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Genomics and Proteomics: Article Comparison

This paper compares and contrasts two articles: (1) “Ancestry and disease in the age of Genomic medicine” by Charles N. Rotimi and Lynn B. Jorde published in the 2010 New England Journal of Medicine, volume 363: 1551-1558 and (2) “Discovery of pathway biomarkers from coupled proteomics and systems biology methods” by Fan Zhang and Jake Y. Chen published in BMC Genomics, volume 11(Suppl 2):S12 – S22. The genomics article by Rotimi and Jorde is the same with the proteomics article by Zhang and Chen in that both papers utilize non-experimental aspects of research design. Both articles have a review of literature on the subject under discussion. The difference is that Zhang and Chen utilize literature review as a way of validating the experimental part of the study. Rotimi and Jorde however utilize review of literature as the sole method in identifying human genetic variation and its implications in medicine.
Both articles discuss advancements in human genetics and how knowledge of human genetics is being applied in disease screening and diagnosis leading to better understanding of disease. The proteomics article by Zhang and Chen (p. 17) expound more on the discovery of biomarkers for breast cancer using the knowledge of proteomics. The authors of this article collect plasma samples from women (healthy and women with breast cancer) and prepares a proteome profile to allow for the identification of protein biomarkers basing the analysis on the fact that cell lines from breast cancer can help in discovering protein biomarkers. This study uses both experimental and literature review to reach a conclusion on the existence of protein biomarkers used in cancer screening. The experimental part of this study involves the preparation and analysis of the plasma samples from healthy women and comparison with samples from women with breast cancer. After identifying protein expression levels in the samples (where there were 208 over-expressed proteins and 46 under-expressed proteins) using techniques such as liquid chromatography and mass spectrometry. Analysis of data is done using t-test statistic (a parametric test) and permutation test (non-parametric test) unlike in the genomics article where there is no data analysis hence no analytical test is used. T
The literature review part of the study involves getting previous research works that have identified human breast cancer cell lines as well as breast cancer cell lines. The authors are therefore able to authenticate their results where 25 potential protein biomarkers are identified. The experimental part of the study also identifies complement and coagulation pathways, focal adhesion as well as regulation of actin cytoskeleton as breast cancer pathways. The authors are keen to cross-check their findings with existing literature for validation purposes.
The genomics article by Rotimi and Jorde (p. 1552) on the other hand is purely a non-experimental research paper where the authors discuss the application of human genetics data in medicine by reviewing existing and current knowledge. In this article, the authors argue that human genetic data reveals variations in human genetic make up in the population and among individuals. As such, this understanding is therefore enlightening on the customization of treatment. The principle idea in this article is that genetic variation in human beings is increasingly coming into light thus helping understand the evolution of human beings in a better way. Rotimi and Jorde (p. 1553) cite single-nucleotide polymorphisms (SNPs) as the critical components that define variations in human genes. Also important in human genetic variation is copy-number variants. Understanding of these variations traces human origin most likely to be Africa. These authors maintain that since human genetic variation is prevalent in all populations and among individuals, it is worth screening for genetic conditions in all populations rather than the traditional stereotyping of certain genetic conditions to certain populations or regions. For instance, glucose-6-phosphate dehydrogenase deficiency is mainly associated with black populations. This is however inaccurate since genetic variations which lead to the disease are globally distributed despite in smaller frequencies in some populations.

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