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Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

The flashlamp-pumped, solid-state holmium:yttrium-aluminium-garnet (YAG) laser has been the laser of choice for use in ureteroscopic lithotripsy for the past 20 years. However, although the holmium laser works well on all stone compositions and is cost-effective, this technology still has several fundamental limitations. Newer laser technologies, including the frequency-doubled, double-pulse YAG (FREDDY), erbium:YAG, femtosecond, and thulium fibre lasers, have all been explored as potential alternatives to the holmium:YAG laser for lithotripsy. Each of these laser technologies is associated with technical advantages and disadvantages, and the search continues for the next generation of laser lithotripsy systems that can provide rapid, safe, and efficient stone ablation. New fibre-optic approaches for safer and more efficient delivery of the laser energy inside the urinary tract include the use of smaller-core fibres and fibres that are tapered, spherical, detachable or hollow steel, or have muzzle brake distal fibre-optic tips. These specialty fibres might provide advantages, including improved flexibility for maximal ureteroscope deflection, reduced cross section for increased saline irrigation rates through the working channel of the ureteroscope, reduced stone retropulsion for improved stone ablation efficiency, and reduced fibre degradation and burnback for longer fibre life.

The efficient healing of critical-sized bone defects using synthetic biomaterial-based strategies is promising but remains challenging as it requires the development of biomaterials that combine a 3D porous architecture and a robust biological activity. Bioactive glasses (BGs) are attractive candidates as they stimulate a biological response that favors osteogenesis and vascularization, but amorphous 3D porous BGs are difficult to produce because conventional compositions crystallize during processing. Here, we rationally designed a porous, strontium-releasing, bioactive glass-based scaffold (pSrBG) whose composition was tailored to deliver strontium and whose properties were optimized to retain an amorphous phase, induce tissue infiltration and encourage bone formation. The hypothesis was that it would allow the repair of a critical-sized defect in an ovine model with newly-formed bone exhibiting physiological matrix composition and structural architecture. Histological and histomorphometric analyses combined with indentation testing showed pSrBG encouraged near perfect bone-to-material contact and the formation of well-organized lamellar bone. Analysis of bone quality by a combination of Raman spectral imaging, small-angle X-ray scattering, X-ray fluorescence and focused ion beam-scanning electron microscopy demonstrated that the repaired tissue was akin to that of normal, healthy bone, and incorporated small amounts of strontium in the newly formed bone mineral. These data show the potential of pSrBG to induce an efficient repair of critical-sized bone defects and establish the importance of thorough multi-scale characterization in assessing biomaterial outcomes in large animal models.

We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter)., eLife digest Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.