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Article ; Online: Genetic variation across and within individuals.

Yu, Zhi / Coorens, Tim H H / Uddin, Md Mesbah / Ardlie, Kristin G / Lennon, Niall / Natarajan, Pradeep

2024

Abstract: Germline variation and somatic mutation are intricately connected and together shape human traits and disease risks. Germline variants are present from conception, but they vary between individuals and accumulate over generations. By contrast, somatic ... ...

Abstract	Germline variation and somatic mutation are intricately connected and together shape human traits and disease risks. Germline variants are present from conception, but they vary between individuals and accumulate over generations. By contrast, somatic mutations accumulate throughout life in a mosaic manner within an individual due to intrinsic and extrinsic sources of mutations and selection pressures acting on cells. Recent advancements, such as improved detection methods and increased resources for association studies, have drastically expanded our ability to investigate germline and somatic genetic variation and compare underlying mutational processes. A better understanding of the similarities and differences in the types, rates and patterns of germline and somatic variants, as well as their interplay, will help elucidate the mechanisms underlying their distinct yet interlinked roles in human health and biology.
Language	English
Publishing date	2024-03-28
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2035157-4
ISSN	1471-0064 ; 1471-0056
ISSN (online)	1471-0064
ISSN	1471-0056
DOI	10.1038/s41576-024-00709-x
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Article: Data Resources for Human Functional Genomics.

Ardlie, Kristin G / Guigó, Roderic

Current opinion in systems biology

2017 Volume 1, Page(s) 75–79

Language	English
Publishing date	2017-02-22
Publishing country	England
Document type	Journal Article
ISSN	2452-3100
ISSN	2452-3100
DOI	10.1016/j.coisb.2016.12.019
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Article ; Online: Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes.

Hivert, Marie-France / White, Frédérique / Allard, Catherine / James, Kaitlyn / Majid, Sana / Aguet, François / Ardlie, Kristin G / Florez, Jose C / Edlow, Andrea G / Bouchard, Luigi / Jacques, Pierre-Étienne / Karumanchi, S Ananth / Powe, Camille E

Nature medicine

2024

Abstract: 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 ... ...

Abstract	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. Higher circulating IGFBP1 levels were associated with greater insulin sensitivity (lesser insulin resistance) at ~26 weeks gestation in the same cohort and in two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts of pregnant women. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.
Language	English
Publishing date	2024-04-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	1220066-9
ISSN	1546-170X ; 1078-8956
ISSN (online)	1546-170X
ISSN	1078-8956
DOI	10.1038/s41591-024-02936-5
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Article ; Online: Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.

Wittich, Henry / Ardlie, Kristin / Taylor, Kent D / Durda, Peter / Liu, Yongmei / Mikhaylova, Anna / Gignoux, Chris R / Cho, Michael H / Rich, Stephen S / Rotter, Jerome I / Manichaikul, Ani / Im, Hae Kyung / Wheeler, Heather E

American journal of human genetics

2024 Volume 111, Issue 3, Page(s) 445–455

Abstract: Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start ... ...

Abstract	Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π
MeSH term(s)	Humans ; Transcriptome/genetics ; Proteome/genetics ; Multifactorial Inheritance ; Quantitative Trait Loci/genetics ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide/genetics
Chemical Substances	Proteome
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	219384-x
ISSN	1537-6605 ; 0002-9297
ISSN (online)	1537-6605
ISSN	0002-9297
DOI	10.1016/j.ajhg.2024.01.006
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Article ; Online: A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and prediction.

Liang, Yanyu / Aguet, François / Barbeira, Alvaro N / Ardlie, Kristin / Im, Hae Kyung

Nature communications

2021 Volume 12, Issue 1, Page(s) 1424

Abstract: Genetic studies of the transcriptome help bridge the gap between genetic variation and phenotypes. To maximize the potential of such studies, efficient methods to identify expression quantitative trait loci (eQTLs) and perform fine-mapping and genetic ... ...

Abstract	Genetic studies of the transcriptome help bridge the gap between genetic variation and phenotypes. To maximize the potential of such studies, efficient methods to identify expression quantitative trait loci (eQTLs) and perform fine-mapping and genetic prediction of gene expression traits are needed. Current methods that leverage both total read counts and allele-specific expression to identify eQTLs are generally computationally intractable for large transcriptomic studies. Here, we describe a unified framework that addresses these needs and is scalable to thousands of samples. Using simulations and data from GTEx, we demonstrate its calibration and performance. For example, mixQTL shows a power gain equivalent to a 29% increase in sample size for genes with sufficient allele-specific read coverage. To showcase the potential of mixQTL, we apply it to 49 GTEx tissues and find 20% additional eQTLs (FDR < 0.05, per tissue) that are significantly more enriched among trait associated variants and candidate cis-regulatory elements comparing to the standard approach.
MeSH term(s)	Alleles ; Chromosome Mapping/methods ; Databases, Genetic ; Genome-Wide Association Study ; Human Genome Project ; Humans ; Models, Genetic ; Models, Statistical ; Quantitative Trait Loci ; Regulatory Sequences, Nucleic Acid
Language	English
Publishing date	2021-03-03
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-021-21592-8
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Article ; Online: RNA-SeQC 2: efficient RNA-seq quality control and quantification for large cohorts.

Graubert, Aaron / Aguet, François / Ravi, Arvind / Ardlie, Kristin G / Getz, Gad

Bioinformatics (Oxford, England)

2021 Volume 37, Issue 18, Page(s) 3048–3050

Abstract: Summary: Post-sequencing quality control is a crucial component of RNA sequencing (RNA-seq) data generation and analysis, as sample quality can be affected by sample storage, extraction and sequencing protocols. RNA-seq is increasingly applied to ... ...

Abstract	Summary: Post-sequencing quality control is a crucial component of RNA sequencing (RNA-seq) data generation and analysis, as sample quality can be affected by sample storage, extraction and sequencing protocols. RNA-seq is increasingly applied to cohorts ranging from hundreds to tens of thousands of samples in size, but existing tools do not readily scale to these sizes, and were not designed for a wide range of sample types and qualities. Here, we describe RNA-SeQC 2, an efficient reimplementation of RNA-SeQC (DeLuca et al., 2012) that adds multiple metrics designed to characterize sample quality across a wide range of RNA-seq protocols. Availability and implementation: The command-line tool, documentation and C++ source code are available at the GitHub repository https://github.com/getzlab/rnaseqc. Code and data for reproducing the figures in this paper are available at https://github.com/getzlab/rnaseqc2-paper. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Humans ; RNA ; RNA-Seq ; Software ; Sequence Analysis, RNA/methods ; Quality Control
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2021-05-03
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btab135
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Article: A vast resource of allelic expression data spanning human tissues

Castel, Stephane E / Aguet, François / Mohammadi, Pejman / Ardlie, Kristin G / Lappalainen, Tuuli

Genome biology. 2020 Dec., v. 21, no. 1

2020

Abstract: Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 ... ...

Institution	GTEx Consortium
Abstract	Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.
Keywords	alleles ; haplotypes ; humans ; single nucleotide polymorphism ; tissues
Language	English
Dates of publication	2020-12
Size	p. 234.
Publishing place	BioMed Central
Document type	Article
ZDB-ID	2040529-7
ISSN	1474-760X ; 1465-6906
ISSN (online)	1474-760X
ISSN	1465-6906
DOI	10.1186/s13059-020-02122-z
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Higher Maternal Body Mass Index Is Associated With Lower Placental Expression of EPYC: A Genome-Wide Transcriptomic Study.

Sordillo, Joanne E / White, Frédérique / Majid, Sana / Aguet, François / Ardlie, Kristin G / Karumanchi, S Ananth / Florez, Jose C / Powe, Camille E / Edlow, Andrea G / Bouchard, Luigi / Jacques, Pierre-Etienne / Hivert, Marie-France

The Journal of clinical endocrinology and metabolism

2023 Volume 109, Issue 3, Page(s) e1159–e1166

Abstract: 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 ... ...

Abstract	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. Methods: We enrolled participants at 5 to 16 weeks of gestation and measured height and weight. We collected placenta samples at delivery. We performed whole-genome RNA sequencing using Illumina HiSeq 4000 and aligned RNA sequences based on the GTEx v8 pipeline. We conducted differential gene expression analysis of over 15 000 genes from 450 placental samples and reported the change in normalized gene expression per 1-unit increase in log2 BMI (kg/m2) as a continuous variable using Limma Voom. We adjusted models for maternal age, fetal sex, gestational age at delivery, gravidity, and surrogate variables accounting for technical variability. We compared participants with BMI of 18.5 to 24.9 mg/kg2 (N = 257) vs those with obesity (BMI ≥30 kg/m2, N = 82) in secondary analyses. Results: Participants' mean ± SD age was 28.2 ± 4.4 years and BMI was 25.4 ± 5.5 kg/m2 in early pregnancy. Higher maternal BMI was associated with lower placental expression of EPYC (slope = -1.94, false discovery rate [FDR]-adjusted P = 7.3 × 10-6 for continuous BMI; log2 fold change = -1.35, FDR-adjusted P = 3.4 × 10-3 for BMI ≥30 vs BMI 18.5-24.9 kg/m2) and with higher placental expression of IGFBP6, CHRDL1, and CXCL13 after adjustment for covariates and accounting for multiple testing (FDR < 0.05). Conclusion: Our genome-wide transcriptomic study revealed novel genes potentially implicated in placental biologic response to higher maternal BMI in early pregnancy.
MeSH term(s)	Pregnancy ; Humans ; Female ; Young Adult ; Adult ; Body Mass Index ; Placenta/metabolism ; Transcriptome ; Prospective Studies ; Gene Expression Profiling
Language	English
Publishing date	2023-10-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	3029-6
ISSN	1945-7197 ; 0021-972X
ISSN (online)	1945-7197
ISSN	0021-972X
DOI	10.1210/clinem/dgad619
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Article ; Online: A vast resource of allelic expression data spanning human tissues.

Castel, Stephane E / Aguet, François / Mohammadi, Pejman / Ardlie, Kristin G / Lappalainen, Tuuli

Genome biology

2020 Volume 21, Issue 1, Page(s) 234

Abstract	Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.
MeSH term(s)	Alleles ; Gene Expression ; Genome, Human ; Haplotypes ; Humans ; Polymorphism, Single Nucleotide ; Sequence Analysis, RNA
Language	English
Publishing date	2020-09-11
Publishing country	England
Document type	Comparative Study ; Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/s13059-020-02122-z
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Article: Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes.

Hivert, Marie-France / White, Frederique / Allard, Catherine / James, Kaitlyn / Majid, Sana / Aguet, François / Ardlie, Kristin / Edlow, Andrea / Florez, Jose / Bouchard, Luigi / Jacques, Pierre-Etienne / Karumanchi, S / Powe, Camille

Research square

2023

Abstract: 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 ... ...

Abstract	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 (
Language	English
Publishing date	2023-10-27
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-3464151/v1
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