Publications by authors named "April P Carson"

The relationship between mitochondrial DNA (mtDNA) heteroplasmy and nuclear DNA (nDNA) methylation (CpGs) remains to be studied. We conducted an epigenome-wide association analysis of heteroplasmy burden scores across 10,986 participants (mean age 77, 63% women, and 54% non-White races/ethnicities) from seven population-based observational cohorts. We identified 412 CpGs (FDR p < 0.

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We created a comprehensive whole blood splice variation quantitative trait locus (sQTL) resource by analyzing isoform expression ratio (isoform-to-gene) in Framingham Heart Study (FHS) participants (discovery: n=2,622; validation: n=1,094) with whole genome (WGS) and transcriptome sequencing (RNA-seq) data. External replication was conducted using WGS and RNA-seq from the Jackson Heart Study (JHS, n=1,020). We identified over 3.

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Black adults have higher incidence of all-cause mortality and worse cardiovascular disease (CVD) outcomes when compared to other U.S. populations.

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Background: Nearly 3% to 4% of Black individuals in the United States carry the transthyretin V142I variant, which increases their risk of heart failure. However, the role of cardiovascular (CV) risk factors (RFs) in influencing the risk of clinical outcomes among V142I variant carriers is unknown.

Objectives: This study aimed to assess the impact of CV RFs on the risk of heart failure in V142I carriers.

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  • Whole genome sequencing (WGS) helps identify rare genetic variants that may explain the missing heritability of coronary artery disease (CAD) by analyzing 4,949 cases and 17,494 controls from the NHLBI TOPMed program.
  • The study estimates that the heritability of CAD is around 34.3%, with ultra-rare variants contributing about 50%, especially those with low linkage disequilibrium.
  • Functional annotations show significant enrichment of CAD heritability, highlighting the importance of ultra-rare variants and specific regulatory mechanisms in different cells as major factors influencing genetic risk for the disease.
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  • The study investigates how rare non-coding genetic variations affect complex traits, specifically focusing on human height by analyzing data from over 333,100 individuals across three large datasets.
  • Researchers found 29 significant rare variants linked to height, with impacts ranging from a decrease of 7 cm to an increase of 4.7 cm, after considering previously known variants.
  • The team also identified specific non-coding variants near key genes associated with height, demonstrating a new method for understanding the effects of rare variants in regulatory regions using whole-genome sequencing.
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We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α = 0.

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  • * It analyzes data from the Atherosclerosis Risk in Communities Study, including diverse participants from four US communities, with an average follow-up period of nearly 19 years.
  • * Findings suggest that individuals who lived in lower SES neighborhoods during middle adulthood had a significantly higher risk of dying before age 75 compared to those from higher SES neighborhoods.
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Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels.

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We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs.

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  • Genome-wide association studies (GWAS) have successfully identified genes linked to telomere length, but previous research hadn't validated these findings until now.
  • In a large analysis involving over 211,000 people, the study discovered five new signals linked to telomere length and highlighted the importance of blood/immune cells in this area.
  • The researchers confirmed that the genes KBTBD6 and POP5 truly affect telomere length by demonstrating that manipulating these genes can lengthen telomeres and that their regulation is crucial for understanding telomere biology.
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Background: Cardiometabolic risk prediction models that incorporate metabolic syndrome traits to predict cardiovascular outcomes may help identify high-risk populations early in the progression of cardiometabolic disease.

Objectives: The purpose of this study was to examine whether a modified cardiometabolic disease staging (CMDS) system, a validated diabetes prediction model, predicts major adverse cardiovascular events (MACE).

Methods: We developed a predictive model using data accessible in clinical practice [fasting glucose, blood pressure, body mass index, cholesterol, triglycerides, smoking status, diabetes status, hypertension medication use] from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study to predict MACE [cardiovascular death, nonfatal myocardial infarction, and/or nonfatal stroke].

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Background: Hypertension prevalence among the overall US adult population has been relatively stable during the last two decades. However, whether this stabilization has occurred across rural-urban communities and across different geographic regions is unknown, particularly among older adults with diabetes who are likely to have concomitant cardiovascular risk factors.

Methods: This serial cross-sectional analysis used the 5% national sample of Medicare administrative claims data (n = 3,516,541) to examine temporal trends (2005-2017) in diagnosed hypertension among older adults with diabetes, across urban-rural communities and US census regions (Northeast, Midwest, South, and West).

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Background: We examined the association of multilevel social determinants of health with incident apparent treatment-resistant hypertension (aTRH).

Methods And Results: We analyzed data from 2774 White and 2257 Black US adults from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study taking antihypertensive medication without aTRH at baseline to estimate the association of social determinants of health with incident aTRH. Selection of social determinants of health was guided by the Healthy People 2030 domains of education, economic stability, social context, neighborhood environment, and health care access.

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  • Inflammation biomarkers offer crucial insights into the inflammatory processes linked to various diseases, and their sequencing can help reveal the genetic makeup of these traits.
  • A study analyzed 21 inflammation biomarkers from around 38,465 individuals, discovering 22 significant associations across 6 inflammatory traits after considering existing findings.
  • The research combined single-variant and rare variant analyses, identifying additional significant associations and highlighting the complexity and diversity of genetic influences on inflammation traits across different ancestries.
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Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood.

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Context: Natriuretic peptide concentrations are inversely associated with risk of diabetes mellitus and may be protective from metabolic dysfunction.

Objective: We studied associations of N-terminal pro-B-type natriuretic peptide (NT-proBNP) with incident diabetes, metabolic syndrome (MetS), and MetS components.

Design/setting/participants: 2,899 participants with baseline (2003-2007) and follow-up (2013-2016) examinations and baseline NT-proBNP measurement in the REasons for Geographic And Racial Differences in Stroke study.

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Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program.

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Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric.

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Background: Heart failure (HF) affects >6 million US adults, with recent increases in HF hospitalizations. We aimed to investigate the association between neighborhood disadvantage and incident HF events and potential differences by diabetes status.

Methods: We included 23 645 participants from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke), a prospective cohort of Black and White adults aged ≥45 years living in the continental United States (baseline 2005-2007).

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Article Synopsis
  • Familial hypercholesterolemia (FH) is a genetic condition linked to high LDL cholesterol levels and increased risk of early coronary heart disease (CHD), though its effects on CHD in those with moderate LDL-C levels are not fully understood.
  • * This study evaluated the CHD risk from FH variants in individuals with both moderately and severely elevated LDL-C levels and estimated the additional deaths from CHD related to FH in U.S. adults.
  • * Among 21,426 participants, those with FH variants had significantly higher rates of developing CHD, with hazard ratios of 2.9 for those with moderately elevated LDL-C and 2.6 for those with severely elevated LDL-C.
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Importance: Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic stem cells with leukemogenic acquired genetic variants, is associated with incident heart failure (HF).

Objective: To evaluate the associations of CHIP and key gene-specific CHIP subtypes with incident HF with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF).

Design, Setting, And Participants: This population-based cohort study included participants from 2 racially diverse prospective cohort studies with uniform HF subtype adjudication: the Jackson Heart Study (JHS) and Women's Health Initiative (WHI).

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We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.

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