A systematic approach to analyze the social determinants of cardiovascular disease.

Cardiovascular diseases are the leading cause of human mortality worldwide. Among the many factors associated with the etiology, incidence, and evolution of such diseases; social and environmental issues constitute an important and often overlooked component. Understanding to a greater extent the scope to which such social determinants of cardiovascular diseases (SDCVD) occur as well as the connections among them would be useful for public health policy making. Here, we will explore the historical trends and associations among the main SDCVD in the published literature. Our aim will be finding meaningful relations among those that will help us to have an integrated view on this complex phenomenon by providing historical context and a relational framework. To uncover such relations, we used a data mining approach to the current literature, followed by network analysis of the interrelationships discovered. To this end, we systematically mined the PubMed/MEDLINE database for references of published studies on the subject, as outlined by the World Health Organization's framework on social determinants of health. The analyzed structured corpus consisted in circa 1190 articles categorized by means of the Medical Subheadings (MeSH) content-descriptor. The use of data analytics techniques allowed us to find a number of non-trivial connections among SDCVDs. Such relations may be relevant to get a deeper understanding of the social and environmental issues associated with cardiovascular disease and are often overlooked by traditional literature survey approaches, such as systematic reviews and meta-analyses.

Demographic history and biologically relevant genetic variation of Native Mexicans inferred from whole-genome sequencing.

Understanding the genetic structure of Native American populations is important to clarify their diversity, demographic history, and to identify genetic factors relevant for biomedical traits. Here, we show a demographic history reconstruction from 12 Native American whole genomes belonging to six distinct ethnic groups representing the three main described genetic clusters of Mexico (Northern, Southern, and Maya). Effective population size estimates of all Native American groups remained below 2,000 individuals for up to 10,000 years ago. The proportion of missense variants predicted as damaging is higher for undescribed (~ 30%) than for previously reported variants (~ 15%). Several variants previously associated with biological traits are highly frequent in the Native American genomes. These findings suggest that the demographic and adaptive processes that occurred in these groups shaped their genetic architecture and could have implications in biological processes of the Native Americans and Mestizos of today.

Transcriptional master regulator analysis in breast cancer genetic networks.

Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology.

Human genetics. The genetics of Mexico recapitulates Native American substructure and affects biomedical traits.

Mexico harbors great cultural and ethnic diversity, yet fine-scale patterns of human genome-wide variation from this region remain largely uncharacterized. We studied genomic variation within Mexico from over 1000 individuals representing 20 indigenous and 11 mestizo populations. We found striking genetic stratification among indigenous populations within Mexico at varying degrees of geographic isolation. Some groups were as differentiated as Europeans are from East Asians. Pre-Columbian genetic substructure is recapitulated in the indigenous ancestry of admixed mestizo individuals across the country. Furthermore, two independently phenotyped cohorts of Mexicans and Mexican Americans showed a significant association between subcontinental ancestry and lung function. Thus, accounting for fine-scale ancestry patterns is critical for medical and population genetic studies within Mexico, in Mexican-descent populations, and likely in many other populations worldwide.

Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.