DNA variants affecting chromatin structure are key to the genetic architecture of obsessive compulsive disorder

Since completion of the draft sequence of the human genome in 2000, the landscape of biomedical research has undergone a rapid transformation. Growing knowledge of genome structure and variation has spawned the development of technologies that allow researchers to study thousands of genes, transcripts, and proteins simultaneously. This has expanded biomedical science beyond reductionist approaches that test the function of individual genes to less biased approaches that study the behavior of many or all genes in homeostasis and disease. Such studies have been grouped under the broad label of functional genomics, which can be defined as the branch of biology that seeks to uncover the properties and function of the entirety of the genes and gene products of an organism.1 Functional genomics is fueling an explosion of new insights in biology and medicine, and many of these insights were completely unanticipated. Because these advances have begun to influence clinical practice,2,3 physicians will be expected to understand the potential uses and limitations of functional genomics in clinical settings. The purpose of this review is to provide a conceptual overview of functional genomics applied to the practice of cardiovascular medicine. We begin with a review of commonly used terms and approaches and then describe examples of their use for screening, diagnosis, and treatment selection in clinical cardiology. We also highlight emerging trends and speculate about where the field is headed in the near term. Although some predictions will be overly optimistic and some major advances unanticipated, we hope this review will help prepare cardiologists for their role in the application of genome science to the diagnosis and treatment of disease. This review is part of a series that introduces several related areas of cardiovascular genetics and genomics.4 We refer to these other contributions to guide further reading …

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder. Prior research suggests that genetic susceptibility and environmental exposures, such as maternal preeclampsia (PE) during pregnancy, play key roles in ASD pathogenesis. However, the specific effects of the interaction between genetic and environmental factors on ASD phenotype severity remain unclear. This study aims to investigate how interactions between de novo variants (DNVs) and common variants in individual genomes and PE exposure affect ASD symptom severity by constructing a gene-environment model. Phenotypic data were obtained from the Simons Simplex Collection (SSC) database for idiopathic ASD patients aged 4-18. Subjects were divided based on maternal PE status: PE+ (exposed) and PE- (unexposed) groups. Those without DNVs were divided into DNV-PE+ and DNV-PE- groups, and those with DNVs into DNV+PE+ and DNV+PE- groups. Based on polygenic risk scores (PRS), subjects below the median were classified into PRSlowPE+ and PRSlowPE- groups, and those at or above the median into PRShighPE+ and PRShighPE- groups. Core ASD phenotypic assessed included adaptive and cognitive abilities, social reciprocity, language and communication skills, and repetitive behaviors. Adaptive and cognitive abilities were scored using adaptive behavior composite scores from the Vineland Adaptive Behavior Scales, Second Edition (VABS-II), along with verbal intelligence quotient (VIQ) and nonverbal intelligence quotient (NVIQ) scores from the SSC database. Social reciprocity abilities were measured using the social domain scores from the Autism Diagnostic Interview-Revised (ADI-R SD), social affective domain scores from the Autism Diagnostic Observation Schedule (ADOS SA), and normalized scores from the Social Responsiveness Scale (SRS). Language and communication abilities were assessed through verbal communication domain (ADI-R VC), nonverbal communication domain (ADI-R NVC) scores from ADI-R, and the communication and social domain scores from ADOS (ADOS CS). Repetitive behaviors were measured using the restricted and repetitive behaviors domain scores from ADI-R (ADI-R RRB), the repetitive domain scores from ADOS (ADOS REP), and the overall scores from the Repetitive Behavior Scale-Revised (RBS-R). Linear regression models were constructed to explore the impact of PE exposure and its interaction with individual genomes (including DNVs and common variants) on core ASD phenotypes. Additionally, ASD candidate genes associated with DNVs underwent gene ontology (GO) enrichment analysis via Metascape, and temporal and spatial gene expression patterns were examined using RNA sequencing (RNA-seq) data from the BrainSpan database. A total of 2 439 ASD patients with recorded DNV information and confirmed PE exposure status were included, with 146 in the PE+ group and 2 293 in the PE- group. There was a trend toward differences between these two groups in SRS (β=2.01, P=0.08) and ADI-R NVC (β=-0.62, P=0.09). Among the 2 439 participants, there were 1 454 in the DNV-PE- group, 90 in the DNV-PE+ group, 839 in the DNV+PE- group, and 56 in the DNV+PE+ group. Analysis of the main effect of PE exposure showed significant impacts on SRS (β=3.71, P=0.01) and RBS-R (β=4.54, P=0.05). Interaction analysis between DNVs and PE exposure revealed a trend toward significance in SRS (β=-4.17, P=0.06). In the 2 236 participants with available PRS data, there were 1 033 in the PRSlowPE- group, 72 in the PRSlowPE+ group, 1 069 in the PRShighPE- group, and 62 in the PRShighPE+ group. Analysis of the main effect of PE exposure showed significant impacts on SRS (β=4.32, P<0.001) and RBS-R (β=5.87, P=0.02). The interaction between PRS and PE exposure showed significant effects on SRS (β=-4.90, P=0.03) and ADI-R NVC (β=-1.43, P=0.04), with trends in NVIQ (β=9.61, P=0.08) and RBS-R (β=-6.20, P=0.08). Additionally, DNV-enriched genes in PE-exposed patients were associated with regulatory of epithelial-to-mesenchymal transition and DNA-binding transcription factor activity. Temporal and spatial expression pattern analysis indicated that genes enriched in these regulatory processes showed higher expression levels prenatally compared to postnatally. PE exposure, an environmental factor influencing ASD, is associated with increased ASD symptom severity. The interaction of PE exposure with genetic factors is crucial in modulating ASD phenotypes. Among PE-exposed individuals, ASD patients with high genetic risk for common variants may show improvements in social reciprocity and communication skills. In contrast, while DNVs may also aid in symptom improvement, their impact is less pronounced than that of common variants. These differences suggest that under similar PE exposure conditions, ASD patients with DNVs or high-risk common variants may exhibit varying degrees of symptom changes. ASD pathology research should consider the combined influence of genetic and environmental factors.

BackgroundIn the United States, about 3 million people have autism spectrum disorder (ASD), and around 1 out of 59 children are diagnosed with ASD. People with ASD have characteristic social communication deficits and repetitive behaviors. The causes of this disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Detecting ASD as early as possible is desirable because early detection of ASD enables timely interventions in children with ASD. Identification of ASD based on objective pathogenic mutation screening is the major first step toward early intervention and effective treatment of affected children.ObjectiveRecent investigation interrogated genomics data for detecting and treating autism disorders, in addition to the conventional clinical interview as a diagnostic test. Since deep neural networks perform better than shallow machine learning models on complex and high-dimensional data, in this study, we sought to apply deep learning to genetic data obtained across thousands of simplex families at risk for ASD to identify contributory mutations and to create an advanced diagnostic classifier for autism screening.MethodsAfter preprocessing the genomics data from the Simons Simplex Collection, we extracted top ranking common variants that may be protective or pathogenic for autism based on a chi-square test. A convolutional neural network–based diagnostic classifier was then designed using the identified significant common variants to predict autism. The performance was then compared with shallow machine learning–based classifiers and randomly selected common variants.ResultsThe selected contributory common variants were significantly enriched in chromosome X while chromosome Y was also discriminatory in determining the identification of autistic individuals from nonautistic individuals. The ARSD, MAGEB16, and MXRA5 genes had the largest effect in the contributory variants. Thus, screening algorithms were adapted to include these common variants. The deep learning model yielded an area under the receiver operating characteristic curve of 0.955 and an accuracy of 88% for identifying autistic individuals from nonautistic individuals. Our classifier demonstrated a considerable improvement of ~13% in terms of classification accuracy compared to standard autism screening tools.ConclusionsCommon variants are informative for autism identification. Our findings also suggest that the deep learning process is a reliable method for distinguishing the diseased group from the control group based on the common variants of autism.

BackgroundRestricted and Repetitive Behaviors (RRB), one of the core symptom categories for Autism Spectrum Disorders (ASD), comprises heterogeneous groups of behaviors. Previous research indicates that there are two or more factors (subcategories) within the RRB domain. In an effort to identify common variants associated with RRB, we have carried out a genome-wide association study (GWAS) using the Autism Genetic Resource Exchange (AGRE) dataset (n = 1,335, all ASD probands of European ancestry) for each identified RRB subcategory, while allowing for comparisons of associated single nucleotide polymorphisms (SNPs) with associated SNPs in the same set of probands analyzed using all the RRB subcategories as phenotypes in a multivariate linear mixed model. The top ranked SNPs were then explored in an independent dataset.ResultsUsing principal component analysis of item scores obtained from Autism Diagnostic Interview-Revised (ADI-R), two distinct subcategories within Restricted and Repetitive Behaviors were identified: Repetitive Sensory Motor (RSM) and Insistence on Sameness (IS). Quantitative RSM and IS scores were subsequently used as phenotypes in a GWAS using the AGRE ASD cohort. Although no associated SNPs with genome-wide significance (P < 5.0E-08) were detected when RSM or IS were analyzed independently, three SNPs approached genome-wide significance when RSM and IS were considered together using multivariate association analysis. These included the top IS-associated SNP, rs62503729 (P-value = 6.48E-08), which is located within chromosome 8p21.2-8p21.1, a locus previously linked to schizophrenia. Notably, all of the most significantly associated SNPs are located in close proximity to STMN4 and PTK2B, genes previously shown to function in neuron development. In addition, several of the top-ranked SNPs showed correlations with STMN4 mRNA expression in adult CEU (Caucasian and European descent) human prefrontal cortex. However, the association signals within chromosome 8p21.2-8p21.1 failed to replicate in an independent sample of 2,588 ASD probands; the insufficient sample size and between-study heterogeneity are possible explanations for the non-replication.ConclusionsOur analysis indicates that RRB in ASD can be represented by two distinct subcategories: RSM and IS. Subsequent univariate and multivariate genome-wide association studies of these RRB subcategories enabled the detection of associated SNPs at 8p21.2-8p21.1. Although these results did not replicate in an independent ASD dataset, genomic features of this region and pathway analysis suggest that common variants in 8p21.2-8p21.1 may contribute to RRB, particularly IS. Together, these observations warrant future studies to elucidate the possible contributions of common variants in 8p21.2-8p21.1 to the etiology of RSM and IS in ASD.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2475-y) contains supplementary material, which is available to authorized users.

Repetitive and restricted behaviours are a core feature of autism, and cognition in autistic individuals may also be repetitive and restricted. We aimed to investigate the relationship between repetitive behaviours and repetitive thinking. We predicted that autistic people would experience more repetitive, perseverative, visual and negative cognition than controls. We predicted that repetitive thinking would be associated with repetitive behaviours in the autistic participants. We recruited autistic (n = 54) and control (n = 66) participants who completed measures of insistence on sameness and obsessive-compulsive behaviours. Participants then took part in 5 days of descriptive experiencing sampling, recording their thoughts when a random alarm sounded. Consistent with our hypothesis, autistic participants reported more repetitive thinking. Contrary with our other hypotheses, autistic participants reported equivalent frequency of perseveration, visual thoughts and negative thoughts to non-autistic participants. Moreover, participants who reported more obsessive thinking reported more repetitive behaviour (insistence on sameness), but there was no such relationship between repetitive thinking and behaviour. Autistic participants who reported more repeated thoughts in the descriptive experience sampling had significantly lower obsessive thinking scores. We conclude that anxiety focused cognitions may drive insistence on sameness behaviours, and that the relationship between repetitive cognition and behaviour is complex and warrants further investigation.Lay abstractA core feature of autism is the tendency to do the same activity or behaviour repetitively. We wanted to find out if autistic people also experience repetitive thinking, for example, having the same thoughts repeatedly. We thought that there would be a link between repetitive behaviour and repetitive thinking. We asked 54 autistic people and 66 non-autistic people to complete questionnaires measuring repetitive behaviours and obsessive thinking. Next, participants were trained by a researcher to record their thoughts using a structured paper form. They then completed 5 days of thought recording, which they did each time a random alarm sounded on their mobile phone. We found that autistic people had more repetitive thoughts than non-autistic people, but they did not report having more negative or visual thoughts compared with non-autistic people. Autistic people who had more repetitive thoughts during the 5 days of thought recording did not report more repetitive behaviour. However, autistic people who reported more obsessive thinking, for example, more negative and unwanted thoughts, also reported higher levels of repetitive behaviour. We conclude that some repetitive behaviours may be linked to anxiety and that more research is needed to better understand repetitive behaviours in autism.

Despite being a monogenic condition, individual variability in the phenotypic profile of fragile X syndrome (FXS) is substantial, with behavioural outcomes differing in severity and frequency. Existing studies have revealed that common variation in 5-HTTLPR (serotonin) and COMT (dopamine) single nucleotide polymorphisms (SNPs) is associated with behavioural variation in FXS when measured cross-sectionally. However, the associations between SNPs and longitudinal behavioural trajectories in FXS remain unknown. This study explored relationships between three SNPs, selected a priori (5-HTTLPR, COMT and monoamine oxidase A (MAOA)), and trajectories of clinically relevant behaviours in 42 males with FXS. Autistic characteristics, property destruction, aggression, stereotyped behaviour, self-injury, repetitive behaviour, and mood/interest and pleasure were measured at two time points across three years via a series of standardised informant questionnaires. DNA was extracted from saliva samples and a combination of PCR and TaqMan genotyping was performed for genetic confirmation of FXS, and COMT, 5-HTTLPR and MAOA analyses. Results revealed that males with FXS with AA COMT genotype were less likely to display persistent stereotyped behaviour compared to AG or GG genotypes. Participants with the S/S 5-HTTLPR genotype displayed a steeper decline in repetitive and stereotyped behaviours compared to the L/S or L/L genotypes. Participants with the three-repeat MAOA genotype demonstrated a steeper decline in communication skills over three years compared to those with four repeats. This study documents the association between common genetic variation and behavioural trajectories in males with FXS. Results suggest specific SNPs play an important role in longitudinal behavioural patterns in FXS. This work may facilitate an understanding of individual trajectories for people with FXS, and, therefore, support future tailored interventions.

Decision letter: Characterizing a psychiatric symptom dimension related to deficits in goal-directed control

BackgroundAutism spectrum conditions (ASC) are a group of neurodevelopmental conditions characterized by difficulties in social interaction and communication alongside repetitive and stereotyped behaviours. ASC are heritable, and common genetic variants contribute substantial phenotypic variability. More than 600 genes have been implicated in ASC to date. However, a comprehensive investigation of candidate gene association studies in ASC is lacking.MethodsIn this study, we systematically reviewed the literature for association studies for 552 genes associated with ASC. We identified 58 common genetic variants in 27 genes that have been investigated in three or more independent cohorts and conducted a meta-analysis for 55 of these variants. We investigated publication bias and sensitivity and performed stratified analyses for a subset of these variants.ResultsWe identified 15 variants nominally significant for the mean effect size, 8 of which had P values below a threshold of significance of 0.01. Of these 15 variants, 11 were re-investigated for effect sizes and significance in the larger Psychiatric Genomics Consortium dataset, and none of them were significant. Effect direction for 8 of the 11 variants were concordant between both the datasets, although the correlation between the effect sizes from the two datasets was poor and non-significant.ConclusionsThis is the first study to comprehensively examine common variants in candidate genes for ASC through meta-analysis. While for majority of the variants, the total sample size was above 500 cases and 500 controls, the total sample size was not large enough to accurately identify common variants that contribute to the aetiology of ASC.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-015-0041-0) contains supplementary material, which is available to authorized users.

These are exciting times, with a plethora of new technologies that are expediting discovery of the genetic underpinnings of human disease. Comprehensive resequencing of the human genome is now feasible and affordable, allowing each person's entire genetic makeup to be revealed. The major focus of

Non-alcoholic fatty liver disease (NAFLD), and its progressive form steatohepatitis (NASH), represent a genetically and phenotypically diverse entity for which there is no approved therapy, making it imperative to define the spectrum of pathways contributing to its pathogenesis. Rare variants in genes encoding nuclear envelope proteins cause lipodystrophy with early-onset NAFLD/NASH; we hypothesized that common variants in nuclear envelope-related genes might also contribute to hepatic steatosis and NAFLD. Using hepatic steatosis as the outcome of interest, we performed an association meta-analysis of nuclear envelope-related coding variants in three large discovery cohorts (N >120,000 participants), followed by phenotype association studies in large validation cohorts (N >600,000) and functional testing of the top steatosis-associated variant in cell culture. A common protein-coding variant, rs6461378 (SUN1 H118Y), was the top steatosis-associated variant in our association meta-analysis (p <0.001). In ancestrally distinct validation cohorts, rs6461378 associated with histologic NAFLD and with NAFLD-related metabolic traits including increased serum fatty acids, type 2 diabetes, hypertension, cardiovascular disease, and decreased HDL. SUN1 H118Y was subject to increased proteasomal degradation relative to wild-type SUN1 in cells, and SUN1 H118Y-expressing cells exhibited insulin resistance and increased lipid accumulation. Collectively, these data support a potential causal role for the common SUN1 variant rs6461378 in NAFLD and metabolic disease. Non-alcoholic fatty liver disease (NAFLD), with an estimated global prevalence of nearly 30%, is a growing cause of morbidity and mortality for which there is no approved pharmacologic therapy. Our data provide a rationale for broadening current concepts of NAFLD genetics and pathophysiology to include the nuclear envelope, and particularly Sad1 and UNC84 domain containing 1 (SUN1), as novel contributors to this common liver disease. Furthermore, if future studies confirm causality of the common SUN1 H118Y variant, it has the potential to become a broadly relevant therapeutic target in NAFLD and metabolic disease.

Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

“A developmental disability that hinders the normal functioning of the brain, affecting, in varying degrees, communication skills and social interaction. Repetitive behaviours, and different ways of learning, paying attention, or reacting to things are often distinctive signs”. This standard definition of autism fails to describe the complexity of a condition that ranges in its manifestations from severe intellectual impairment to superior cognitive skills, like in the Asperger syndrome. To comprise such diversity, autism disorders are now covered under the umbrella term “autism spectrum disorder” (ASD). In most cases, ASD manifests during the first 5 years of life, with boys significantly more likely to be diagnosed than girls. ASD usually goes together with several other problems that frequently include anxiety, sleep disorders, or epilepsy. No cure exists; treatment, such as speech therapy, just attempts to alleviate specific deficits of autistic patients. > Nothing is simple in autism. Even the real number of people affected is uncertain. Nothing is simple in autism. Even the real number of people affected is uncertain. The US CDC estimates that about 1 in 68 (or 1.5%) of children in the USA are living with ASD (http://www.cdc.gov/ncbddd/autism/data.html). The WHO has a more conservative estimate, last revised in January this year, of 1 in 160 children, based on a larger set of epidemiological surveys (http://www.who.int/mediacentre/factsheets/autism-spectrum-disorders/en/). Needless to say, most studies were conducted in developed countries, and the prevalence of ASD in many low‐ and middle‐income countries remains largely unknown. > Along the years, many potential causes have been indicated, including genetic and environmental factors, exposure to toxins during pregnancy, wide gaps between parent ages, and so on Although the general consensus is that prevalence rates are increasing globally, this point is debated too. Some analyses indicate that a large percentage of the increase in ASD owes to improved awareness and …

ABSTRACT: Menopause timing has a major impact on infertility and risk of disease. Younger age at natural (nonsurgical) menopause (ANM) is associated with a higher risk of osteoporosis, cardiovascular disease, and type 2 diabetes and a lower risk of breast cancer. Late menopause is associated with a higher risk of breast cancer. It is well known that the age at which women go through menopause is partly determined by genes, but the underlying mechanisms are poorly understood. Genome-wide association studies have identified 18 common genetic variants associated with ANM. These variants explain less than 5% of the variation in ANM compared with the 21% explained by all common variants on genome-wide association study arrays. This genome-wide association study was the collaborative effort of researchers from 177 institutions worldwide. The study was designed to investigate genetic variants associated with timing of menopause among a population of approximately 70,000 women of European ancestry. A dual strategy was used to identify both common and, for the first time, low-frequency coding variants associated with ANM. The causal relationship between ANM and breast cancer was investigated using a Mendelian randomization approach. Combined analysis identified 1208 single-nucleotide polymorphisms (SNPs) of a total of approximately 2.6 million that reached the genome-wide significance threshold for association with ANM. Forty-four regions with common variants were identified; among these 44 loci were 2 rare low-frequency missense alleles of large effect. A majority of ANM SNPs were enriched in DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal relationship between delayed ANM and breast cancer risk; there was approximately 6% increase in risk per year; P = 3 × 10-14); increased risk with delayed menopause appeared to be mediated primarily by prolonged sex hormone exposure in a woman’s lifetime, not DDR mechanisms. This is the first study to confirm the link between early and late menopause and breast cancer risk using genetic information. Age at natural menopause genetic variants influence breast cancer risk primarily through variation in menopause timing. Although carrying higher numbers of ANM-increasing variants and enrichment in DDR genes are associated with a modest increase in breast cancer risk, the major mechanism for increased risk appears to be prolonged estrogen and/or progesterone exposure due to delayed menopause.

The association between glucocerebrosidase, encoded by GBA, and Parkinson's disease (PD) highlights the role of the lysosome in PD pathogenesis. Genome-wide association studies in PD have revealed multiple associated loci, including the GALC locus on chromosome 14. GALC encodes the lysosomal enzyme galactosylceramidase, which plays a pivotal role in the glycosphingolipid metabolism pathway. It is still unclear whether GALC is the gene driving the association in the chromosome 14 locus and, if so, by which mechanism. We first aimed to examine whether variants in the GALC locus and across the genome are associated with galactosylceramidase activity. We performed a genome-wide association study in two independent cohorts from (i) Columbia University; and (ii) the Parkinson's Progression Markers Initiative study, followed by a meta-analysis with a total of 976 PD patients and 478 controls with available data on galactosylceramidase activity. We further analysed the effects of common GALC variants on expression and galactosylceramidase activity using genomic colocalization methods. Mendelian randomization was used to study whether galactosylceramidase activity may be causal in PD. To study the role of rare GALC variants, we analysed sequencing data from 5028 PD patients and 5422 controls. Additionally, we studied the functional impact of GALC knockout on alpha-synuclein accumulation and on glucocerebrosidase activity in neuronal cell models and performed in silico structural analysis of common GALC variants associated with altered galactosylceramidase activity. The top hit in PD genome-wide association study in the GALC locus, rs979812, is associated with increased galactosylceramidase activity (b = 1.2; SE = 0.06; P = 5.10 × 10-95). No other variants outside the GALC locus were associated with galactosylceramidase activity. Colocalization analysis demonstrated that rs979812 was also associated with increased galactosylceramidase expression. Mendelian randomization suggested that increased galactosylceramidase activity may be causally associated with PD (b = 0.025, SE = 0.007, P = 0.0008). We did not find an association between rare GALC variants and PD. GALC knockout using CRISPR-Cas9 did not lead to alpha-synuclein accumulation, further supporting that increased rather than reduced galactosylceramidase levels may be associated with PD. The structural analysis demonstrated that the common variant p.I562T may lead to improper maturation of galactosylceramidase affecting its activity. Our results nominate GALC as the gene associated with PD in this locus and suggest that the association of variants in the GALC locus may be driven by their effect of increasing galactosylceramidase expression and activity. Whether altering galactosylceramidase activity could be considered as a therapeutic target should be further studied.

Epidemiological evidence strongly favors the notion that the risk of cardiovascular disease (CVD) is inversely related to the plasma high-density lipoprotein (HDL) cholesterol concentration.1 Low HDL cholesterol is still predictive of high CVD risk in subjects with low LDL cholesterol,2 as well as during statin treatment.3 These observational data and other studies, which show that HDL particles contain a large number of antioxidative, antiinflammatory, and antiproliferative proteins, underlie the generally held view that HDL particles have atheroprotective properties.1–5 However, evidence is accumulating supporting the concept that high HDL cholesterol levels do not always predict reduced CVD risk. The Incremental Decrease in End Points through Aggressive Lipid Lowering (IDEAL) trial and the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk case-control study revealed that (recurrent) CVD risk is not decreased in subjects with the highest HDL cholesterol and the greatest mean HDL particle size.6 More recently, a high HDL cholesterol, high C-reactive protein (CRP) subgroup of individuals at increased risk for a first cardiovascular event was identified in the community-dwelling Prevention of Renal and Vascular End-Stage Disease (PREVEND) cohort using the “outcome event mapping approach,” a graphical exploratory data analysis tool that has been originally developed by Corsetti et al.7 Applying this analytic method to the Thrombogenic Factors and Recurrent Coronary Events (THROMBO) postinfarction cohort, the presence of a subgroup …