Biology subjects

Vasan, R. S.

Publications and source records attributed to Vasan, R. S..

14 recordsLinked to original sources

bioRxiv2025

Altered Gut Microbiota Mediates the Association between APOE Genotype and Amyloid-β Accumulation in Middle-Aged Adults

ImportanceThe apolipoprotein E (APOE) {varepsilon}4 allele is the strongest genetic risk factor for Alzheimers disease (AD), yet the mechanisms linking APOE to amyloid-{beta} (A{beta}) pathology remain incompletely understood. Emerging evidence suggests that the gut microbiome may modulate neurodegeneration; however, its role as a mediator in the APOE-A{beta} relationship remains unclear. ObjectiveTo evaluate whether specific microbial taxa mediate APOE-related effects on brain A{beta} burden in an established population-based study of middle-aged adults. Design, Setting, and ParticipantsThis cross-sectional study analyzed data from the Framingham Heart Study cohort. Data were collected at the third examination visit (n = 227, %Female = 58, mean age = 56.5 {+/-} 8.3), between 2016 and 2019. ExposuresGut bacterial DNA was sequenced using 16S rRNA, and amplicon sequence variants (ASVs) were agglomerated at various taxonomic levels (14 phyla, 70 families, and [~]140 genera). APOE genotypes were derived from blood DNA using PCR and restriction isotyping. Predicted microbial functional potential was based on KEGG Orthologs. Main Outcomes and MeasuresOverall and regional measures of cerebral amyloid-{beta} deposition were assessed using carbon-11 Pittsburgh (PiB) Compound-B PET scans. The global PiB deposition served as the primary outcome for "overall" amyloid burden. Regional amyloid deposition values were analyzed as secondary outcomes. ResultsA higher A{beta} burden was significantly associated with the depletion of protective genera (e.g., Faecalibacterium {beta} [95%CI],-0.35 [-0.40,-0.30]; Ruminococcus-0.25 [-0.27,-0.23]; Butyricicoccus-0.27 [-0.32,-0.22]) and the enrichment of pro-inflammatory taxa (e.g., Alistipes 0.07 [0.06, 0.08], Bacteroides 0.10 [0.07, 0.13]) and Barnesiella (0.18 [0.16, 0.20]). These associations were more pronounced in APOE {varepsilon}4 carriers, who exhibited a broader spectrum of microbial dysbiosis. Mediation analysis showed that Ruminococcus, Butyricicoccus, Clostridium, and Christensenellaceae collectively mediated [~]0.3-0.4% of the effect of APOE {varepsilon}4 on global A{beta} burden. Functional profiling revealed a reduced abundance of microbial genes involved in key metabolic pathways among individuals with higher A{beta} levels. Conclusion and RelevanceGut microbiome composition partially mediates the relationship between APOE {varepsilon}4 and cerebral amyloid burden. These findings support a gut-brain axis mechanism in AD and suggest that microbiome-targeted interventions may mitigate APOE-related risk.

neuroscience↗

bioRxiv2025

Adherence to Lifes Essential 8 Enhances Gut Microbiota Diversity and Cognitive Performance

Emerging evidence suggests a complex interplay among cardiovascular health, gut microbiome composition, and cognitive function. Lifes Essential 8 (LE8), developed by the American Heart Association, includes vital metrics of cardiovascular health, such as diet, physical activity, nicotine exposure, sleep health, body mass index (BMI), blood glucose, blood lipids, and blood pressure. In this study, we analyzed data from 781 participants in the Framingham Heart Study (FHS) to explore the relationship between LE8 adherence, gut microbiota, and cognitive performance. Participants with greater adherence to LE8 demonstrated significantly increased gut microbial diversity (-diversity: Chao1, p = 0.0014; Shannon, p = 0.0071) and distinct microbial compositions ({beta}-diversity: PERMANOVA p = 1e-4). Higher adherence to LE8 was related to an increased abundance of genera Barnesiella and Ruminococcus, while a reduced abundance of Clostridium was associated with higher LE8 adherence. Greater gut microbial diversity (-diversity: Chao1, p = 0.0012; Shannon, p = 0.0066), and beneficial genera like Oscillospira correlated with better global cognitive scores (GCS). Taxonomic overlap analyses revealed microbial taxa that simultaneously influence both LE8 adherence and cognitive outcomes. Mediation analyses indicated that specific taxa, including Barnesiella and Lentisphaerae, mediated the link between LE8 adherence and cognitive performance. These taxa may serve as key modulators in the gut-brain axis, connecting cardiovascular and brain health. Conversely, higher Clostridium abundance was associated with poorer cognitive performance. This study highlights the significance of comprehensive cardiovascular health metrics in shaping gut microbiota and enhancing cognitive resilience. Our findings underscore the therapeutic potential of targeting gut microbiota to mitigate cognitive decline, warranting further exploration through longitudinal and metagenomic studies.

neuroscience↗

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↗

bioRxiv2023

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

genetics↗

bioRxiv2022

Cerebral Small Vessel Disease Burden is Associated with Decreased Abundance of Gut Barnesiella intestinihominis Bacterium in the Framingham Heart Study

A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been linked to several diseases, including Alzheimers disease and related dementias (ADRD). However, the relationship between gut dysbiosis and markers of cerebral small vessel disease (cSVD), a major contributor to ADRD, is unknown. In this cross-sectional study, we examined the connection between the gut microbiome, cognitive, and neuroimaging markers of cSVD in the Framingham Heart Study (FHS). Markers of cSVD included white matter hyperintensities (WMH), peak width of skeletonized mean diffusivity (PSMD), and executive function (EF), estimated as the difference between the trail-making tests B and A. We included 972 FHS participants with MRI scans, neurocognitive measures, and stool samples and quantified the gut microbiota composition using 16S rRNA sequencing. We used multivariable association and differential abundance analyses adjusting for age, sex, BMI, and education level to estimate the association between gut microbiota and WMH, PSMD, and EF measures. Our results suggest an increased abundance of Pseudobutyrivibrio and Ruminococcus genera was associated with lower WMH and PSMD (p-values < 0.001), as well as better executive function (p-values < 0.01). In addition, in both differential and multivariable analyses, we found that the gram-negative bacterium Barnesiella intestinihominis was strongly associated with markers indicating a higher cSVD burden. Finally, functional analyses using PICRUSt implicated various KEGG pathways, including microbial quorum sensing, AMP/GMP-activated protein kinase, phenylpyruvate, and {beta}-hydroxybutyrate production previously associated with cognitive performance and dementia. Our study provides important insights into the association between the gut microbiome and cSVD, but further studies are needed to replicate the findings.

neuroscience↗

bioRxiv2021

Clonal hematopoiesis is driven by aberrant activation of TCL1A

A diverse set of driver genes, such as regulators of DNA methylation, RNA splicing, and chromatin remodeling, have been associated with pre-malignant clonal expansion of hematopoietic stem cells (HSCs). The factors mediating expansion of these mutant clones remain largely unknown, partially due to a paucity of large cohorts with longitudinal blood sampling. To circumvent this limitation, we developed and validated a method to infer clonal expansion rate from single timepoint data called PACER (passenger-approximated clonal expansion rate). Applying PACER to 5,071 persons with clonal hematopoiesis accurately recapitulated the known fitness effects due to different driver mutations. A genome-wide association study of PACER revealed that a common inherited polymorphism in the TCL1A promoter was associated with slower clonal expansion. Those carrying two copies of this protective allele had up to 80% reduced odds of having driver mutations in TET2, ASXL1, SF3B1, SRSF2, and JAK2, but not DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 by CRISPR editing led to aberrant expression of TCL1A and expansion of HSCs in vitro. These effects were abrogated in HSCs from donors carrying the protective TCL1A allele. Our results indicate that the fitness advantage of multiple common driver genes in clonal hematopoiesis is mediated through TCL1A activation. PACER is an approach that can be widely applied to uncover genetic and environmental determinants of pre-malignant clonal expansion in blood and other tissues.

genetics↗

bioRxiv2019

EDEM3 modulates plasma triglyceride level through its regulation of LRP1 expression

Human genetics studies have uncovered genetic variants that can be used to guide biological research and prioritize molecular targets for therapeutic intervention for complex diseases and metabolic conditions. We have identified a missense variant (P746S) in EDEM3 associated with lower blood triglyceride (TG) levels in >300,000 individuals. Functional analyses in cell and mouse models show that EDEM3 deficiency strongly increased the uptake of very low-density lipoprotein and thereby reduced the plasma TG level, as a result of up-regulated expression of LRP1 receptor. We demonstrate that EDEM3 deletion up-regulated the pathways for RNA and ER protein processing and transport, and consequently increased the cell surface mannose-containing glycoproteins, including LRP1. Metabolomics analyses reveal a cellular TG accumulation under EDEM3 deficiency, a profile consistent with individuals with carrying EDEM3 P746S. Our study identifies EDEM3 as a regulator of blood TG, and targeted inhibition of EDEM3 may provide a complementary approach for lowering elevated blood TG concentrations.

genetics↗

bioRxiv2019

Whole-Genome Association Analyses of Sleep-disordered Breathing Phenotypes in the NHLBI TOPMed Program

Sleep-disordered breathing (SDB) is a common disorder associated with significant morbidity. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program we report the first whole-genome sequence analysis of SDB. We identified 4 rare gene-based associations with SDB traits in 7,988 individuals of diverse ancestry and 4 replicated common variant associations with inclusion of additional samples (n=13,257). We identified a multi-ethnic set-based rare-variant association (p = 3.48 x 10-8) on chromosome X with ARMCX3. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Results highlighted associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis and HIF1A-mediated hypoxic response.

genetics↗

bioRxiv2019

Impact of rare and common genetic variants on diabetes diagnosis by hemoglobin A1c in multi-ancestry cohorts: The Trans-Omics for Precision Medicine Program.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in patients with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K/FN3KRP in Europeans and G6PD in African-Americans and Hispanics) and discovered a new African-ancestry specific low-frequency variant (rs1039215 in HBG2/HBE1, minor allele frequency (MAF)=0.03). The most associated G6PD variant (p.Val98Met, rs1050828-T, MAF=12% in African-Americans, MAF=2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693 - p.Leu353Pro, MAF=0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African-American cohorts and replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

genetics↗

bioRxiv2019

Loss-of-function genomic variants with impact on liver-related blood traits highlight potential therapeutic targets for cardiovascular disease

Cardiovascular diseases (CVD), and in particular cerebrovascular and ischemic heart diseases, are leading causes of death globally.1 Lowering circulating lipids is an important treatment strategy to reduce risk.2,3 However, some pharmaceutical mechanisms of reducing CVD may increase risk of fatty liver disease or other metabolic disorders.4,5,6 To identify potential novel therapeutic targets, which may reduce risk of CVD without increasing risk of metabolic disease, we focused on the simultaneous evaluation of quantitative traits related to liver function and CVD. Using a combination of low-coverage (5x) whole-genome sequencing and targeted genotyping, deep genotype imputation based on the TOPMed reference panel7, and genome-wide association study (GWAS) meta-analysis, we analyzed 12 liver-related blood traits (including liver enzymes, blood lipids, and markers of iron metabolism) in up to 203,476 people from three population-based cohorts of different ancestries. We identified 88 likely causal protein-altering variants that were associated with one or more liver-related blood traits. We identified several loss-of-function (LoF) variants reducing low-density lipoprotein cholesterol (LDL-C) or risk of CVD without increased risk of liver disease or diabetes, including variants in known lipid genes (e.g. APOB, LPL). A novel LoF variant, ZNF529:p.K405X, was associated with decreased levels of LDL-C (P=1.3x10-8) but demonstrated no association with liver enzymes or non-fasting blood glucose levels. Silencing of ZNF529 in human hepatocytes resulted in upregulation of LDL receptor (LDLR) and increased LDL-C uptake in the cells, suggesting that inhibition of ZNF529 or its gene product could be used for treating hypercholesterolemia and hence reduce the risk of CVD. Taken together, we demonstrate that simultaneous consideration of multiple phenotypes and a focus on rare protein-altering variants may identify promising therapeutic targets.

genomics↗

bioRxiv2019

Recovery of trait heritability from whole genome sequence data

Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be largely recovered from whole-genome sequence (WGS) data on 25,465 unrelated individuals of European ancestry. We assigned 33.7 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned genetic variance accordingly. The estimated heritability was 0.68 (SE 0.10) for height and 0.30 (SE 0.10) for BMI, with a range of ~0.60 - 0.71 for height and ~0.25 - 0.35 for BMI, depending on quality control and analysis strategies. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection thereon. Cumulatively variants with 0.0001 < MAF < 0.1 explained 0.47 (SE 0.07) and 0.30 (SE 0.10) of heritability for height and BMI, respectively. Our results imply that rare variants, in particular those in regions of low LD, is a major source of the still missing heritability of complex traits and disease.

genetics↗

bioRxiv2018

Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies

With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

genetics↗

bioRxiv2018

A Fully-Adjusted Two-Stage Procedure for Rank Normalization in Genetic Association Studies

When testing genotype-phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. While it has been shown that applying a rank-normalization transformation to trait values before testing may improve these statistical properties, the factor driving them is not the trait distribution itself, but its residual distribution after regression on both covariates and genotype. Because genotype is expected to have a small effect (if any) investigators now routinely use a two-stage method, in which they first regress the trait on covariates, obtain residuals, rank-normalize them, and then secondly use the rank-normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice no further adjustment is done in the second stage. Here, we show that this widely-used approach can lead to tests with undesirable statistical properties, due to both a combination of a mis-specified mean-variance relationship, and remaining covariate associations between the rank-normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome-wide and whole-genome sequencing association studies. We further propose and evaluate an alternative fully-adjusted two-stage approach that adjusts for covariates both when residuals are obtained, and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.

genetics↗

bioRxiv2017

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

Deep-coverage whole genome sequencing at the population level is now feasible and offers potential advantages for locus discovery, particularly in the analysis rare mutations in non-coding regions. Here, we performed whole genome sequencing in 16,324 participants from four ancestries at mean depth >29X and analyzed correlations of genotypes with four quantitative traits - plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. We conducted a discovery analysis including common or rare variants in coding as well as non-coding regions and developed a framework to interpret genome sequence for dyslipidemia risk. Common variant association yielded loci previously described with the exception of a few variants not captured earlier by arrays or imputation. In coding sequence, rare variant association yielded known Mendelian dyslipidemia genes and, in non-coding sequence, we detected no rare variant association signals after application of four approaches to aggregate variants in non-coding regions. We developed a new, genome-wide polygenic score for LDL-C and observed that a high polygenic score conferred similar effect size to a monogenic mutation (~30 mg/dl higher LDL-C for each); however, among those with extremely high LDL-C, a high polygenic score was considerably more prevalent than a monogenic mutation (23% versus 2% of participants, respectively).

genomics↗