Walter Klimecki

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic metabolizing enzymes can lead to differences in target tissue dosimetry for key metabolites causative in toxic and carcinogenic response. This type of variation can be quantitatively incorporated into pharmacokinetic (PK) models and used together with population-based modeling approaches to evaluate the impact of genetic variation in methylation capacity on dose of key metabolites to target tissue. The PK model is an essential bridge to the pharmacodynamic (PD) models. A particular benefit of PD modeling for arsenic is that alternative models can be constructed for multiple proposed modes of action for arsenicals. Genomics data will prove useful for identifying the key pathways involved in particular responses and aid in determining other types of data needed for quantitative modeling. These models, when linked with PK models, can be used to better understand and explain dose- and time-response behaviors. This in turn assists in prioritizing modes of action with respect to their risk assessment relevance and future research. This type of integrated modeling approach can form the basis for a highly informative mode-of-action directed risk assessment for inorganic arsenic (iAs). This paper will address both practical and theoretical aspects of integrating PK and PD data in a modeling framework, including practical barriers to its application.

The epigenetic silencing of tumor suppressor genes is a common event during carcinogenesis, and often involves aberrant DNA methylation and histone modification of gene regulatory regions, resulting in the formation of a transcriptionally repressive chromatin state. Two examples include the antimetastatic, tumor suppressor genes, desmocollin 3 (DSC3) and MASPIN, which are frequently silenced in this manner in human breast cancer. Treatment of the breast tumor cell lines MDA-MB-231 and UACC 1179 with 5-aza-2'-deoxycytidine (5-aza-CdR) induced transcriptional reactivation of both genes in a dose-dependent manner. Importantly, DSC3 and MASPIN reactivation was closely and consistently linked with significant decreases in promoter H3 K9 di-methylation. Moreover, 5-aza-CdR treatment also resulted in global decreases in H3 K9 di-methylation, an effect that was linked to its ability to mediate dose-dependent, post-transcriptional decreases in the key enzyme responsible for this epigenetic modification, G9A. Finally, small interfering RNA (siRNA)-mediated knockdown of G9A and DNMT1 led to increased MASPIN expression in MDA-MB-231 cells, to levels that were supra-additive, verifying the importance of these enzymes in maintaining multiple layers of epigenetic repression in breast tumor cells. These results highlight an additional, complimentary mechanism of action for 5-aza-CdR in the reactivation of epigenetically silenced genes, in a manner that is independent of its effects on DNA methylation, further supporting an important role for H3 K9 methylation in the aberrant repression of tumor suppressor genes in human cancer.

The T-cell immunoglobulin domain and mucin domain (TIM) gene family and the gene for IL-2-inducible T-cell kinase (ITK), located in chromosome 5 q 33 and potentially involved in the T-cell proliferation and differentiation, are good candidate genes for allergic diseases.

PMID: 15696078;Abstract:

Background: Defensins are antimicrobial peptides that may take part in airway inflammation and hyperresponsiveness. We characterized the genetic diversity in the defensin β-1 (DEFB1) locus and tested for an association between common genetic variants and asthma diagnosis. Methods: To identify single nucleotide polymorphisms (SNPs), we resequenced this gene in 23 self-defined European Americans and 24 African Americans. To test whether DEFB1 genetic variants are associated with asthma, we genotyped 4 haplotype-tag SNPs in 517 asthmatic and 519 control samples from the Nurses' Health Study (NHS) and performed a case-control association analysis. To replicate these findings, we evaluated the DEFB1 polymorphisms in a second cohort from the Childhood Asthma Management Program. Results: Within the NHS, single SNP testing suggested an association between asthma diagnosis and a 5′ genomic SNP (g.-1816 T>C; P = .025) and intronic SNP (IVS+692 G>A; P = .054). A significant association between haplotype (Adenine, Cytosine, Thymine, Adenine [ACTA]) and asthma (P = .024) was also identified. Associations between asthma diagnosis and both DEFB1 polymorphisms were observed in Childhood Asthma Management Program, a second cohort: g.-1816 T>C and IVS+692 G>A demonstrated significant transmission distortion (P = .05 and .007, respectively). Transmission distortion was not observed in male subjects. The rare alleles (-1816C and +692A) were undertransmitted to offspring with asthma, suggesting a protective effect, contrary to the findings in the NHS cohort. Similar effects were evident at the haplotype level: ACTA was undertransmitted (P = .04) and was more prominent in female subjects (P = .007). Conclusion: Variation in DEFB1 contributes to asthma diagnosis, with apparent gender-specific effects.