The global governance of human cloning: the case of UNESCO

Since Dolly the Sheep was cloned in 1996, the question of whether human reproductive cloning should be banned or pursued has been the subject of international debate. Feelings run strong on both sides. In 2005, the United Nations adopted its Declaration on Human Cloning to try to deal with the issue. The declaration is ambiguously worded, prohibiting “all forms of human cloning inasmuch as they are incompatible with human dignity and the protection of human life”. It received only ambivalent support from UN member states. Given this unsatisfactory outcome, in 2008 UNESCO (the United Nations Educational, Scientific and Cultural Organization) set up a Working Group to investigate the possibility of a legally binding convention to ban human reproductive cloning. The Working Group was made up of members of the International Bioethics Committee, established in 1993 as part of UNESCO’s Bioethics Programme. It found that the lack of clarity in international law is unhelpful for those states yet to formulate national regulations or policies on human cloning. Despite this, member states of UNESCO resisted the idea of a convention for several years. This changed in 2015, but there has been no practical progress on the issue. Drawing on official records and first-hand observations at bioethics meetings, this article examines the human cloning debate at UNESCO from 2008 onwards, thus building on and advancing current scholarship by applying recent ideas on global governance to an empirical case. It concludes that, although human reproductive cloning is a challenging subject, establishing a robust global governance framework in this area may be possible via an alternative deliberative format, based on knowledge sharing and feasibility testing rather than the interest-based bargaining that is common to intergovernmental organizations and involving a wide range of stakeholders. This article is published as part of a collection on global governance

Human-animal chimeras for vaccine development: an endangered species or opportunity for the developing world?

<p>Abstract</p> <p>Background</p> <p>In recent years, the field of vaccines for diseases such as Human Immunodeficiency Virus (HIV) which take a heavy toll in developing countries has faced major failures. This has led to a call for more basic science research, and development as well as evaluation of new vaccine candidates. Human-animal chimeras, developed with a 'humanized' immune system could be useful to study infectious diseases, including many neglected diseases. These would also serve as an important tool for the efficient testing of new vaccine candidates to streamline promising candidates for further trials in humans. However, developing human-animal chimeras has proved to be controversial.</p> <p>Discussion</p> <p>Development of human-animal chimeras for vaccine development has been slowed down because of opposition by some philosophers, ethicists and policy makers in the west-they question the moral status of such animals, and also express discomfort about transgression of species barriers. Such opposition often uses a contemporary western world view as a reference point. Human-animal chimeras are often being created for diseases which cause significantly higher morbidity and mortality in the developing world as compared to the developed world. We argue in our commentary that given this high disease burden, we should look at socio-cultural perspectives on human-animal chimera like beings in the developing world. On examination, it's clear that such beings have been part of mythology and cultural descriptions in many countries in the developing world.</p> <p>Summary</p> <p>To ensure that important research on diseases afflicting millions like malaria, HIV, Hepatitis-C and dengue continues to progress, we recommend supporting human-animal chimera research for vaccine development in developing countries (especially China and India which have growing technical expertise in the area). The negative perceptions in some parts of the west about human-animal chimeras can be used as an opportunity for nurturing important vaccine development research in the developing world.</p

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

<p>Abstract</p> <p>Background</p> <p>Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets.</p> <p>Methods</p> <p>We have analyzed 8 publicly available gene expression data sets. A global approach, "gene set enrichment analysis" as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets.</p> <p>Results</p> <p>The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis.</p> <p>Conclusion</p> <p>By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may constitute new targets are identified.</p

Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries