Publications by authors named "Alexander P Reiner"

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).

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Sickle cell trait (SCT) has been associated with alterations in various immune-related laboratory parameters including lower circulating lymphocyte counts. To further characterize the impact of SCT on the immune system, we performed flow cytometry of monocyte and lymphocyte immune cell subsets from peripheral blood mononuclear cells collected in a large, community-based cohort of SCT-positive (n = 68) and SCT-negative (n = 959) Black adults. SCT was significantly associated with lower proportions of CD8 and CD4 T cell subsets that include senescent-like markers of repeated immune system challenges.

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Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA.

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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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Background: Available evidence supports the importance of inflammation in atrial fibrillation (AF) pathogenesis, yet general anti-inflammatory therapies have failed to show benefit for prevention of the arrhythmia. Better understanding of the specific inflammatory pathways involved is necessary to advance therapeutics.

Methods And Results: We evaluated 9 circulating markers of inflammation measured by immunoassays and incidence of AF in a population-based older cohort.

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Cardiac diseases represent common highly morbid conditions for which molecular mechanisms remain incompletely understood. Here we report the analysis of 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P < 8.

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Article Synopsis
  • Researchers studied plasma proteomic profiles linked to subclinical mutations in blood cells, particularly focusing on clonal hematopoiesis of indeterminate potential (CHIP) and its connection to various health outcomes, including coronary artery disease (CAD).
  • The study involved a large, diverse group of participants and identified a significant number of unique proteins associated with key driver genes, showing differences based on genetics, sex, and race.
  • Methods like Mendelian randomization and mouse model tests helped clarify the causal effects of these proteins, revealing shared plasma proteins between CHIP and CAD that could inform future clinical insights.
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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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  • Latin Americans are often overlooked in genetic studies, which can widen gaps in personalized medicine due to the challenges of accessing genetic data and consent processes.
  • The Genetics of Latin American Diversity (GLAD) Project compiles genetic information from over 53,000 individuals across various regions to explore diverse ancestry and gene flow in the Americas.
  • GLAD includes a tool called GLAD-match to align external genetic samples with its database while protecting individual privacy, thus supporting more inclusive genomic research and enhancing personalized medicine for Latin Americans.
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Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies require ancestry-specific models for protein expression as a function of SNP genotypes. In order to improve protein expression prediction in ancestral populations historically underrepresented in genomic studies, we propose a new penalized maximum likelihood estimator for fitting ancestry-specific joint protein quantitative trait loci models.

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Aims/hypothesis: Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.

Methods: Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs.

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Background: During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.

Results: We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years).

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Article Synopsis
  • Circulating metabolite levels are indicators of human health and can be influenced by genetic factors; however, most research has focused on European populations.
  • The study utilized metabolomics data from 25,058 diverse individuals, identifying 1,778 gene loci linked to 667 metabolites and providing methods for data analysis and handling.
  • Notably, the research uncovered new genetic associations, including 108 novel gene-metabolite pairs, and highlighted sex differences in metabolism, enhancing the understanding of genetic influences on human health.
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Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL.

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Article Synopsis
  • - This study focuses on eQTL (gene expression) and sQTL (alternative splicing) analyses, specifically involving 1,012 African American participants from the Jackson Heart Study, addressing a previous bias towards European populations in similar research.
  • - Researchers identified a significant number of unique eQTL and sQTL credible sets, totaling over 42,000, with many findings being rare alleles that might not have been detected in European ancestry populations.
  • - An open database containing these QTL results has been created for easy access, allowing other researchers to query and download data efficiently.
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In most Proteome-Wide Association Studies (PWAS), variants near the protein-coding gene (±1 Mb), also known as cis single nucleotide polymorphisms (SNPs), are used to predict protein levels, which are then tested for association with phenotypes. However, proteins can be regulated through variants outside of the cis region. An intermediate GWAS step to identify protein quantitative trait loci (pQTL) allows for the inclusion of trans SNPs outside the cis region in protein-level prediction models.

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  • Venous thromboembolism (VTE) poses significant health risks, with a notable difference in incidence rates between Black and White Americans.
  • Researchers developed polygenic risk scores (PRSs) for VTE using data from both European and African-ancestry populations to enhance predictive capability.
  • Results showed that multi-ancestry PRSs slightly outperformed ancestry-specific ones in predicting VTE risk, indicating potential benefits in using diverse data for better risk assessment across populations.
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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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Article Synopsis
  • The study introduces endoPRS, a new weighted lasso model aimed at enhancing polygenic risk score (PRS) predictions for complex diseases by incorporating endophenotype data.
  • Unlike existing multi-trait PRS methods, endoPRS accounts for vertical pleiotropy, where one trait mediates the effects of another, without relying on specific genetic assumptions.
  • Simulation results and case studies, such as predicting childhood asthma risk using eosinophil count data from the UK Biobank, show that endoPRS significantly outperforms other PRS methods, highlighting its potential for improved clinical applications.
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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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  • 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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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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  • The study aimed to find genetic risk factors for cardiovascular disease (CVD) in individuals with type 2 diabetes (T2D) through a genome-wide association approach.
  • Out of 49,230 T2D participants, 8,956 experienced incident CVD events, revealing three new genetic loci associated with increased CVD risk and confirming five known coronary artery disease variants.
  • The findings suggest both novel and established genetic factors contribute to CVD risk in T2D patients, highlighting the importance of genetic screening in this population.
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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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Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA.

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