scholarly journals Genomic research perspectives in Kazakhstan

2014 ◽  
Vol 2 ◽  
Author(s):  
Ainur Akilzhanova
Keyword(s):  
Personalized Medicine ◽  
Population Genomics ◽  
Cancer Genomics ◽  
Clinical Symptoms ◽  
Disease Risk ◽  
Genomic Medicine ◽  
Life Sciences ◽  
Genomic Research ◽  
Laboratory Staff ◽  
Research Perspectives

Introduction: Technological advancements rapidly propel the field of genome research. Advances in genetics and genomics such as the sequence of the human genome, the human haplotype map, open access databases, cheaper genotyping and chemical genomics, have transformed basic and translational biomedical research. Several projects in the field of genomic and personalized medicine have been conducted at the Center for Life Sciences in Nazarbayev University. The prioritized areas of research include: genomics of multifactorial diseases, cancer genomics, bioinformatics, genetics of infectious diseases and population genomics. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine. Results: To further develop genomic and biomedical projects at Center for Life Sciences, the development of bioinformatics research and infrastructure and the establishment of new collaborations in the field are essential.Widespread use of genetic tools will allow the identification of diseases before the onset of clinical symptoms, the individualization of drug treatment, and could induce individual behavioral changes on the basis of calculated disease risk. However, many challenges remain for the successful translation of genomic knowledge and technologies into health advances, such as medicines and diagnostics.It is important to integrate research and education in the fields of genomics, personalized medicine, and bioinformatics, which will be possible with opening of the new Medical Faculty at Nazarbayev University. People in practice and training need to be educated about the key concepts of genomics and engaged so they can effectively apply their knowledge in a matter that will bring the era of genomic medicine to patient care. This requires the development of well-equipped laboratories, bioinformatics, as well as qualified trained physicians and laboratory staff.

scholarly journals Personalized medicine in thrombosis: back to the future

Blood ◽  
2016 ◽  
Vol 127 (22) ◽  
pp. 2665-2671 ◽  
Author(s):  
Srikanth Nagalla ◽  
Paul F. Bray
Keyword(s):  
Personalized Medicine ◽  
Disease Risk ◽  
Platelet Reactivity ◽  
Clinical Care ◽  
Genomic Medicine ◽  
Personal Data ◽  
Value Added ◽  
Antiplatelet Agents ◽  
Small Effect Size ◽  
The Individual

Abstract Most physicians believe they practiced personalized medicine prior to the genomics era that followed the sequencing of the human genome. The focus of personalized medicine has been primarily genomic medicine, wherein it is hoped that the nucleotide dissimilarities among different individuals would provide clinicians with more precise understanding of physiology, more refined diagnoses, better disease risk assessment, earlier detection and monitoring, and tailored treatments to the individual patient. However, to date, the “genomic bench” has not worked itself to the clinical thrombosis bedside. In fact, traditional plasma-based hemostasis-thrombosis laboratory testing, by assessing functional pathways of coagulation, may better help manage venous thrombotic disease than a single DNA variant with a small effect size. There are some new and exciting discoveries in the genetics of platelet reactivity pertaining to atherothrombotic disease. Despite a plethora of genetic/genomic data on platelet reactivity, there are relatively little actionable pharmacogenetic data with antiplatelet agents. Nevertheless, it is crucial for genome-wide DNA/RNA sequencing to continue in research settings for causal gene discovery, pharmacogenetic purposes, and gene-gene and gene-environment interactions. The potential of genomics to advance medicine will require integration of personal data that are obtained in the patient history: environmental exposures, diet, social data, etc. Furthermore, without the ritual of obtaining this information, we will have depersonalized medicine, which lacks the precision needed for the research required to eventually incorporate genomics into routine, optimal, and value-added clinical care.

scholarly journals The Impact of Ethnicity and Genetic Ancestry on Disease Prevalence and Risk in Colombia

2021 ◽  
Vol 12 ◽  
Author(s):  
Aroon T. Chande ◽  
Shashwat Deepali Nagar ◽  
Lavanya Rishishwar ◽  
Leonardo Mariño-Ramírez ◽  
Miguel A. Medina-Rivas ◽  
...  
Keyword(s):  
Ethnic Groups ◽  
Disease Risk ◽  
Genomic Medicine ◽  
Disease Prevalence ◽  
Genetic Ancestry ◽  
Genomic Research ◽  
European Ancestry ◽  
Full Potential ◽  
Strongly Correlated ◽  
The Impact

Currently, the vast majority of genomic research cohorts are made up of participants with European ancestry. Genomic medicine will only reach its full potential when genomic studies become more broadly representative of global populations. We are working to support the establishment of genomic medicine in developing countries in Latin America via studies of ethnically and ancestrally diverse Colombian populations. The goal of this study was to analyze the effect of ethnicity and genetic ancestry on observed disease prevalence and predicted disease risk in Colombia. Population distributions of Colombia’s three major ethnic groups – Mestizo, Afro-Colombian, and Indigenous – were compared to disease prevalence and socioeconomic indicators. Indigenous and Mestizo ethnicity show the highest correlations with disease prevalence, whereas the effect of Afro-Colombian ethnicity is substantially lower. Mestizo ethnicity is mostly negatively correlated with six high-impact health conditions and positively correlated with seven of eight common cancers; Indigenous ethnicity shows the opposite effect. Malaria prevalence in particular is strongly correlated with ethnicity. Disease prevalence co-varies across geographic regions, consistent with the regional distribution of ethnic groups. Ethnicity is also correlated with regional variation in human development, partially explaining the observed differences in disease prevalence. Patterns of genetic ancestry and admixture for a cohort of 624 individuals from Medellín were compared to disease risk inferred via polygenic risk scores (PRS). African genetic ancestry is most strongly correlated with predicted disease risk, whereas European and Native American ancestry show weaker effects. African ancestry is mostly positively correlated with disease risk, and European ancestry is mostly negatively correlated. The relationships between ethnicity and disease prevalence do not show an overall correspondence with the relationships between ancestry and disease risk. We discuss possible reasons for the divergent health effects of ethnicity and ancestry as well as the implication of our results for the development of precision medicine in Colombia.

scholarly journals ‘CTRL’: an online, Dynamic Consent and participant engagement platform working towards solving the complexities of consent in genomic research

2021 ◽  
Author(s):  
Matilda A. Haas ◽  
Harriet Teare ◽  
Megan Prictor ◽  
Gabi Ceregra ◽  
Miranda E. Vidgen ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
International Standards ◽  
Security And Privacy ◽  
Genomic Research ◽  
Return Of Results ◽  
Future Research ◽  
Design And Development ◽  
Participant Engagement ◽  
Dynamic Consent

AbstractThe complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

scholarly journals The Role of Network Science in Glioblastoma

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1045
Author(s):  
Marta B. Lopes ◽  
Eduarda P. Martins ◽  
Susana Vinga ◽  
Bruno M. Costa
Keyword(s):  
Personalized Medicine ◽  
Drug Development ◽  
Information Flow ◽  
Clinical Studies ◽  
Network Science ◽  
Cancer Genomics ◽  
High Dimensional ◽  
Network Discovery ◽  
Software Implementations

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.

scholarly journals Personalized Cancer Medicine in the Media: Sensationalism or Realistic Reporting?

2021 ◽  
Vol 11 (8) ◽  
pp. 741
Author(s):  
Katherine Hicks-Courant ◽  
Jenny Shen ◽  
Angela Stroupe ◽  
Angel Cronin ◽  
Elizabeth F. Bair ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Media Coverage ◽  
Disease Risk ◽  
Federal Drug Administration ◽  
Personalized Cancer Medicine ◽  
The Media ◽  
Cancer Medicine ◽  
Media Reports ◽  
Personalized Cancer ◽  
Standard Tests

Background: Given that media coverage can shape healthcare expectations, it is essential that we understand how the media frames “personalized medicine” (PM) in oncology, and whether information about unproven technologies is widely disseminated. Methods: We conducted a content analysis of 396 news reports related to cancer and PM published between 1 January 1998 and 31 December 2011. Two coders independently coded all the reports using a pre-defined framework. Determination of coverage of “standard” and “non-standard” therapies and tests was made by comparing the media print/broadcast date to the date of Federal Drug Administration approval or incorporation into clinical guidelines. Results: Although the term “personalized medicine” appeared in all reports, it was clearly defined only 27% of the time. Stories more frequently reported PM benefits than challenges (96% vs. 48%, p < 0.001). Commonly reported benefits included improved treatment (89%), prediction of side effects (30%), disease risk prediction (33%), and lower cost (19%). Commonly reported challenges included high cost (28%), potential for discrimination (29%), and concerns over privacy and regulation (21%). Coverage of inherited DNA testing was more common than coverage of tumor testing (79% vs. 25%, p < 0.001). Media reports of standard tests and treatments were common; however, 8% included information about non-standard technologies, such as experimental medications and gene therapy. Conclusion: Confusion about personalized cancer medicine may be exacerbated by media reports that fail to clearly define the term. While most media stories reported on standard tests and treatments, an emphasis on the benefits of PM may lead to unrealistic expectations for cancer genomic care.

Trailblazing Precision Medicine in Europe: a joint view by Genomic Medicine Sweden and the Centers for Personalized Medicine, ZPM, in Germany

2021 ◽  
Author(s):  
Albrecht Stenzinger ◽  
Anders Edsjö ◽  
Carolin Ploeger ◽  
Mikaela Friedman ◽  
Stefan Fröhling ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Precision Medicine ◽  
Genomic Medicine

scholarly journals Indispensability of Clinical Bioinformatics for Effective Implementation of Genomic Medicine in Pathology Laboratories

ACI Open ◽  
2020 ◽  
Vol 04 (02) ◽  
pp. e167-e172
Author(s):  
Srikar Chamala ◽  
Siddardha Majety ◽  
Shesh Nath Mishra ◽  
Kimberly J. Newsom ◽  
Shaileshbhai Revabhai Gothi ◽  
...  
Keyword(s):  
Patient Care ◽  
Clinical Laboratory ◽  
Clinical Care ◽  
Genomic Medicine ◽  
Clinical Pathology ◽  
Genetic Mutation ◽  
Genomic Research ◽  
Pathology Laboratory ◽  
Clinical Bioinformatics ◽  
Effective Implementation

AbstractPatient care is rapidly evolving toward the inclusion of precision genomic medicine when genomic tests are used by clinicians to determine disease predisposition, prognosis, diagnosis, and improve therapeutic decision-making. However, unlike other clinical pathology laboratory tests, the development, deployment, and delivery of genomic tests and results are an intricate process. Genomic technologies are diverse, fast changing, and generate massive data. Implementation of these technologies in a Clinical Laboratory Improvement Amendments-certified and College of American Pathologists-accredited pathology laboratory often require custom clinical grade computational data analysis and management workflows. Additionally, accurate classification and reporting of clinically actionable genetic mutation requires well-curated disease/application-specific knowledgebases and expertise. Moreover, lack of “out of the box” technical features in electronic health record systems necessitates custom solutions for communicating genetic information to clinicians and patients. Genomic data generated as part of clinical care easily adds great value for translational research. In this article, we discuss current and future innovative clinical bioinformatics solutions and workflows developed at our institution for effective implementation of precision genomic medicine across molecular pathology, patient care, and translational genomic research.

The most useful and commonly available acute rejection surveillance strategies are routine monitoring of myocardial function and donor-specific anti-HLA Abs monitoring

2021 ◽  
Author(s):  
Moataz Dowaidar
Keyword(s):  
Acute Rejection ◽  
Cell Function ◽  
Clinical Symptoms ◽  
Contractile Function ◽  
Therapy Monitoring ◽  
Genomic Medicine ◽  
Non Invasive ◽  
Monitoring Tools ◽  
Immune Mediated ◽  
Routine Monitoring

Given the complexity of acute rejection (AR) pathogenesis and its vast spectrum of clinical symptoms, no methodology (invasive or non-invasive) can provide all the information needed to identify functionally and prognostically relevant AR, treatment selection, and therapy monitoring early. Only the use of EMBs in combination with non-invasive technologies and methods to detect subclinical changes in myocardial contractile function (e.g., TDI and STE), to detect alloimmune activation (e.g., IM assay, assessment of complement-activating donor-specific anti-HLA Abs (DSAbs), screening of circulating cfdDNA), and to predict the imminent risk of immune-mediated injury (e.g., assessment of complement-activating DSAbs).Searching for both ACR and AMR in all EMBs is a key prerequisite for accurate diagnosis and decision-making in individuals suspected of AR. Close non-invasive allograft surveillance to detect patients at high risk of AR, along with properly planned EMBs (depending on the particular risk profile of the patient), can improve AR surveillance while decreasing rsEMBs. Because rsEMBs are less prevalent after the first post-HTx year and largely symptom-driven diagnostic EMBs, ongoing development of comprehensive, non-invasive technology to monitor both ACR and AMR is of significant importance. This is especially helpful for detecting late subclinical AMR, which would otherwise go unreported.The most useful and commonly available AR surveillance strategies are routine monitoring of myocardial functions utilizing sensitive ECHO techniques (TDI and STE for acute subclinical dysfunction diagnosis) and DSAb monitoring. As a result, early and late use of HTx is strongly suggested. New IM technologies such as T-cell function assays and genomic medicine approaches such as GEP, circulating dd-cfdDNA screening and microRNA assessment are promising non-invasive monitoring tools for future clinical use, but it is still necessary to test the practical value of their individual or combined use for AR detection (including both ACR and AMR), not just for ACR.

Genomic Medicine Frontier in Human Solid Tumors: Prospects and Challenges

2013 ◽  
Vol 31 (15) ◽  
pp. 1874-1884 ◽  
Author(s):  
Rodrigo Dienstmann ◽  
Jordi Rodon ◽  
Jordi Barretina ◽  
Josep Tabernero
Keyword(s):  
Solid Tumors ◽  
Cancer Progression ◽  
Cancer Genomics ◽  
Genomic Medicine ◽  
Genomic Data ◽  
Cost Effective ◽  
Assessment Model ◽  
Historical View ◽  
Systemic Treatments ◽  
Human Solid Tumors

Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the “one test-one drug” paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.

Sign in / Sign up

Export Citation Format

Share Document