Identifying the downstream effects of disease-associated single nucleotide polymorphisms (SNPs) is challenging: the causal gene is often unknown or it is unclear how the SNP affects the causal gene, making it difficult to design experiments that reveal functional consequences. To help overcome this problem, we performed the largest expression quantitative trait locus (eQTL) meta-analysis so far reported in non-transformed peripheral blood samples of 5,311 individuals, with replication in 2,775 individuals. We identified and replicated trans-eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Although we did not study specific patient cohorts, we identified trait-associated SNPs that affect multiple trans-genes that are known to be markedly altered in patients: for example, systemic lupus erythematosus (SLE) SNP rs49170141 altered C1QB and five type 1 interferon response genes, both hallmarks of SLE2-4. Subsequent ChIP-seq data analysis on these trans-genes implicated transcription factor IKZF1 as the causal gene at this locus, with DeepSAGE RNA-sequencing revealing that rs4917014 strongly alters 3’ UTR levels of IKZF1. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Biomechanical forces are emerging as critical regulators of embryogenesis, particularly in the developing cardiovascular system 1,2 . After initiation of the heartbeat in vertebrates, cells lining the ventral aspect of the dorsal aorta, the placental vessels, and the umbilical and vitelline arteries initiate expression of the transcription factor Runx1 (refs 3-5), a master regulator of haematopoiesis, and give rise to haematopoietic cells 4 . It remains unknown whether the biomechanical forces imposed on the vascular wall at this developmental stage act as a determinant of haematopoietic potential 6 . Here, using mouse embryonic stem cells differentiated in vitro, we show that fluid shear stress increases the expression of Runx1 in CD41 + c-Kit + haematopoietic progenitor cells 7 ,concomitantly augmenting their haematopoietic colony-forming potential. Moreover, we find that shear stress increases haematopoietic colony-forming potential and expression of haematopoietic markers in the paraaortic splanchnopleura/aorta-gonads-mesonephros of mouse embryos and that abrogation of nitric oxide, a mediator of shear-stress-induced signalling 8 , compromises haematopoietic potential in vitro and in vivo. Collectively, these data reveal a critical role for biomechanical forces in haematopoietic development.In the mouse, the first haemogenic areas appear in the yolk sac starting at day 7.5 of development (E7.5) 9 . After the establishment of circulation and the onset of vascular flow at day 8.5, additional haemogenic sites appear between day 9 and 10.5 as Runx1 + regions within

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Background We sought to validate a recently published risk algorithm for incident atrial fibrillation (AF) in independent cohorts and other race/ethnic groups. Methods We evaluated the performance of a Framingham Heart Study (FHS)-derived risk algorithm modified for 5-year incidence of AF in the FHS (n=4764 participants) and two geographically and ethnically diverse cohorts: AGES (Age, Gene/Environment Susceptibility-Reykjavik Study, n=4238), and CHS (Cardiovascular Health Study, n=5410 of whom 874 (16.2%) were African Americans (AA)); aged 45–95 years. The risk algorithm included age, sex, body mass index, systolic blood pressure, electrocardiographic PR-interval, hypertension treatment, and heart failure. Results We observed 1359 incident AF events in 100,074 person-years of follow-up. Unadjusted five-year event-rates differed by cohort (AGES 12.8 cases/1000 person-years; CHS whites 22.7 cases/1000 person-years; FHS 4.5 cases/1000 person-years) and race/ethnicity (CHS AA 18.4 cases/1000 person-years). The strongest risk factors in all samples were age and heart failure. The relative risks for incident AF associated with risk factors were comparable across cohorts and race groups. After recalibration for baseline incidence and risk factor distribution, the Framingham algorithm performed reasonably well in all samples (AGES C-statistic 0.67, 95% confidence interval 0.64–0.71; CHS whites, 0.68, 0.66–0.70; CHS AA 0.66, 0.61–0.71). Risk factors combined in the algorithm explained between 47.0% (AGES) and 63.6% (FHS) of the population attributable risk. Conclusions Risk of incident AF in community-dwelling whites and AA can be assessed reliably by routinely available and potentially modifiable clinical variables. Seven risk factors accounted for up to 64% percent of risk.

Renal function generally is assessed by measurement of GFR and urinary albumin excretion. Other intrinsic kidney functions, such as proximal tubular secretion, typically are not quantified. Tubular secretion of solutes is more efficient than glomerular filtration and a major mechanism for renal drug elimination, suggesting important clinical consequences of secretion dysfunction. Measuring tubular secretion as an independent marker of kidney function may provide insight into kidney disease etiology and improve prediction of adverse outcomes. We estimated secretion function by measuring secreted solute (hippurate, cinnamoylglycine, p-cresol sulfate, and indoxyl sulfate) clearance using liquid chromatography-tandem mass spectrometric assays of serum and timed urine samples in a prospective cohort study of 298 patients with kidney disease. We estimated GFR by mean clearance of creatinine and urea from the same samples and evaluated associations of renal secretion with participant characteristics, mortality, and CKD progression to dialysis. Tubular secretion rate modestly correlated with eGFR and associated with some participant characteristics, notably fractional excretion of electrolytes. Low clearance of hippurate or p-cresol sulfate associated with greater risk of death independent of eGFR (hazard ratio, 2.3; 95% confidence interval, 1.1 to 4.7; hazard ratio, 2.5; 95% confidence interval, 1.0 to 6.1, respectively). Hazards models also suggested an association between low cinnamoylglycine clearance and risk of dialysis, but statistical analyses did not exclude the null hypothesis. Therefore, estimates of proximal tubular secretion function correlate with glomerular filtration, but substantial variability in net secretion remains. The observed associations of net secretion with mortality and progression of CKD require confirmation.

Long-term visit-to-visit SBP variability was independently associated with a higher risk of subsequent mortality and MI but not stroke. More research is needed to determine the relationship of BP variability with cardiovascular risk and the clinical implications.

The Cerebrovascular Disease and its Consequences in American Indians (CDCAI) Study recruited surviving members of a 20-year, longitudinal, population-based cohort of American Indians focused on cardiovascular disease, its risk factors, and its consequences. The goal of the CDCAI Study is to characterize the burden, risk factors, and manifestations of vascular brain injury identified on cranial MRI. The CDCAI Study investigators enrolled 1,033 participants aged 60 and older from 11 American Indian communities and tribes in the Northern Plains, Southern Plains, and Southwestern United States. In addition to cranial MRI performed according to standardized protocols, participants underwent extensive medical interview, clinical examination, neurocognitive testing, physical function evaluation, electrocardiogram, and provided blood and urine specimens. Participants also self-administered questionnaires covering demographics, quality of life, and medical history. This report describes the design, implementation, and some of the unique challenges of this study and data collection.