these discoveries. We also study how genetic variants interact with environmental factors to influence the underlying biology of complex diseases and traits.

Prioritize disease- and trait-associated SNPs for functional follow-up

Loci identified by GWAS usually contain several single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium (LD) with each other. Testing every variant for biological relevance individually can be labor-intensive and time-consuming. We use computational approaches to identify SNPs in putative regulatory regions and prioritize these SNPs for experimental analysis.

Genome-wide data sets containing information about chromatin structure, transcription factor binding, and epigenetic marks in human cells are important resources for identifying potential regulatory regions. The ENCODE and Roadmap Epigenomics Projects contain experimental evidence of open chromatin (FAIRE, and DNase I-seq), histone modifications (histone ChIP-seq), and transcription factor binding sites (transcription factor ChIP-seq and DNase I footprinting) in several human cell lines and tissues. Using these genomic data from disease-relevant cell lines and tissues, we seek to identify trait-associated SNPs likely to regulate gene transcription.

Investigate the functional mechanisms underlying genetic associations

For most of the new loci identified by GWAS, the underlying functional mechanisms remain unknown. Determining the biological basis for the associations of genetic loci with complex diseases and traits will improve our general scientific understanding of pathways contributing to disease etiology. We employ molecular and cellular biology techniques to identify the functional variant(s) and gene(s) at these loci, explain the molecular mechanisms linking functional variant(s) to gene(s), and explain the biological mechanisms linking gene(s) to metabolic traits.

Identify new genetic loci associated with complex diseases and traits

To identify genetic variants that confer disease susceptibility or influence variability in related traits, we conduct genome-wide association studies (GWAS) in human population studies. In recent years, we and our collaborators have used the GWAS approach to identify hundreds of new genetic loci associated with type 2 diabetes, obesity, cholesterol levels, metabolic traits, and cardiovascular risk factors. Large-scale meta-analyses and other multidisciplinary collaborations are key to many of these discoveries. We also study how genetic variants interact with environmental factors to influence the underlying biology of complex diseases and traits.

Prioritize disease- and trait-associated SNPs for functional follow-up

Loci identified by GWAS usually contain several single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium (LD) with each other. Testing every variant for biological relevance individually can be labor-intensive and time-consuming. We use computational approaches to identify SNPs in putative regulatory regions and prioritize these SNPs for experimental analysis.
Genome-wide data sets containing information about chromatin structure, transcription factor binding, and epigenetic marks in human cells are important resources for identifying potential regulatory regions. The ENCODE and Roadmap Epigenomics Projects contain experimental evidence of open chromatin (FAIRE, and DNase I-seq), histone modifications (histone ChIP-seq), and transcription factor binding sites (transcription factor ChIP-seq and DNase I footprinting) in several human cell lines and tissues. Using these genomic data from disease-relevant cell lines and tissues, we seek to identify trait-associated SNPs likely to regulate gene transcription.

Investigate the functional mechanisms underlying genetic associations

For most of the new loci identified by GWAS, the underlying functional mechanisms remain unknown. Determining the biological basis for the associations of genetic loci with complex diseases and traits will improve our general scientific understanding of pathways contributing to disease etiology. We employ molecular and cellular biology techniques to identify the functional variant(s) and gene(s) at these loci, explain the molecular mechanisms linking functional variant(s) to gene(s), and explain the biological mechanisms linking gene(s) to metabolic traits.

Publications

PubMed Link

Karen Mohlke in UNC Genetics News