Stem cells nomenclature

Stem cells appellation derives from German Stammzelle that defines firstly the evolutionary unicellular ancestor of multicellular organisms and secondarily the ancestral stem cell in an organism, initially in the germ line. Subsequently this term was applied to other tissues, generating some confusion.

In particular some problems arise with the notions of precursor and progenitor: indeed we talk about progenitor if the appellation of stem cells leaves doubts about the nature of the cells, while precursor is usually used to define the ancestral embryonic cell in the lineage of interest –for instance blasts are precursors of neuroblast, myoblast and so on- General and frequently accepted criteria to define one stem cell are the self renewal and the transit amplification; another criterion that has been proposed is the classification of cell states in terms of epigenetic, chromatin rearrangement and gene- expression. In this way it could be possible to distinguish stem cell from progenitor and precursor without nomenclature bias. Also the assumption that in one tissue only one stem cell is present, could be corrected and when cell stem signature will be done, it could be possible –and reasonable- to identify different stem cells with different genetic signatures.

Smoking behavior is genetically determined?

Drug addiction is usually genetically determined by peculiar single nucleotide polymorphism. These mutations are clustered and associated to more frequent form of dependence. Given the status of smoking behavior that is often considered as a drug, scientists from the University of Missouri analyzed SNPs in large Caucasian population. They identified nine loci where the mutations of SNP were located. Furthermore, in African population they observed other two SNPs different from the first none above.

All these single nucleotide polymorphism’s were identified near to IL15 gene and were correlated with high parameters currently used to evaluate nicotine dependence. Male specificity was observed in both populations analyzed. IL15 is an important cytokine that controls the immune system and, in this case, seems strongly associated also with smoking habit. The molecular mechanism that SNPs use seemed to be related to gene regulation and expression because the most of mutations were identified in the binding site for transcription factors. Smoking is one of principal risk factor for lung cancer, so the determination of SNPs that could influence this behavior could allow to identify potential smokers into the population and, maybe, avoid that they start to smoke. This approach could decrease the number of smokers and, potentially, of lung cancer patients.

Genome-wide study on cardiovascular diseases

We have already talked about the importance of genome-wide analysis to study diseases and we have described some method for SNPs identification. In the current number of Nature Genetics an interesting study on cardiovascular diseases has been published. Co-authors belong to 95 institutions (hospitals, universities and research centers) in Europe and USA.

They analyzed the genotype of thousands patients and identified a correlation between high systolic pressure and mutations in limited region of the genome. In particular, they observed an association with the following eight genes: CYP17A1, CYP1A2, FGF5, SH2B3, MTHFR, c10orf107, ZNF652 and PLCD3.. This study has been confirmed by another work, always available in the same volume of Nature Genetics in which scientists identified four loci for systolic blood pressure (ATP2B1, CYP17A1, PLEKHA7, SH2B3), six for diastolic blood pressure (ATP2B1, CACNB2, CSK-ULK3, SH2B3, TBX3-TBX5, ULK4) and one for hypertension (ATP2B1). Why are so important these works? Firstly, these genes could be validated in further studies in order to understand if they could be considered as a target to prevent hypertension and develop new therapies for. Secondarily, this collaboration between so many institutions has to be a model for other studies about world-wide diseases.

References:
Nature Genetics 41, 667 – 676 (2009)
Nature Genetics 41, 677 – 687 (2009)