Biomedical subjects

Alanna C Morrison

Publications and source records attributed to Alanna C Morrison.

13 recordsLinked to original sources

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2026

Proteomic Profiling of Pulmonary Function and Cardiovascular Disease Risk in the Atherosclerosis Risk in Communities Study.

BACKGROUND: Pulmonary function is linked to cardiovascular disease risk; however, the underlying mechanisms remain unclear. We aimed to identify protein biomarkers associated with pulmonary function and examine their impact on incident chronic obstructive pulmonary disease, coronary heart disease, heart failure, and all-cause mortality. METHODS: Data from White and Black Americans in the Atherosclerosis Risk in Communities study (visit 2: N=11 354, mean age=57 years; visit 5: N=3517, mean age=75 years), a prospective cohort, were analyzed. Linear regression assessed associations between protein levels and pulmonary function measures, including forced expiratory volume in 1 second and forced vital capacity. The impact of the identified proteins on incident chronic obstructive pulmonary disease, coronary heart disease, heart failure, and mortality was estimated using logistic regression and Cox proportional hazards models. Pathway enrichment and Mendelian randomization explored underlying biological functions and causal effects. RESULTS: Of 4766 proteins analyzed, 364 were cross-sectionally associated with forced expiratory volume in 1 second (and forced vital capacity (false discovery rate<0.05). Ninety-four and 270 proteins had concordant positive and negative effects, respectively. Five pathways related to pulmonary and cardiac function were enriched. Of the 364 proteins, 112 were linked to all 4 outcomes, where 86 were associated with increased risk (odds ratio/hazard ratio [OR/HR], 1.05-1.42) and 26 with reduced risk (OR/HR, 0.69-0.96). Six proteins (STAT3 [signal transducer and activator of transcription 3], MIC-1 [growth differentiation factor 15], apoA-II [apolipoprotein A-II], TPST1 [protein-tyrosine sulfotransferase 1], integrin a1b1 [integrin alpha-I: beta-1 complex], and BLC [C-X-C motif chemokine 13]) showed potential inverse causal effects on with forced expiratory volume in 1 second and forced vital capacity, and integrin a1b1 demonstrated consistent inverse associations with chronic obstructive pulmonary disease, coronary heart disease, and heart failure risks. CONCLUSIONS: Proteins associated with pulmonary function may influence CVD risk. Six proteins, including integrin a1b1, represent promising targets for future interventions.

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PubMed2025

Historical review: more than two decades understanding the genetic architecture of hemostasis and thrombosis.

From the beginning of the millennium and the development of genome-wide analyses, the technical advances and remarkable increase in research sample sizes have led to an escalating number of discoveries revealing genetic determinants of levels of the main factors regulating hemostasis and thrombosis and demonstrating a clear polygenic complex regulation of most coagulation factors. These discoveries have been useful to understand the biology underlying hemostasis regulation and to understand risk of associated thrombotic disease, such as venous thromboembolism, coronary artery disease, and ischemic stroke. In this historical review, we outline the main discoveries in genetic studies of coagulation factors (fibrinogen and its alternatively spliced γ' isoform, D-dimer, factor [F]V, FVII, FVIII, von Willebrand factor, and FXI), the main natural anticoagulants (protein C, protein S, and antithrombin), components of fibrinolysis (tissue plasminogen activator and plasminogen activator inhibitor-1), and global coagulation tests (prothrombin time and activated partial thromboplastin time). We explore the clinical implications of these discoveries and suggest new avenues for future investigation.

Humans↗

PubMed2025

Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.

BACKGROUND: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability. RESULTS: Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate. CONCLUSIONS: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.

Humans↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed2025

Polygenic scores for obstructive sleep apnoea reveal pathways contributing to cardiovascular disease.

BACKGROUND: Obstructive sleep apnoea (OSA) is a common chronic condition, with obesity its strongest risk factor. Polygenic scores (PGSs) summarise the genetic liability to phenotype and can provide insights into relationships between phenotypes. Recently, large datasets that include genetic data and OSA status became available, providing an opportunity to utilise PGS approaches to study the genetic relationship between OSA and other phenotypes, while differentiating OSA-specific from obesity-specific genetic factors. METHODS: Using race/ethnic diverse samples from over 1.2 million individuals from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger's MyCode, MGB Biobank, and the Human Phenotype Project, we developed and assessed PGSs for OSA, both without (BMIunadjOSA-PGS) and with adjustment for the genetic contributions of BMI (BMIadjOSA-PGS). FINDINGS: Adjusted odds ratios (ORs) for OSA per 1 standard deviation of the PGSs ranged from 1.38 to 2.75. The associations of BMIadjOSA- and BMIunadjOSA-PGSs with CVD outcomes in AoU shared both common and distinct patterns. Only BMIunadjOSA-PGS was associated with type 2 diabetes, heart failure, and coronary artery disease, while both BMIadjOSA- and BMIunadjOSA-PGSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA-PGS association with hypertension was driven by females (OR = 1.1, p-value = 0.002, OR = 1.01 p-value = 0.2 in males). OSA PGSs were also associated with body fat measures with some sex-specific associations. INTERPRETATION: Distinct components of OSA genetic risk are related and independent of obesity. Sex-specific associations with body fat distribution measures may explain differing OSA risks and associations with cardiometabolic morbidities between sexes. FUNDING: R01AG080598.

Humans↗

PubMed2025

Genetic study of von Willebrand factor antigen levels ≤ 50 IU/dL identifies variants associated with increased risk of von Willebrand disease and bleeding.

BACKGROUND: von Willebrand disease (VWD) is a common inherited bleeding disorder caused by low levels or activity of circulating von Willebrand factor (VWF). Genetic susceptibility to VWF antigen (VWF:Ag) below normal (≤ 50 IU/dL) in the general population is underexplored. OBJECTIVES: To identify genetic variants influencing VWF:Ag levels ≤ 50 IU/dL. METHODS: We performed a genome-wide association study in 926 cases with VWF:Ag levels ≤ 50 IU/dL and 12 846 controls from 7 studies from the Trans-Omics for Precision Medicine program. We then examined whether significant genome-wide findings were also associated with clinical diagnosis of VWD in 5 biobanks with 708 VWD cases and 1 286 069 controls, and with 6 bleeding and thrombotic disorders in FinnGen. RESULTS: Variants at 2 loci were associated (P < 5 × 10-9) with VWF:Ag levels ≤ 50 IU/dL: ABO and VWF. The VWF index variant, p.Tyr1584Cys, is a rare (0.22%) missense variant with odds ratio (OR) of 78.58, while the ABO index variant is a common intronic variant with a smaller effect (OR = 2.52). Notably, both VWF (OR = 7.16) and ABO (OR = 1.57) variants were also associated (P < .025) with diagnosed VWD. Among p.Tyr1584Cys heterozygotes, the penetrance of VWF:Ag levels ≤ 50 IU/dL was 24.2% and the penetrance of diagnosed VWD was 0.3%. p.Tyr1584Cys was associated (P < .0042) with increased odds of heavy menstrual bleeding (OR = 1.27), iron deficiency anemia (OR = 1.55), and intrapartum hemorrhage (OR = 2.20), but decreased odds of deep vein thrombosis (OR = 0.54). CONCLUSIONS: Although there are currently conflicting interpretations of pathogenicity p.Tyr1584Cys, our results suggest that it is a low penetrance pathogenic variant that contributes to VWF:Ag levels ≤ 50 IU/dL, bleeding, and VWD.

Humans↗

PubMed2025

Rare damaging CCR2 variants are associated with lower lifetime cardiovascular risk.

BACKGROUND: Previous work has shown a role of CCL2, a key chemokine governing monocyte trafficking, in atherosclerosis. However, it remains unknown whether targeting CCR2, the cognate receptor of CCL2, provides protection against human atherosclerotic cardiovascular disease. METHODS: Computationally predicted damaging or loss-of-function (REVEL > 0.5) variants within CCR2 were detected in whole-exome-sequencing data from 454,775 UK Biobank participants and tested for association with cardiovascular endpoints in gene-burden tests. Given the key role of CCR2 in monocyte mobilization, variants associated with lower monocyte count were prioritized for experimental validation. The response to CCL2 of human cells transfected with these variants was tested in migration and cAMP assays. Validated damaging variants were tested for association with cardiovascular endpoints, atherosclerosis burden, and vascular risk factors. Significant associations were replicated in six independent datasets (n = 1,062,595). RESULTS: Carriers of 45 predicted damaging or loss-of-function CCR2 variants (n = 787 individuals) were at lower risk of myocardial infarction and coronary artery disease. One of these variants (M249K, n = 585, 0.15% of European ancestry individuals) was associated with lower monocyte count and with both decreased downstream signaling and chemoattraction in response to CCL2. While M249K showed no association with conventional vascular risk factors, it was consistently associated with a lower risk of myocardial infarction (odds ratio [OR]: 0.66, 95% confidence interval [CI]: 0.54-0.81, p = 6.1 × 10-5) and coronary artery disease (OR: 0.74, 95%CI: 0.63-0.87, p = 2.9 × 10-4) in the UK Biobank and in six replication cohorts. In a phenome-wide association study, there was no evidence of a higher risk of infections among M249K carriers. CONCLUSIONS: Carriers of an experimentally confirmed damaging CCR2 variant are at a lower lifetime risk of myocardial infarction and coronary artery disease without carrying a higher risk of infections. Our findings provide genetic support for the translational potential of CCR2-targeting as an atheroprotective approach.

Humans↗

PubMed2025

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Journal Article↗

PubMed2025

Unveiling the Genetic Landscape of Coronary Artery Disease Through Common and Rare Structural Variants.

BACKGROUND: Genome-wide association studies have identified several hundred susceptibility single nucleotide variants for coronary artery disease (CAD). Despite single nucleotide variant-based genome-wide association studies improving our understanding of the genetics of CAD, the contribution of structural variants (SVs) to the risk of CAD remains largely unclear. METHOD AND RESULTS: We leveraged SVs detected from high-coverage whole genome sequencing data in a diverse group of participants from the National Heart Lung and Blood Institute's Trans-Omics for Precision Medicine program. Single variant tests were performed on 58 706 SVs in a study sample of 11 556 CAD cases and 42 907 controls. Additionally, aggregate tests using sliding windows were performed to examine rare SVs. One genome-wide significant association was identified for a common biallelic intergenic duplication on chromosome 6q21 (P=1.54E-09, odds ratio=1.34). The sliding window-based aggregate tests found 1 region on chromosome 17q25.3, overlapping USP36, to be significantly associated with coronary artery disease (P=1.03E-10). USP36 is highly expressed in arterial and adipose tissues while broadly affecting several cardiometabolic traits. CONCLUSIONS: Our results suggest that SVs, both common and rare, may influence the risk of coronary artery disease.

Humans↗

PubMed2024

The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup.

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup. We define a metric called "expected PRS" (ePRS), the expected value of a PRS based on one's global or local admixture patterns. We further define the "residual PRS" (rPRS), measuring the deviation of the PRS from the ePRS. Simulation studies confirm that it suffices to adjust for ePRS to obtain nearly unbiased estimates of the PRS-outcome association without further adjusting for PCs. Using the TOPMed dataset, the estimated effect size of the rPRS adjusting for the ePRS is similar to the estimated effect of the PRS adjusting for genetic PCs. Similarly, we applied the ePRS framework to six cardiovascular-related traits in the All of Us dataset, and the results are consistent with those from the TOPMed analysis. The ePRS framework can protect from population stratification in association analysis and provide an equitable strategy to quantify genetic risk across diverse populations.

Journal Article↗

PubMed2024

Cardiovascular Risk Factors and Genetic Risk in Transthyretin V142I Carriers.

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. METHODS: This study included self-identified Black individuals without prevalent heart failure from 6 TOPMed (Trans-Omics for Precision Medicine) cohorts, the REGARDS (Reasons for Geographic And Racial Differences in Stroke) study, and the All of Us Research Program. The cohort was stratified based on the V142I genotype and the number of CV RFs (hypertension, diabetes, obesity, and hypercholesterolemia). Adjusted Cox models were used to assess the association of heart failure with the V142I genotype and CV RF profile, taking noncarriers with a favorable CV RF profile as reference. RESULTS: The cross-sectional analysis, including 1,625 V142I carriers among 48,365 Black individuals, found that the prevalence of CV RFs did not vary by V142I carrier status. In the longitudinal analysis, there were 587 (3.2%) V142I carriers among 18,407 Black individuals (median age: 60 years [Q1-Q3: 52-68 years], 63.0% female). Among carriers, the heart failure risk was attenuated with a favorable (0 or 1 RF) CV RF profile (adjusted HR: 2.26; 95% CI: 1.58-3.23) compared with an unfavorable (3 or 4 RFs) CV RF profile (adjusted HR: 4.14; 95% CI: 2.79-6.14). CONCLUSIONS: A favorable CV RF profile lowers but does not abrogate V142I variant-associated heart failure risk. This study highlights the importance of having a favorable CV RF profile among V142I carriers for risk reduction of heart failure.

Aged↗

PubMed2024

Rare variant contribution to the heritability of coronary artery disease.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Humans↗