Recent studies have focused on genomic and proteomic approaches to diagnosing and determining the mechanism(s) of preterm labor. Polymorphic changes in the protein coding regions of specific genes and in regulatory and intronic sequences have been described. In most of the studies reported to date, candidate genes or proteins involved in inflammatory reactivity or uterine contractility have been investigated.[8-26] Summaries high throughput screening assay of these observations and candidate genes have been reported.[12] Most of the studies reported to date have involved modest-sized patient cohorts and polymorphisms from genes involved in infection/inflammation.
The results suggest that alteration in the structure and/or expression of these proteins interacts with infection and/or other environmental influences and is associated with preterm birth. The results generally, however, do not provide insight into the causes of prematurity
in the absence of inflammation. They also do not demonstrate whether the observed associations are reflective of genetic mechanism(s) and/or gene–environmental interactions. The promises of the genomic era have been presented eloquently.[27-29] The genome-wide association study (GWAS) approach queries the genome in a hypothesis-free unbiased approach, with the potential BGB324 supplier for identifying novel genetic variants. However, while there have been a number of important ‘hits’ (e.g., macular degeneration, obesity), there are many ‘misses’ and failures to replicate findings even from large-scale studies.[30-32] Moreover, the GWAS-based interrogation of large numbers of anonymous SNPs or CNVs severely limits power and makes it difficult computationally to examine combinatorial gene–gene interactions.[33-35] We created a more manageable set of genes and genetic variants for which there is a prior evidence for involvement in preterm delivery. dbPTB was developed to create, aggregate and store this unique combination and specialized information
on preterm birth. We believe this smaller set of genes may allow important but otherwise difficult computational approaches to examination of gene–gene interactions in combinatorial or higher order fashion. As the first basis for population of this database, we used published literature. One hundred Cepharanthine and eighty-six genes were identified by using the literature-based curation, 215 genes were from publically available databases and an additional 216 genes came from the pathway-based interpolation. This total of 617 genes represents a parsimonious but robust set of genes for which there is good a priori biological evidence for involvement in preterm birth. These genes and genetic variants can be used now in case–controlled studies comparing genetic variants, SNPs or copy number variations for their relationship to PTB. None.