Biology subjects

Post, W.

Publications and source records attributed to Post, W..

6 recordsLinked to original sources

bioRxiv2023

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.

genetics↗

bioRxiv2022

Dorsal Hippocampus To Nucleus Accumbens Projections Drive Reinforcement Via Activation of Accumbal Dynorphin Neurons.

The hippocampus represents a key structure in the integration of emotional processing, learning and memory, and reward-related behaviors. While the ventral subdivision of the hippocampus (vHPC) is involved in processing emotional values of salient stimuli and goal-directed behaviors, the dorsal hippocampus (dHPC) plays a critical role in episodic, spatial, and associative memory. In addition, it has been shown that the dHPC is necessary for context- and cue-associated reward behaviors, including the expression of reward seeking. The nucleus accumbens (NAc), a central structure in the mesolimbic reward pathway, integrates the salience of aversive and rewarding stimuli and its activity is sufficient to drive aversive and appetitive behaviors. Recent evidence has demonstrated that dHPC[->]Nucleus Accumbens (NAc) pathway is necessary for expression of a conditioned place preference. However, despite years of groundbreaking research and identification of direct projections from the dHPC to the NAc, the sufficiency for dHPC[->]NAC inputs to drive reinforcement and reward associated behavior remains to be determined. Here using a wide range of complementary and cutting-edge techniques including behavior, in-vivo manipulation using optogenetics, chemogenetics, brain clearing, local field potential and fiber photometry recordings, we demonstrate that activation of excitatory projections from the CA1 subregion of the dHPC (dCA1) is sufficient to drive reinforcing behaviors. In addition, we provide strong evidence that this reinforcing behavior is driven by 1) a direct projection from the dCA1 to the NAc and 2) enhanced glutamatergic signaling within the NAc. Furthermore, we uncovered that while dCA1 stimulation increases the activity of both enkephalin- and dynorphin-containing medium spiny neurons in the NAc, the selective activity of dynorphin-containing neurons is necessary for the expression of this reinforcing behavior. Our findings shed light on a novel pathway governing reinforcement and further extend the role of the dHPC on reward seeking.

neuroscience↗

bioRxiv2020

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To better understand etiological pathways that might lead to discovery of new treatments or prevention strategies, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome while also exploring associations with common variants. Methods and ResultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR=1.80, 95% confidence interval: 1.43, 2.27; P=7.12 x 10-7). Three common variants, rs9349379 in PHACTR1, and rs1333048 and rs4977574 in the 9p21 region, were significantly associated with prevalent CHD. Four common variants (rs4977574, rs10757278, rs1333049, and rs1333048) within the 9p21 locus were significantly associated with incident MI. We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) [≥] 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. ConclusionThis study confirmed previously reported loci influencing heart disease risk, and one single variant and three genes associated with MI and CHD were newly identified and warrant future investigation.

genetics↗

bioRxiv2019

Mitochondrial DNA Copy Number and Incident Atrial Fibrillation

BackgroundMechanistic studies suggests that mitochondria DNA (mtDNA) dysfunction may be associated with increased risk of atrial fibrillation (AF). The association between mtDNA copy number (mtDNA-CN) and incident AF in the general population, however, remains unknown. MethodsWe conducted prospective analyses of 19,709 participants from the Atherosclerosis Risk in Communities Study (ARIC), the Multi-Ethnic Study of Atherosclerosis (MESA) and the Cardiovascular Health Study (CHS). mtDNA-CN from peripheral blood was calculated from probe intensities on the Affymetrix Genome-Wide Human single nucleotide polymorphisms (SNP) Array 6.0 in ARIC and MESA, and from multiplexed real time quantitative polymerase chain reaction (qPCR) in CHS. Incident AF cases were identified through electrocardiograms, review of hospital discharge codes, Medicare claims, and death certificates. ResultsThe median follow-up time was 21.4 years in ARIC, 12.9 years in MESA and 11.0 years in CHS, during which 4,021 participants developed incident atrial fibrillation (1,761 in ARIC, 790 in MESA, and 1,470 in CHS). The fully-adjusted pooled hazard ratio for incident atrial fibrillation comparing the 1st to the 5th quintile of mitochondria DNA copy number was 1.13 (1.01, 1.27). The fully-adjusted pooled hazard ratio comparing the 10th vs the 90th percentile of mitochondria DNA copy number was 1.13 (1.04, 1.24). Dose-response spline analysis also showed an inverse association between mitochondria DNA copy number and hazard for atrial fibrillation for all three cohorts. These associations were consistent across subgroups. ConclusionsMitochondria DNA copy number was inversely associated with the risk of AF independent of traditional cardiovascular risk factors. These findings implicate mitochondria DNA copy number as a novel risk factor for atrial fibrillation. Further research is warranted to understand the underlying mechanisms and to evaluate the role of mitochondria DNA copy number in the management of atrial fibrillation risk.

genetics↗

bioRxiv2019

Multi-ethnic genome-wide association study of decomposed cardioelectric phenotypes illustrates strategies to identify and characterize evidence of shared genetic effects for complex traits

BackgroundPublished genome-wide association studies (GWAS) are mainly European-centric, examine a narrow view of phenotypic variation, and infrequently interrogate genetic effects shared across traits. We therefore examined the extent to which a multi-ethnic, combined trait GWAS of phenotypes that map to well-defined biology can enable detection and characterization of complex trait loci.\n\nMethodsWith 1000 Genomes Phase 3 imputed data in 34,668 participants (15% African American; 3% Chinese American; 51% European American; 30% Hispanic/Latino), we performed covariate-adjusted univariate GWAS of six contiguous electrocardiogram (ECG) traits that decomposed an average heartbeat and two commonly reported composite ECG traits that summed contiguous traits. Combined phenotype testing was performed using the adaptive sum of powered scores test (aSPU).\n\nResultsWe identified six novel and 87 known ECG trait loci (aSPU p-value < 5E-9). Lead SNP rs3211938 at novel locus CD36 was common in African Americans (minor allele frequency=10%) and near-monomorphic in European Americans, with effect sizes for the composite trait, QT interval, among the largest reported. Only one novel locus was detected for the composite traits, due to opposite directions of effects across contiguous traits that summed to near-zero. Combined phenotype testing did not detect novel loci unapparent by univariate testing. However, this approach aided locus characterization, particularly when loci harbored multiple independent signals that differed by trait.\n\nConclusionsDespite including one-third as few participants as the largest published GWAS of ECG traits, our study identifies multiple novel ECG genetic loci, emphasizing the importance of ancestral diversity and phenotype measurement in this era of ever-growing GWAS.\n\nAUTHOR SUMMARYWe leveraged a multiethnic cohort with precise measures of cardioelectric function to identify novel genetic loci affecting this complex, multifaceted phenotype. The success of our approach stresses the importance of phenotypic precision and participant diversity for future locus discovery and characterization efforts, and cautions against compromises made in genome-wide association studies to pursue ever-growing sample sizes.

epidemiology↗

bioRxiv2019

An open resource of structural variation for medical and population genetics

Structural variants (SVs) rearrange large segments of the genome and can have profound consequences for evolution and human diseases. As national biobanks, disease association studies, and clinical genetic testing grow increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral for interpreting genetic variation. To date, no large-scale reference maps of SVs exist from high-coverage sequencing comparable to those available for point mutations in protein-coding genes. Here, we constructed a reference atlas of SVs across 14,891 genomes from diverse global populations (54% non-European) as a component of gnomAD. We discovered a rich landscape of 433,371 distinct SVs, including 5,295 multi-breakpoint complex SVs across 11 mutational subclasses, and examples of localized chromosome shattering, as in chromothripsis. The average individual harbored 7,439 SVs, which accounted for 25-29% of all rare protein-truncating events per genome. We found strong correlations between constraint against damaging point mutations and rare SVs that both disrupt and duplicate protein-coding sequence, suggesting intolerance to reciprocal dosage alterations for a subset of tightly regulated genes. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than any effect on noncoding SVs. Finally, we benchmarked carrier rates for medically relevant SVs, finding very large ([≥]1Mb) rare SVs in 3.8% of genomes (~1:26 individuals) and clinically reportable incidental SVs in 0.18% of genomes (~1:556 individuals). These data have been integrated directly into the gnomAD browser (https://gnomad.broadinstitute.org) and will have broad utility for population genetics, disease association, and diagnostic screening.

genomics↗