Contributions of Women to Cardiovascular Science Over Two Decades: Authorship, Leadership, and Mentorship.

Background Women remain underrepresented in cardiology. We aimed to assess gender trends in research authorship, authorship in leading roles, mentorship, and research team diversity. Methods and Results We identified "cardiac and cardiovascular systems" journals from 2002 to 2020 using Journal Citation Reports 2019 (Web of Science, Clarivate Analytics).

Associations of a polygenic risk score with coronary artery disease phenotypes in the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial.

A polygenic risk score (PGS) is associated with obstructive coronary artery disease (CAD) independent of traditional risk factors. Coronary computed tomography angiography (CTA) can characterize coronary plaques, including features of highrisk CAD. However, it is unknown if a PGS is associated with obstructive CAD and high-risk CAD phenotypes in patients with symptoms suggestive of CAD.

An antiplatelet response gene expression signature is associated with bleeding.

Aims: Gene expression biosignatures may hold promise to individualize antiplatelet therapy in conjunction with current guidelines and risk scores. The Aspirin Response Signature (ARS) score is comprised of a weighted sum of correlated, pro-thrombotic gene transcripts measured in whole blood. In prior work where volunteers were exposed to aspirin 325 mg daily, higher ARS score was associated with lower platelet function; separately, in a clinical cohort of patients, higher ARS scores were associated with increased risk of adverse cardiovascular events.

"Physiological Dysregulation" as a Promising Measure of Robustness and Resilience in Studies of Aging and a New Indicator of Preclinical Disease.

Recently suggested novel implementation of the statistical distance measure (DM) for evaluating "physiological dysregulation" (PD) in aging individuals (based on measuring deviations of multiple biomarkers from baseline or normal physiological states) allows reducing high-dimensional biomarker space into a single PD estimate. Here we constructed DM using biomarker profiles from FRAMCOHORT (Framingham Heart Study) and CHS (Cardiovascular Health Study) Research Materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center, and estimated effect of PD on total survival, onset of unhealthy life (proxy for "robustness") and survival following the onset of unhealthy life (proxy for "resilience"). We investigated relationships between PD and declines in stress resistance and adaptive capacity not directly observed in data.

Hidden heterogeneity in Alzheimer's disease: Insights from genetic association studies and other analyses.

Despite evident success in clarifying many important features of Alzheimer's disease (AD) the efficient methods of its prevention and treatment are not yet available. The reasons are likely to be the fact that AD is a multifactorial and heterogeneous health disorder with multiple alternative pathways of disease development and progression. The availability of genetic data on individuals participated in longitudinal studies of aging health and longevity, as well as on participants of cross-sectional case-control studies allow for investigating genetic and non-genetic connections with AD and to link the results of these analyses with research findings obtained in clinical, experimental, and molecular biological studies of this health disorder.

cophesim: a comprehensive phenotype simulator for testing novel association methods.

Simulation is important in evaluating novel methods when input data is not easily obtainable or specific assumptions are needed. We present , a software to add the phenotype to generated genotype data prepared with a genetic simulator. The output of can be used as a direct input for different genome wide association study tools.

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases.

rqt: an R package for gene-level meta-analysis.

Motivation: Despite recent advances of modern GWAS methods, it is still remains an important problem of addressing calculation an effect size and corresponding p-value for the whole gene rather than for single variant.

Results: We developed an R package rqt, which offers gene-level GWAS meta-analysis. The package can be easily included into bioinformatics pipeline or used stand-alone.

: an R package for querying web-based annotation tools.

We developed , an R package for querying web based genome annotation tools HaploReg and RegulomeDB. gathers information in a data frame which is suitable for downstream bioinformatic analyses. This will facilitate post-genome wide association studies streamline analysis for rapid discovery and interpretation of genetic associations.

stpm: an R package for stochastic process model.

Background: The Stochastic Process Model (SPM) represents a general framework for modeling the joint evolution of repeatedly measured variables and time-to-event outcomes observed in longitudinal studies, i.e., SPM relates the stochastic dynamics of variables (e.

Pure and Confounded Effects of Causal SNPs on Longevity: Insights for Proper Interpretation of Research Findings in GWAS of Populations with Different Genetic Structures.

This paper shows that the effects of causal SNPs on lifespan, estimated through GWAS, may be confounded and the genetic structure of the study population may be responsible for this effect. Simulation experiments show that levels of linkage disequilibrium (LD) and other parameters of the population structure describing connections between two causal SNPs may substantially influence separate estimates of the effect of the causal SNPs on lifespan. This study suggests that differences in LD levels between two causal SNP loci within two study populations may contribute to the failure to replicate previous GWAS findings.

MetAmp: combining amplicon data from multiple markers for OTU analysis.

Motivation: We present a novel method and corresponding application, MetAmp, to combine amplicon data from multiple genomic markers into Operational Taxonomic Units (OTUs) for microbial community analysis, calibrating the markers using data from known microbial genomes. When amplicons for multiple markers such as the 16S rRNA gene hypervariable regions are available, MetAmp improves the accuracy of OTU-based methods for characterizing bacterial composition and community structure. MetAmp works best with at least three markers, and is applicable to non-bacterial analyses and to non 16S markers.

SlopMap: a software application tool for quick and flexible identification of similar sequences using exact k-mer matching.

With the advent of Next-Generation (NG) sequencing, it has become possible to sequence a entire genomes quickly and inexpensively. However, in some experiments one only needs to extract and assembly a portion of the sequence reads, for example when performing transcriptome studies, sequencing mitochondrial genomes, or characterizing exomes. With the raw DNA-library of a complete genome it would appear to be a trivial problem to identify reads of interest.