Precision Diagnostics in Myeloid Malignancies: Development and Validation of a National Capture-Based Gene Panel.

Gene panel sequencing has become a common diagnostic tool for detecting somatically acquired mutations in myeloid neoplasms. However, many panels have restricted content, provide insufficient sensitivity levels, or lack clinically validated workflows. We here describe the development and validation of the Genomic Medicine Sweden myeloid gene panel (GMS-MGP), a capture-based 191 gene panel including mandatory genes in contemporary guidelines as well as emerging candidates. The GMS-MGP displayed uniform coverage across all targets, including recognized difficult GC-rich areas. The validation of 117 previously described somatic variants showed a 100% concordance with a limit-of-detection of a 0.5% variant allele frequency (VAF), achieved by utilizing error correction and filtering against a panel-of-normals. A national interlaboratory comparison investigating 56 somatic variants demonstrated highly concordant results in both detection rate and reported VAFs. In addition, prospective analysis of 323 patients analyzed with the GMS-MGP as part of standard-of-care identified clinically significant genes as well as recurrent mutations in less well-studied genes. In conclusion, the GMS-MGP workflow supports sensitive detection of all clinically relevant genes, facilitates novel findings, and is, based on the capture-based design, easy to update once new guidelines become available. The GMS-MGP provides an important step toward nationally harmonized precision diagnostics of myeloid malignancies.

From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.

The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.

Integrating a Polygenic Risk Score into a clinical setting would impact risk predictions in familial breast cancer.

BACKGROUND: Low-impact genetic variants identified in population-based genetic studies are not routinely measured as part of clinical genetic testing in familial breast cancer (BC). We studied the consequences of integrating an established Polygenic Risk Score (PRS) (BCAC 313, PRS313) into clinical sequencing of women with familial BC in Sweden. METHODS: We developed an add-on sequencing panel to capture 313 risk variants in addition to the clinical screening of hereditary BC genes. Index patients with no pathogenic variant from 87 families, and 1000 population controls, were included in comparative PRS calculations. Including detailed family history, sequencing results and tumour pathology information, we used BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.6 to estimate contralateral and lifetime risks without and with PRS313. RESULTS: Women with BC but no pathogenic variants in hereditary BC genes have a higher PRS313 compared with population controls (mean+0.78 SD, p<3e-9). Implementing PRS313 in the clinical risk estimation before their BC diagnosis would have changed the recommended follow-up in 24%-45% of women. CONCLUSIONS: Our results show the potential impact of incorporating PRS313 directly in the clinical genomic investigation of women with familial BC.

Genetic insights into resting heart rate and its role in cardiovascular disease.

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Novel pathological variants of NHP2 affect N-terminal domain flexibility, protein stability, H/ACA Ribonucleoprotein (RNP) complex formation and telomerase activity.

Telomere biology disorders (TBDs) are characterized by short telomeres, premature aging, bone marrow failure and cancer predisposition. Germline mutations in NHP2, encoding for one component of the telomerase cofactor H/ACA RNA binding complex together with Dyskerin, NOP10 and GAR1, have been previously reported in rare cases of TBDs. Here, we report two novel NHP2 variants (NHP2-A39T and NHP2-T44M) identified in a compound heterozygous patient affected by premature aging, bone marrow failure/myelodysplastic syndrome and gastric cancer. Although still able to support cell viability, both variants reduce the levels of hTR, the telomerase RNA component, and telomerase activity, expanding the panel of NHP2 pathological variants. Furthermore, both variants fail to be incorporated in the H/ACA RNA binding complex when in competition with wild-type endogenous NHP2, and the lack of incorporation causes their drastic proteasomal degradation. By RoseTTAFold prediction followed by molecular dynamics simulations, we reveal a dramatic distortion of residues 33-41, which normally position on top of the NHP2 core, as the main defect of NHP2-A39T, and high flexibility and the misplacement of the N-terminal region (residues 1-24) in NHP2-T44M and, to a lower degree, in NHP2-A39T. Because deletion of amino acids 2-24 causes a reduction in NHP2 levels only in the presence of wild-type NHP2, while deletion of amino acids 2-38 completely disrupts NHP2 stability, we propose that the two variants are mis-incorporated into the H/ACA binding complex due to the altered dynamics of the first 23 amino acids and/or the distortion of the residues 25-41 loop.

Somatic Exonic Deletions in RUNX1 Constitutes a Novel Recurrent Genomic Abnormality in Acute Myeloid Leukemia.

PURPOSE: In acute myeloid leukemia (AML), somatic mutations (commonly missense, nonsense, and frameshift indels) in RUNX1 are associated with a dismal clinical outcome. Inherited RUNX1 mutations cause familial platelet disorder. As approximately 5%-10% of germline RUNX1 mutations are large exonic deletions, we hypothesized that such exonic RUNX1 aberrations may also be acquired during the development of AML. EXPERIMENTAL DESIGN: Sixty patients with well-characterized AML were analyzed with multiplex ligation-dependent probe amplification (n = 60), microarray (n = 11), and/or whole-genome sequencing (n = 8). RESULTS: In total, 25 (42% of the cohort) RUNX1-aberrant patients (defined by the presence of classical mutations and/or exonic deletions) were identified. Sixteen patients (27%) carried only exonic deletions, 5 (8%) carried classical mutations, and 4 (7%) carried both exonic deletions and mutations. No significant difference was observed between patients with classical RUNX1 mutations and RUNX1 exonic deletions in median overall survival (OS, 53.1 vs. 38.8 months, respectively, P = 0.63). When applying the European Leukemia Net (ELN) classification including the RUNX1-aberrant group, 20% of the patients initially stratified as intermediate-risk (5% of the whole cohort) were reassigned to the high-risk group, which improved the performance of ELN classification regarding OS between intermediate- and high-risk groups (18.9 vs. 9.6 months, P = 0.09). CONCLUSIONS: Somatic RUNX1 exonic deletions constitute a novel recurrent aberration in AML. Our findings have important clinical implications regarding AML classification, risk stratification, and treatment decision. Moreover, they argue in favor of further investigating such genomic aberrations not only in RUNX1 but also in other genes implicated in cancer biology and management. See related commentary by Chakraborty and Stengel, p. 2742.

Five Percent Variant Allele Frequency Is a Reliable Reporting Threshold for TP53 Variants Detected by Next Generation Sequencing in Chronic Lymphocytic Leukemia in the Clinical Setting.

The clinical significance of small TP53 clones detected with next generation sequencing (NGS) in chronic lymphocytic leukemia is an issue of active debate. According to the official guidelines, treatment decisions should be guided only by variants with variant allele frequency (VAF) ≥10%. We present data on 325 consecutive patients with chronic lymphocytic leukemia analyzed with NGS. In total 47 pathogenic/likely pathogenic (P/LP), TP53 variants were detected in 26 patients (8%). Eleven of these (23%) were in the 5% to 10% VAF range and reported according to our institutional policy. All TP53 variants in the 5% to 10% VAF range were confirmed (100% concordance) with a second NGS panel. Our results where further validated with the performance of Sanger sequencing and digital droplet PCR (ddPCR). In 12 patients with available fluorescence in situ hybridization data and TP53 mutations within 5% to 10% VAF, deletion of chromosome 17p (del(17p)) was detectable in only 1 patient. We propose a robust diagnostic algorithm, which allows the safe detection and reporting of TP53 variants with VAF down to 5% in the clinical setting. Our study provides evidence that NGS is equally potent to detect variants with VAF 5% to 10% compared to those with VAF 10% to 15%, highlighting the urgent need for harmonization of NGS methodologies across diagnostic laboratories.

PD-L1 and IDO1 are potential targets for treatment in patients with primary diffuse large B-cell lymphoma of the CNS.

BACKGROUND: Programmed cell death 1 (PD-1) and its ligands PD-L1 and PD-L2, as well as Indoleamine 2,3-deoxygenase (IDO1) can be expressed both by tumor and microenvironmental cells and are crucial for tumor immune escape. We aimed to evaluate the role of PD-1, its ligands and IDO1 in a cohort of patients with primary diffuse large B-cell lymphoma of the CNS (PCNSL). MATERIAL AND METHODS: Tissue microarrays (TMAs) were constructed in 45 PCNSL cases. RNA extraction from whole tissue sections and RNA sequencing were successfully performed in 33 cases. Immunohistochemical stainings for PD-1, PD-L1/paired box protein 5 (PAX-5), PD-L2/PAX-5 and IDO1, and Epstein-Barr virus encoding RNA (EBER) in situ hybridization were analyzed. RESULTS: High proportions of PD-L1 and PD-L2 positive tumor cells were observed in 11% and 9% of cases, respectively. High proportions of PD-L1 and PD-L2 positive leukocytes were observed in 55% and 51% of cases, respectively. RNA sequencing revealed that gene expression of IDO1 was high in patients with high proportion of PD-L1 positive leukocytes (p = .01). Protein expression of IDO1 in leukocytes was detected in 14/45 cases, in 79% of these cases a high proportion of PD-L1 positive leukocytes was observed. Gene expression of IDO1 was high in EBER-positive cases (p = .0009) and protein expression of IDO1 was detected in five of six EBER-positive cases. CONCLUSION: Our study shows a significant association between gene and protein expression of IDO1 and protein expression of PD-L1 in the tumor microenvironment of PCNSL, possibly of importance for prediction of response to immunotherapies.

Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus.

BACKGROUND: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). METHODS: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). RESULTS: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. CONCLUSIONS: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.

Arteria: An automation system for a sequencing core facility.

BACKGROUND: In recent years, nucleotide sequencing has become increasingly instrumental in both research and clinical settings. This has led to an explosive growth in sequencing data produced worldwide. As the amount of data increases, so does the need for automated solutions for data processing and analysis. The concept of workflows has gained favour in the bioinformatics community, but there is little in the scientific literature describing end-to-end automation systems. Arteria is an automation system that aims at providing a solution to the data-related operational challenges that face sequencing core facilities. FINDINGS: Arteria is built on existing open source technologies, with a modular design allowing for a community-driven effort to create plug-and-play micro-services. In this article we describe the system, elaborate on the underlying conceptual framework, and present an example implementation. Arteria can be reduced to 3 conceptual levels: orchestration (using an event-based model of automation), process (the steps involved in processing sequencing data, modelled as workflows), and execution (using a series of RESTful micro-services). This creates a system that is both flexible and scalable. Arteria-based systems have been successfully deployed at 3 sequencing core facilities. The Arteria Project code, written largely in Python, is available as open source software, and more information can be found at https://arteria-project.github.io/ . CONCLUSIONS: We describe the Arteria system and the underlying conceptual framework, demonstrating how this model can be used to automate data handling and analysis in the context of a sequencing core facility.

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes.

Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10-8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.

Genome-wide meta-analysis identifies novel determinants of circulating serum progranulin.

Progranulin is a secreted protein with important functions in processes including immune and inflammatory response, metabolism and embryonic development. The present study aimed at identification of genetic factors determining progranulin concentrations. We conducted a genome-wide association meta-analysis for serum progranulin in three independent cohorts from Europe: Sorbs (N = 848) and KORA (N = 1628) from Germany and PPP-Botnia (N = 335) from Finland (total N = 2811). Single nucleotide polymorphisms (SNPs) associated with progranulin levels were replicated in two additional German cohorts: LIFE-Heart Study (Leipzig; N = 967) and Metabolic Syndrome Berlin Potsdam (Berlin cohort; N = 833). We measured mRNA expression of genes in peripheral blood mononuclear cells (PBMC) by micro-arrays and performed mRNA expression quantitative trait and expression-progranulin association studies to functionally substantiate identified loci. Finally, we conducted siRNA silencing experiments in vitro to validate potential candidate genes within the associated loci. Heritability of circulating progranulin levels was estimated at 31.8% and 26.1% in the Sorbs and LIFE-Heart cohort, respectively. SNPs at three loci reached study-wide significance (rs660240 in CELSR2-PSRC1-MYBPHL-SORT1, rs4747197 in CDH23-PSAP and rs5848 in GRN) explaining 19.4%/15.0% of the variance and 61%/57% of total heritability in the Sorbs/LIFE-Heart Study. The strongest evidence for association was at rs660240 (P = 5.75 × 10-50), which was also associated with mRNA expression of PSRC1 in PBMC (P = 1.51 × 10-21). Psrc1 knockdown in murine preadipocytes led to a consecutive 30% reduction in progranulin secretion. In conclusion, the present meta-GWAS combined with mRNA expression identified three loci associated with progranulin and supports the role of PSRC1 in the regulation of progranulin secretion.

Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes. METHODS & FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants. CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

The Genetic Landscape of Renal Complications in Type 1 Diabetes.

Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10-5) and the risk of type 2 diabetes (P=6.1×10-4) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10-6), and pentose and glucuronate interconversions (P=3.0×10-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

Excess maternal transmission of variants in the THADA gene to offspring with type 2 diabetes.

AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) have identified more than 65 genetic loci associated with risk of type 2 diabetes. However, the contribution of distorted parental transmission of alleles to risk of type 2 diabetes has been mostly unexplored. Our goal was therefore to search for parent-of-origin effects (POE) among type 2 diabetes loci in families. METHODS: Families from the Botnia study (n = 4,211, 1,083 families) were genotyped for 72 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes and assessed for POE on type 2 diabetes. The family-based Hungarian Transdanubian Biobank (HTB) (n = 1,463, >135 families) was used to replicate SNPs showing POE. Association of type 2 diabetes loci within families was also tested. RESULTS: Three loci showed nominal POE, including the previously reported variants in KCNQ1, for type 2 diabetes in families from Botnia (rs2237895: p POE = 0.037), which can be considered positive controls. The strongest POE was seen for rs7578597 SNP in the THADA gene, showing excess transmission of the maternal risk allele T to diabetic offspring (Botnia: p POE = 0.01; HTB p POE = 0.045). These data are consistent with previous evidence of allelic imbalance for expression in islets, suggesting that the THADA gene can be imprinted in a POE-specific fashion. Five CpG sites, including those flanking rs7578597, showed differential methylation between diabetic and non-diabetic donor islets. CONCLUSIONS/INTERPRETATION: Taken together, the data emphasise the need for genetic studies to consider from which parent an offspring has inherited a susceptibility allele.

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research.

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.

Glucose-Dependent Insulinotropic Polypeptide Stimulates Osteopontin Expression in the Vasculature via Endothelin-1 and CREB.

Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone with extrapancreatic effects beyond glycemic control. Here we demonstrate unexpected effects of GIP signaling in the vasculature. GIP induces the expression of the proatherogenic cytokine osteopontin (OPN) in mouse arteries via local release of endothelin-1 and activation of CREB. Infusion of GIP increases plasma OPN concentrations in healthy individuals. Plasma endothelin-1 and OPN concentrations are positively correlated in patients with critical limb ischemia. Fasting GIP concentrations are higher in individuals with a history of cardiovascular disease (myocardial infarction, stroke) when compared with control subjects. GIP receptor (GIPR) and OPN mRNA levels are higher in carotid endarterectomies from patients with symptoms (stroke, transient ischemic attacks, amaurosis fugax) than in asymptomatic patients, and expression associates with parameters that are characteristic of unstable and inflammatory plaques (increased lipid accumulation, macrophage infiltration, and reduced smooth muscle cell content). While GIPR expression is predominantly endothelial in healthy arteries from humans, mice, rats, and pigs, remarkable upregulation is observed in endothelial and smooth muscle cells upon culture conditions, yielding a "vascular disease-like" phenotype. Moreover, the common variant rs10423928 in the GIPR gene is associated with increased risk of stroke in patients with type 2 diabetes.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

The impact of low-frequency and rare variants on lipid levels.

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.