Validating metal-organic framework nanoparticles for their nanosafety in diverse biomedical applications.

Metal-organic frameworks (MOFs) are promising platforms for the synthesis of nanoparticles for diverse medical applications. Their fundamental design principles allow for significant control of the framework architecture and pore chemistry, enabling directed functionalization for nanomedical applications. However, before applying novel nanomaterials to patients, it is imperative to understand their potential health risks. In this study, the nanosafety of different MOF nanoparticles is analyzed comprehensively for diverse medical applications. The authors first evaluate the effects of MOFs on human endothelial and mouse lung cells, which constitute a first line of defense upon systemic blood-mediated and local lung-specific applications of nanoparticles. Second, we validated these MOFs for multifunctional surface coatings of dental implants using human gingiva fibroblasts. Moreover, biocompatibility of MOFs is assessed for surface coating of nerve guidance tubes using human Schwann cells and rat dorsal root ganglion cultures. The main finding of this study is that the nanosafety and principal suitability of our MOF nanoparticles as novel agents for drug delivery and implant coatings strongly varies with the effector cell type. We conclude that it is therefore necessary to carefully evaluate the nanosafety of MOF nanomaterials with respect to their particular medical application and their interacting primary cell types, respectively

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. 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) 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 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 <sup>1</sup> . 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 <sup>2</sup> ) 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