Development of a Polygenic Risk Score to Predict Diverticulitis.

BACKGROUND: Despite its prevalence and associated morbidity, we remain limited in our ability to predict the course of a patient with diverticular disease. Although several clinical and genetic risk factors have been identified, we do not know how these factors relate to one another. OBJECTIVE: Our aim was to determine whether a polygenic risk score could improve risk prediction for diverticulitis and recurrent diverticulitis compared with a model using only clinical factors. DESIGN: This is an observational study. SETTING: The study examines the predictive ability of a polygenic risk score for diverticulitis developed using prior genome-wide association studies and validated using the MyCode biobank. PATIENTS: This study included patients of European ancestry in the Geisinger Health System who were enrolled in the MyCode Community Health biobanking program. MAIN OUTCOME MEASURES: The ability of a polygenic risk score to predict diverticulosis, diverticulitis, and recurrent diverticulitis was the main outcome measure of this study. RESULTS: A total of 60,861 patients were included, of whom 9912 (16.3%) had diverticulosis or diverticulitis (5015 with diverticulosis and 4897 with diverticulitis). When divided into deciles, our polygenic risk score stratified patients by risk of both diverticulosis and diverticulitis with a 2-fold difference in disease risk between the highest and lowest deciles for diverticulitis and a 4.8-fold difference for recurrent complicated diverticulitis. When compared with clinical factors alone, our polygenic risk score was able to improve risk prediction of recurrent diverticulitis. LIMITATIONS: Our population is largely located in a single geographic region and were classified by disease status, using international classification of diseases codes. CONCLUSIONS: This predictive model stratifies patients based on genetic risk for diverticular disease. The increased frequency of recurrent disease in our high-risk patients suggests that a polygenic risk score, in addition to other factors, may help guide the discussion regarding surgical intervention. See Video Abstract . DESARROLLO DE UNA PUNTUACIN DE RIESGO POLIGNICO PARA PREDECIR LA DIVERTICULITIS: ANTECEDENTES:A pesar de su prevalencia y morbilidad asociada, nuestra capacidad para predecir el curso en un paciente con enfermedad diverticular sigue siendo limitada. Si bien se han identificado varios factores de riesgo clínicos y genéticos, no sabemos cómo se relacionan estos factores entre sí.OBJETIVO:Determinar si una puntuación de riesgo poligénico podría mejorar la predicción del riesgo de diverticulitis y diverticulitis recurrente en comparación con un modelo que utiliza solo factores clínicos.DISEÑO:Un estudio observacional que examina la capacidad predictiva de una puntuación de riesgo poligénico para la diverticulitis desarrollada usando estudios previos de asociación amplia del genoma y validada usando el biobanco MyCode.ÁMBITOS Y PACIENTES:Pacientes de ascendencia europea en el Sistema de Salud Geisinger que estaban inscritos en el programa de biobancos MyCode Community Health.PRINCIPALES MEDIDAS DE VALORACIÓN:La capacidad de una puntuación de riesgo poligénico para predecir diverticulosis, diverticulitis y diverticulitis recurrente.RESULTADOS:Se incluyeron un total de 60.861 pacientes, de los cuales 9.912 (16,3%) presentaban diverticulosis o diverticulitis (5.015 con diverticulosis y 4.897 con diverticulitis). Cuando se dividió en deciles, nuestra puntuación de riesgo poligénico estratificó a los pacientes según el riesgo de diverticulosis y diverticulitis con una diferencia de 2 veces en el riesgo de enfermedad entre los deciles más alto y más bajo para diverticulitis y una diferencia de 4,8 veces para diverticulitis complicada recurrente. En comparación con los factores clínicos solos, nuestra puntuación de riesgo poligénico pudo mejorar la predicción del riesgo de diverticulitis recurrente.LIMITACIONES:Nuestra población se encuentra en gran parte en una sola región geográfica y se clasificó por estado de enfermedad utilizando códigos de clasificación internacional de enfermedades.CONCLUSIONES:Este modelo predictivo estratifica a los pacientes en función del riesgo genético de enfermedad diverticular. La mayor frecuencia de enfermedad recurrente en nuestros pacientes de alto riesgo sugiere que un puntaje de riesgo poligénico, además de otros factores, puede ayudar a guiar la discusión sobre la intervención quirúrgica. (Traducción- Dr. Ingrid Melo ).

Genomic profiling of human vascular cells identifies TWIST1 as a causal gene for common vascular diseases.

Genome-wide association studies have identified multiple novel genomic loci associated with vascular diseases. Many of these loci are common non-coding variants that affect the expression of disease-relevant genes within coronary vascular cells. To identify such genes on a genome-wide level, we performed deep transcriptomic analysis of genotyped primary human coronary artery smooth muscle cells (HCASMCs) and coronary endothelial cells (HCAECs) from the same subjects, including splicing Quantitative Trait Loci (sQTL), allele-specific expression (ASE), and colocalization analyses. We identified sQTLs for TARS2, YAP1, CFDP1, and STAT6 in HCASMCs and HCAECs, and 233 ASE genes, a subset of which are also GTEx eGenes in arterial tissues. Colocalization of GWAS association signals for coronary artery disease (CAD), migraine, stroke and abdominal aortic aneurysm with GTEx eGenes in aorta, coronary artery and tibial artery discovered novel candidate risk genes for these diseases. At the CAD and stroke locus tagged by rs2107595 we demonstrate colocalization with expression of the proximal gene TWIST1. We show that disrupting the rs2107595 locus alters TWIST1 expression and that the risk allele has increased binding of the NOTCH signaling protein RBPJ. Finally, we provide data that TWIST1 expression influences vascular SMC phenotypes, including proliferation and calcification, as a potential mechanism supporting a role for TWIST1 in CAD.

Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver.

Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory elements of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the effects of genetic variation on histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 74 GWAS loci that have been associated with at least one complex phenotype. Our results reveal a repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.

Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis.

Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07-1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5-7%, lowest risk quartile) to 41% (95%CI 33-49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy.

A Genome-First Approach to Estimate Prevalence of Germline Pathogenic Variants and Risk of Pancreatic Cancer in Select Cancer Susceptibility Genes.

Patients with germline pathogenic variants (GPV) in cancer predisposition genes are at increased risk of pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer. The genes most frequently found to harbor GPV in unselected PDAC cases are ATM, BRCA1, BRCA2, CDKN2A, CHEK2, and PALB2. However, GPV prevalence and gene-specific associations have not been extensively studied in the general population. To further explore these associations, we analyzed genomic and phenotypic data obtained from the UK Biobank (UKB) and Geisinger MyCode Community Health Initiative (GHS) cohorts comprising 200,600 and 175,449 participants, respectively. We estimated the frequency and calculated relative risks (RRs) of heterozygotes in both cohorts and a subset of individuals with PDAC. The combined frequency of heterozygous carriers of GPV in the general population ranged from 1.22% for CHEK2 to 0.05% for CDKN2A. The frequency of GPV in PDAC cases varied from 2.38% (ATM) to 0.19% (BRCA1 and CDKN2A). The RRs of PDAC were elevated for all genes except for BRCA1 and varied widely by gene from high (ATM) to low (CHEK2, BRCA2). This work expands our understanding of the frequencies of GPV heterozygous carriers and associations between PDAC and GPV in several important PDAC susceptibility genes.

The role of resting myocardial blood flow and myocardial blood flow reserve as a predictor of major adverse cardiovascular outcomes.

Cardiac perfusion PET is increasingly used to assess ischemia and cardiovascular risk and can also provide quantitative myocardial blood flow (MBF) and flow reserve (MBFR) values. These have been shown to be prognostic biomarkers of adverse outcomes, yet MBF and MBFR quantification remains underutilized in clinical settings. We compare MBFR to traditional cardiovascular risk factors in a large and diverse clinical population (60% African-American, 35.3% Caucasian) to rank its relative contribution to cardiovascular outcomes. Major adverse cardiovascular events (MACE), including unstable angina, non-ST and ST-elevation myocardial infarction, stroke, and death, were assessed for consecutive patients who underwent rest-dipyridamole stress 82Rb PET cardiac imaging from 2012-2015 at the Hospital of the University of Pennsylvania (n = 1283, mean follow-up 2.3 years). Resting MBF (1.1 ± 0.4 ml/min/g) was associated with adverse cardiovascular outcomes. MBFR (2.1 ± 0.8) was independently and inversely associated with MACE. Furthermore, MBFR was more strongly associated with MACE than both traditional cardiovascular risk factors and the presence of perfusion defects in regression analysis. Decision tree analysis identified MBFR as superior to established cardiovascular risk factors in predicting outcomes. Incorporating resting MBF and MBFR in CAD assessment may improve clinical decision making.

Cell-specific post-transcriptional regulation of γ-synuclein gene by micro-RNAs.

γ-Synuclein is a member of the synucleins family of small proteins, which consists of three members:α, ß- and γ-synuclein. γ-Synuclein is abnormally expressed in a high percentage of advanced and metastatic tumors, but not in normal or benign tissues. Furthermore, γ-synuclein expression is strongly correlated with disease progression, and can stimulate proliferation, induce invasion and metastasis of cancer cells. γ-Synuclein transcription is regulated basically through the binding of AP-1 to specific sequences in intron 1. Here we show that γ-synuclein expression may be also regulated by micro RNAs (miRs) on post-transcriptional level. According to prediction by several methods, the 3'-untranslated region (UTR) of γ-synuclein gene contains targets for miRs. Insertion of γ-synuclein 3'-UTR downstream of the reporter luciferase (LUC) gene causes a 51% reduction of LUC activity after transfection into SKBR3 and Y79 cells, confirming the presence of efficient targets for miRs in this fragment. Expression of miR-4437 and miR-4674 for which putative targets in 3'-UTR were predicted caused a 61.2% and 60.1% reduction of endogenous γ-synuclein expression confirming their role in gene expression regulation. On the other hand, in cells overexpressing γ-synuclein no significant effect of miRs on γ-synuclein expression was found suggesting that miRs exert their regulatory effect only at low or moderate, but not at high level of γ-synuclein expression. Elevated level of γ-synuclein differentially changes the level of several miRs expression, upregulating the level of some miRs and downregulating the level of others. Three miRs upregulated as a result of γ-synuclein overexpression, i.e., miR-885-3p, miR-138 and miR-497 have putative targets in 3'-UTR of the γ-synuclein gene. Some of miRs differentially regulated by γ-synuclein may modulate signaling pathways and cancer related gene expression. This study demonstrates that miRs might provide cell-specific regulation of γ-synuclein expression and set the stage to further evaluate their role in pathophysiological processes.