Publications by authors named "Francois Aguet"

Background/aims: The placenta expresses and releases specific microRNAs (miRNAs) into the maternal circulation that may influence insulin secretion during pregnancy. We hypothesized that specific decidual/placental miRNAs are associated with maternal insulin secretion during pregnancy.

Methods: In the Genetics of Glucose regulation in Gestation and Growth (Gen3G) prospective cohort, we estimated maternal insulin secretion using the Stumvoll first phase index derived from an oral glucose tolerance test at ~26 weeks of gestation.

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Background: Chronic obstructive pulmonary disease (COPD) exhibits marked heterogeneity in lung function decline, mortality, exacerbations, and other disease-related outcomes. Omic risk scores (ORS) estimate the cumulative contribution of omics, such as the transcriptome, proteome, and metabolome, to a particular trait. This study evaluates the predictive value of ORS for COPD-related traits in both smoking-enriched and general population cohorts.

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Only a minority of patients with rare genetic diseases are presently diagnosed by exome sequencing, suggesting that additional unrecognized pathogenic variants may reside in noncoding sequence. In this work, we describe PromoterAI, a deep neural network that accurately identifies noncoding promoter variants that dysregulate gene expression. We show that promoter variants with predicted expression-altering consequences produce outlier expression at both the RNA and protein levels in thousands of individuals and that these variants experience strong negative selection in human populations.

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We investigate the impact of germline variants on cancer patients' proteomes, encompassing 1,064 individuals across 10 cancer types. We introduced an approach, "precision peptidomics," mapping 337,469 coding germline variants onto peptides from patients' mass spectrometry data, revealing their potential impact on post-translational modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases. We identified rare pathogenic and common germline variants in cancer genes potentially affecting proteomic features, including variants altering protein abundance and structure and variants in kinases (ERBB2 and MAP2K2) impacting phosphorylation.

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Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterize 14,324 ancestrally diverse RNA-sequencing samples from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and integrate whole genome sequencing data to perform and expression and splicing quantitative trait locus (-/trans-e/sQTL) analyses in six tissues and cell types, most notably whole blood (N=6,454) and lung (N=1,291). We show this dataset enables greater detection of secondary cis-e/sQTL signals than was achieved in previous studies, and that secondary cis-eQTL and primary trans-eQTL signal discovery is not saturated even though eGene discovery is.

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Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants (pQTL) and phenotypes. Here, we examined 2,157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1,930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2,157 proteins followed a bimodal distribution (median r=0.

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Despite considerable advances in identifying risk factors for obesity development, there remains substantial gaps in our knowledge about its etiology. Variation in obesity (defined by BMI) is thought to be due in part to heritable factors; however, obesity-associated genetic variants only account for a small portion of heritability. Epigenetic regulation defined by genetic and/or environmental factors with changes in gene expression, may account for some of this "missing heritability".

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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 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 (WGS) of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program.

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Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood.

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Article Synopsis
  • A study explored how different biological factors (like proteins and metabolites) can help identify distinct groups of people with obesity who have varying risks for heart and metabolic diseases.
  • Using data from 243 participants, researchers found two groups: one (iCluster1) with favorable cholesterol levels and another (iCluster2) with higher BMI and inflammation levels.
  • The findings suggest these groups could reflect different stages of obesity-related issues, potentially influenced by factors like diet and behavior, despite similar ages across the groups.
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encodes a human long noncoding RNA (lncRNA) adjacent to , a coding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here, we report our findings in three unrelated children with a syndromic, early-onset neurodevelopmental disorder, each of whom had a de novo deletion in the locus. The children had severe encephalopathy, shared facial dysmorphisms, cortical atrophy, and cerebral hypomyelination - a phenotype that is distinct from the phenotypes of patients with haploinsufficiency.

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Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types.

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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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Reduced insulin sensitivity (insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM). We conducted transcriptomic profiling of 434 human placentas and identified a positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~26 weeks gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which, together with high gene expression levels in our placenta samples, suggests a placental or decidual source.

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Article Synopsis
  • Long non-coding RNAs (lncRNAs) make up a significant part of the human genome, but findings show that a specific lncRNA, located near a coding gene, is linked to severe developmental disorders and epilepsy through harmful mutations.
  • Researchers found three individuals with a rare deletion affecting this lncRNA, displaying similar symptoms such as developmental delays and distinct facial features, differing from typical haploinsufficiency effects.
  • The study revealed that this deletion leads to altered mRNA and protein levels in patients, demonstrating that structural variants can cause neurodevelopmental disorders and emphasizing the importance of further evaluating lncRNAs in relation to genetic diseases.
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Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium.

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Article Synopsis
  • Chronic kidney disease significantly impacts global health, particularly among individuals of African ancestry and those in the Americas, who are often excluded from genetic studies.
  • A comprehensive meta-analysis involving over 145,000 individuals from these groups led to the discovery of 41 significant genetic loci associated with kidney function, two of which hadn't been previously identified across any ancestry group.
  • The study emphasizes the importance of diverse populations in genetic research for better understanding kidney disease and suggests that multi-ancestry polygenic scores can improve predictive capabilities and clinical applications.
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Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue.

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Article Synopsis
  • Noncoding DNA helps scientists understand how genes work and how they relate to diseases in humans.
  • Researchers studied the DNA of many primates to find specific regulatory parts that are important for gene regulation.
  • They discovered a lot of these regulatory elements in humans that are different from those in other mammals, which can help explain human traits and health issues.
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Reduced insulin sensitivity (or greater insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM) pathophysiology. We conducted transcriptomic profiling of 434 human placentas and identified a strong positive association between insulin-like growth factor binding protein 1 gene () expression in the placenta and insulin sensitivity at ~ 26 weeks' gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which together with high placental gene expression levels, suggests a placental source.

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Article Synopsis
  • Identifying impactful rare genetic variants is difficult, but using personal multi-omics can help overcome this challenge, as shown in a study involving several hundred individuals over 10 years.
  • By analyzing whole-genome sequencing and other omics data, researchers found that combining expression and protein data significantly increased the detection of rare stop and frameshift variants.
  • A new Bayesian hierarchical model called "Watershed" was used to prioritize rare variants linked to significant traits, revealing variants that influence complex conditions like height, schizophrenia, and Alzheimer's disease.
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Context: Elevated body mass index (BMI) in pregnancy is associated with adverse maternal and fetal outcomes. The placental transcriptome may elucidate molecular mechanisms underlying these associations.

Objective: We examined the association of first-trimester maternal BMI with the placental transcriptome in the Gen3G prospective cohort.

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Article Synopsis
  • The study focuses on the role of noncoding genetic variants linked to complex traits, specifically examining how these variants affect gene-regulatory activity in different tissues using epigenomic analysis of histone marks.* -
  • Researchers analyzed data from 387 samples to identify 282,000 active regulatory elements (AREs), including 2,436 sex-biased and 5,397 genetically influenced AREs connected to 130,000 genetic variants (haQTLs).* -
  • The findings integrate genetic and epigenomic data to enhance understanding of disease-associated genetic loci and prioritize genetic circuits related to traits like schizophrenia through mechanisms such as gene linking scores (gLink scores).*
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Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood.

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Article Synopsis
  • Multi-omics datasets are increasingly popular, creating a need for integration methods to unlock their potential, which is addressed by a new technique called multi-set correlation and factor analysis (MCFA) that aids in analyzing complex genomic data.
  • MCFA was applied to various biological data (methylation, protein, RNA, and metabolite levels) from 614 samples, revealing strong clustering by ancestry without the need for genetic data and highlighting unique technical variations in individual datasets.
  • The study also incorporated genetic data through a genome-wide association study (GWAS), identifying several factors linked to genetic traits and metabolic diseases, thereby setting a groundwork for future research using large multi-modal genomic datasets.
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