Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu

Bone 13C/12C ratios reflect (palaeo‐)climatic variations

Stable isotope ratios of hydrogen, oxygen, nitrogen and carbon can serve as (palaeo-) environmental indicators. 2H and 18O have the clearest relationship with precipitation and temperature, while the sensitivity of carbon is thought to be far less pronounced, and understanding is not complete. Carbon isotopic variation in ecosystems is mainly due to photosynthesis in plants, and passed on in the foodweb without much overall modification (this enables palaeodiet reconstructions using archaeological bone). Using radiocarbon databases which also contain 13C data, we have compared a number of European countries for geographical variation in 13C/12C ratio of archaeological wood, charcoal and bone samples. We find similar trends for all three materials. A significant trend from northwestern to southern Europe exists in the plant samples, which we relate to climatic differences influencing 13C/12C ratios during carbon fixation. This shift passes through the food web, and is thus found in the bone samples, which makes it possible to use accumulated bone stable isotopic data for palaeoclimatic reconstructions.

Autoantibodies in interstitial lung diseases

The role of autoantibody testing for patients with interstitial lung disease is an evolving area. Recent guidelines recommend routine anti-nuclear antibodies, rheumatoid factor, and anti-citrullinated cyclic peptide antibody testing for patients undergoing diagnostic evaluation for interstitial lung disease, with further autoantibody testing reserved for selected cases guided by rheumatological features. Even this approach may miss patients with clinically significant autoantibodies when interstitial lung disease is the dominant or first manifestation of autoimmune disease. We retrospectively performed autoimmune serology in a clinically well characterised cohort of interstitial lung disease patients. Using stored serum, additional testing was performed to ensure all patients had complete autoantibody profiles including anti-nuclear antibodies, extractable nuclear antigen antibodies, double-stranded DNA antibodies, rheumatoid factor, anti-citrullinated cyclic peptide antibodies, anti-neutrophil cytoplasmic antibodies, and myositis antibodies. Eighty patients with interstitial lung disease, and available stored serum, were assessed. Mean age at interstitial lung disease diagnosis was 65.2 years and 42 patients were male. Positive autoimmune serology was found in 56 of 80 (70.0%) patients; the most common positive result was anti-nuclear antibodies (n=34; 42.5%). Myositis antibodies were detected in 13 of 80 (16.2%) patients. Four (5%) patients had elevated anti-citrullinated cyclic peptide antibodies, and two (2.5%) patients had detectable myeloperoxidase antibodies. Eleven (13.7%) patients with negative anti-nuclear antibodies had other significant disease associated autoantibodies. An extended panel of autoantibody testing may detect cases of connective tissue disease associated interstitial lung disease, regardless of clinical or radiological subtype, and prior to extra-pulmonary manifestations of systemic autoimmunity

Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platf

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background

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