The HUGO Journal

Angiotensin-I-converting enzyme (ACE) is known to be associated with human cardiovascular and psychiatric pathophysiology. We have undertaken a global survey of the haplotypes in ACE gene to study diversity and to draw inferences on the nature of selective forces that may be operating on this gene. We have investigated the haplotype profiles reconstructed using polymorphisms in the regulatory (rs4277405, rs4459609, rs1800764, rs4292, rs4291), exonic (rs4309, rs4331, rs4343), and intronic (rs4340; Alu [I/D]) regions covering 17.8 kb of the ACE gene. We genotyped these polymorphisms in a large number of individuals drawn from 15 Indian ethnic groups and estimated haplotype frequencies. We compared the Indian data with available data from other global populations. Globally, five major haplotypes were observed. High-frequency haplotypes comprising mismatching alleles at the loci considered were seen in all populations. The three most frequent haplotypes among Africans were distinct from the major haplotypes of other world populations. We have studied the evolution of the two major haplotypes (TATATTGIA and CCCTCCADG), one of which contains an Alu insertion (I) and the other a deletion (D), seen most frequently among Caucasians (68%), non-African HapMap populations (65–88%), and Indian populations (70–95%) in detail. The two major haplotypes among Caucasians are reported to represent two distinct clades A and B. Earlier studies have postulated that a third clade C (represented by the haplotypes TACATCADG and TACATCADA) arose from an ancestral recombination event between A and B. We find that a more parsimonious explanation is that clades A and B have arisen by recombination between haplotypes belonging to clade C and a high-frequency African haplotype CCCTTCGIA. The haplotypes, which according to our hypothesis are the putative non-recombinants (PuNR), are uncommon in all non-African populations (frequency range 0–12%). Conversely, the frequencies of the putative recombinant haplotypes (PuR) are very low in the Africans populations (2–8%), indicating that the recombination event is likely to be ancient and arose before, perhaps shortly prior to, the global dispersal of modern humans. The global frequency spectrum of the PuR and the PuNR is difficult to explain only by drift. It appears likely that the ACE gene has been undergoing a combination of different selective pressures.

Recently articles have been published disputing the main finding of the ENCODE project that the majority of the human genome exhibits biochemical indices of function, based primarily on low sequence conservation and the existence of larger genomes in some ostensibly simpler organisms (the C-value enigma), indicating the likely presence of significant amounts of junk. Here we challenge these arguments, showing that conservation is a relative measure based on circular assumptions of the non-functionality of transposon-derived sequences and uncertain comparison sets, and that regulatory sequence evolution is subject to different and much more plastic structure-function constraints than protein-coding sequences, as well as positive selection for adaptive radiation. We also show that polyploidy accounts for the higher than expected genome sizes in some eukaryotes, compounded by variable levels of repetitive sequences of unknown significance. We argue that the extent of precise dynamic and differential cell- and tissue-specific transcription and splicing observed from the majority of the human genome is a more reliable indicator of genetic function than conservation, although the unexpectedly large amount of regulatory RNA presents a conceptual challenge to the traditional protein-centric view of human genetic programming. Finally, we suggest that resistance to these findings is further motivated in some quarters by the use of the dubious concept of junk DNA as evidence against intelligent design.

The concept of personalized medicine not only promises to enhance the life of patients and increase the quality of clinical practice and targeted care pathways, but also to lower overall healthcare costs through early-detection, prevention, accurate risk assessments and efficiencies in care delivery. Current inefficiencies are widely regarded as substantial enough to have a significant impact on the economies of major nations like the US and China, and, therefore the world economy. A recent OECD report estimates healthcare expenditure for some of the developed western and eastern nations to be anywhere from 10% to 18%, and growing (with the US at the highest). Personalized medicine aims to use state-of-the-art genomic technologies, rich medical record data, tissue and blood banks and clinical knowledge that will allow clinicians and payors to tailor treatments to individuals, thereby greatly reducing the costs of ineffective therapies incurred through the current trial and error clinical paradigm. Pivotal to the field are drugs that have been designed to target a specific molecular pathway that has gone wrong and results in a diseased condition and the diagnostic tests that allow clinicians to separate responders from non-responders. However, the truly personalized approach in medicine faces two major problems: complex biology and complex economics; the pathways involved in diseases are quite often not well understood, and most targeted drugs are very expensive. As a result of all current efforts to translate the concepts of personalized healthcare into the clinic, personalized medicine becomes participatory and this implies patient decisions about their own health. Such a new paradigm requires powerful tools to handle significant amounts of personal information with the approach to be known as “P4 medicine”, that is predictive, preventive, personalized and participatory. P4 medicine promises to increase the quality of clinical care and treatments and will ultimately save costs. The greatest challenges are economic, not scientific.

Differences in immunological response among vaccine recipients are determined both by their genetic differences and environmental factors. Knowledge of genetic determinants of immunological response to a vaccine can be used to design a vaccine that circumvents immunogenetic restrictions. The currently available vaccine for typhoid is a pure polysaccharide vaccine, immune response to which is T-cell independent. Little is known about whether genetic variation among vaccinees associates with variation in their antibody response to a polysaccharide vaccine. We conducted a study on 1,000 individuals resident in an area at high-risk for typhoid; vaccinated them with the typhoid vaccine, measured their antibody response to the vaccine, assayed >2,000 curated SNPs chosen from 283 genes that are known to participate in immune-response; and analyzed these data using a strategy to (a) minimize the statistical problems associated with testing of multiple hypotheses, and (b) internally cross-validate inferences, using a half-sample design, with little loss of statistical power. The first stage analysis, using the first half-sample, identified 54 SNPs in 43 genes to be significantly associated with immune response. In the second-stage, these inferences were cross-validated using the second half-sample. First-stage results of only 8 SNPs (out of 54) in 7 genes (out of 43) were cross-validated. We tested additional SNPs in these 7 genes, and found 8 more SNPs to be significantly associated. Haplotypes constructed with these SNPs in these 7 genes also showed significant association. These 7 genes are DEFB1, TLR1, IL1RL1, CTLA4, MAPK8, CD86 and IL17D. The overall picture that has emerged from this study is that (a) immune response to polysaccharide antigens is qualitatively different from that to protein antigens, and (b) polymorphisms in genes involved in polysaccharide recognition, signal transduction, inhibition of T-cell proliferation, pro-inflammatory signaling and eventual production of antimicrobial peptides are associated with antibody response to the polysaccharide vaccine for typhoid.

Fanconi Anemia (FA) is a rare disorder with incidence of 1in 350,000 births. It is characterized by progressive bone marrow failure leading to death of many patients in their childhood while development of cancer at later stages of life in some. The treatment of FA is still a medical challenge. Current treatments of FA include androgen administration, hematopoietic growth factors administration and hematopoietic stem cell transplantation (HSCT). Clinical gene therapy trials are still ongoing. The partial success of current therapies has renewed interest in the search for new treatments. Generation of patient-specific induced pluripotent stem (iPS) has shown promising results for cell and gene based therapy. Small molecule interventions have been observed to delay tumor onset in FA. Tumors deficient in FA pathway can be treated by profiling of DNA repair pathway through synthetic lethality mechanism. Targeting toll-like receptor 8 (TLR8) dependent TNFα overexpression is yet another upcoming therapeutic approach to treat FA patients. In conclusion, in the present scenario of treatments available for FA, a proper algorithm of treatment decisions must be followed for better management of FA patients and to ensure their increased survival. Innovative therapeutic approaches that can prevent both anemia and cancer should be developed for more effective treatment of FA.

In the area of omics and translational bio(medical)sciences, there is an increasing need to integrate, normalize, analyze, store and protect genomics data. Large datasets and scientific knowledge are rationally combined into valuable clinical information that ultimately will benefit human healthcare and are en route to clinical practice. Data from biomarker discovery and Next Generation Sequencing (NGS) are very valuable and will combine in comprehensive analyses to stratify medicine and guide therapy planning and ultimately benefit patients. However, the combination into useful and applicable information and knowledge is not trivial. Personalized medicine generally promises to result in both higher quality in treatment for individual patients and in lower costs in health care since patients will be offered only such therapies that are more effective for them and treatments that will not be safe or effective will be avoided. Recent advancements in biomedical and genomic sciences have paved the way to translate such research into clinical practice and health policies. However, the move towards greater personalization of medicine also comes along with challenges in the development of novel diagnostic and therapeutic tools in a complex framework that assumes that the use of genomic information is part of a translational continuum, which spans from basic to clinical research, preclinical and clinical trials, to policy research and the analysis of health and economic outcomes. The use of next-generation genomic technologies to improve the quality of life and efficiency of healthcare delivered to patients has become a mainstay theme in the field as benefits derived from such approaches include reducing a patient’s need to go through ineffective therapies, lowering side- and off-target effects of drugs, prescribing prophylactic therapies before acute exacerbations, and reducing expenditures. As such, personalized medicine promises to increase the quality of clinical care and, in some cases, to decrease health care costs. Besides the scientific challenges, there are several economic hurdles. For instance, healthcare providers need to know, whether the approach of personalized healthcare is affordable and worth the expenses. In addition, the economic rationale of personalized healthcare includes not only the reduction of the high expense of hospitalizations, the predictive diagnostics that will help to reduce cost through prevention or the increased efficacy of personalized therapies needs to offset prices of drugs. There are also several factors that influence payer adoption, coverage and reimbursement; the strength of evidence drives payers‘ decisions about coverage and reimbursement, varies widely depending on the personalized healthcare technology applied and regulation and cost-effectiveness seem to be increasingly associated with reimbursement, which is strongly influenced by professional society guidelines. In general, we see the following main obstacles to the advancement of personalized medicine: (i) the scientific challenges (a poor understanding of molecular mechanisms or a lack of molecular markers associated with some diseases, for example), (ii) the economic challenges (poorly aligned incentives), and (iii) operational issues in public healthcare systems. The operational issues can often be largely resolved within a particular stakeholder group, but correcting the incentive structure and modifying the relationships between stakeholders is more complex. This article focuses on the scientific difficulties that remain to translate genomics technologies into clinical practice and reviews recent technological advances in genomics and the challenges and potential benefits of translating this knowledge into clinical practice, with a particular focus on their applications in oncology.

Growing investments in health research by governments and charitable organizations have fueled an increase in collaborative research projects between investigators from affluent and developing countries. Current international guidelines are silent on common intra-consortium data-sharing issues that arise in the context of such collaborations. A lack of guidance on intra-consortium data sharing threatens to undermine the success of crucial research ventures. In this work we outline some of the practical problems commonly faced by investigators working in multi-institutional, international genomic collaborations and offer recommendations on these issues. A data sharing policy should be prospectively negotiated and concluded between collaborators as early as possible. Sponsors of research, including those from developing countries, should issue detailed guidance on the above and related issues as doing so will facilitate research and catalyze scientific progress.