Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.</p

Modelo Dual de Educación con sabor latino

Latinoamérica se encuentra en un momento decisivo de adaptación a nuevas realidades económicas y políticas globales. Los países de la región comparten muchos retos. Por ello, es importante que compartan también soluciones exitosas. Ello no quiere decir que haya sido fácil trasplantar el modelo alemán al contexto latinoamericano, ni que lo que ha logrado con éxito ser implementado por la red DHLA sea fácil en otros países de la región. Pero justamente ahí radica la riqueza de este libro. Sus lectores, estudiosos de la educación, hacedores de políticas, entre otros, encontrarán cómo se hizo la adaptación “con sabor latino”, trasgrediendo aquellas apuestas de copiar al pie de la letra modelos foráneos. Ahí está el secreto. En cada institución de cada país se incursionó en este mundo de la educación dual desde las necesidades particulares de sus economías y con la idiosincrasia e instituciones locales. Este libro es una fotografía de casi dos décadas. Es un recorrido por las instituciones que han asumido el compromiso de este modelo en beneficio de las nuevas generaciones de profesionales y del empresariado. También se hace un reconocimiento a quienes han creído en el modelo dual, por encima de la tradición educativa y de obstáculos de todo orden

Summary statistics of UK Biobank blood pressure genome-wide association studies (GWAS) using 337,422 unrelated white European individuals

Three blood pressure traits were analysed: systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP; the difference between SBP and DBP). Mean SBP and DBP values from automated values were calculated. After calculating blood pressure values, SBP and DBP were adjusted for medication use by adding 15 and 10 mm Hg to their values, respectively, for individuals reported to be taking blood pressure–lowering medication.For the UK Biobank genome-wide association studies (GWAS), we performed linear mixed model (LMM) association testing under an additive genetic model of the three continuous, medication-adjusted blood pressure traits (SBP, DBP, PP) for all measured and imputed genetic variants (Data Field-22828) with minor allele frequency (MAF) &gt;=1% and imputation score&gt;=0.3 in dosage format using the BOLT-LMM (v2.4.1) software. Covariates were age, age2, sex, BMI, genotyping array and 10PCs. Genomic inflation was not applied to the GWAS summary statistics.Sample QC was described below:We included up to 337,422 individuals from UK Biobank for the purpose of this project. We followed UK Biobank sample-based quality control criteria (Nature 2018;562:203-209); excluded were samples/individuals based on the following criteria: (i) outliers in heterozygosity and missingness, (ii) self-reported gender not consistent with genetic data inferred gender (ii) sample call rate (computed using probesets internal to Affymetrix