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Artikel: Distinct explanations underlie gene-environment interactions in the UK Biobank.

Durvasula, Arun / Price, Alkes L

medRxiv : the preprint server for health sciences

2024

Abstract: The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized, but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for ... ...

Abstract	The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized, but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for a given trait and E variable. First, we detect locus-specific GxE interaction by testing for genetic correlation
Sprache	Englisch
Erscheinungsdatum	2024-04-18
Erscheinungsland	United States
Dokumenttyp	Preprint
DOI	10.1101/2023.09.22.23295969
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Accurate inference of population history in the presence of background selection.

Cousins, Trevor / Tabin, Daniel / Patterson, Nick / Reich, David / Durvasula, Arun

bioRxiv : the preprint server for biology

2024

Abstract: All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample ... ...

Abstract	All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample work has demonstrated the pervasive effects of natural selection and in particular background selection (BGS) on patterns of genetic variation in diverse species. Simulations and theoretical work have shown that methods to infer changes in effective population size over time (
Sprache	Englisch
Erscheinungsdatum	2024-01-20
Erscheinungsland	United States
Dokumenttyp	Preprint
DOI	10.1101/2024.01.18.576291
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Negative selection on complex traits limits phenotype prediction accuracy between populations.

Durvasula, Arun / Lohmueller, Kirk E

American journal of human genetics

2021 Band 108, Heft 4, Seite(n) 620–631

Abstract: Phenotype prediction is a key goal for medical genetics. Unfortunately, most genome-wide association studies are done in European populations, which reduces the accuracy of predictions via polygenic scores in non-European populations. Here, we use ... ...

Abstract	Phenotype prediction is a key goal for medical genetics. Unfortunately, most genome-wide association studies are done in European populations, which reduces the accuracy of predictions via polygenic scores in non-European populations. Here, we use population genetic models to show that human demographic history and negative selection on complex traits can result in population-specific genetic architectures. For traits where alleles with the largest effect on the trait are under the strongest negative selection, approximately half of the heritability can be accounted for by variants in Europe that are absent from Africa, leading to poor performance in phenotype prediction across these populations. Further, under such a model, individuals in the tails of the genetic risk distribution may not be identified via polygenic scores generated in another population. We empirically test these predictions by building a model to stratify heritability between European-specific and shared variants and applied it to 37 traits and diseases in the UK Biobank. Across these phenotypes, ∼30% of the heritability comes from European-specific variants. We conclude that genetic association studies need to include more diverse populations to enable the utility of phenotype prediction in all populations.
Mesh-Begriff(e)	Africa/ethnology ; Computer Simulation ; Datasets as Topic ; Europe/ethnology ; Genetic Predisposition to Disease ; Genetic Variation/genetics ; Genetics, Population ; Humans ; Models, Genetic ; Multifactorial Inheritance/genetics ; Phenotype ; Population Growth ; Selection, Genetic/genetics ; United Kingdom
Sprache	Englisch
Erscheinungsdatum	2021-03-09
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	219384-x
ISSN	1537-6605 ; 0002-9297
ISSN (online)	1537-6605
ISSN	0002-9297
DOI	10.1016/j.ajhg.2021.02.013
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Recovering signals of ghost archaic introgression in African populations.

Durvasula, Arun / Sankararaman, Sriram

Science advances

2020 Band 6, Heft 7, Seite(n) eaax5097

Abstract: While introgression from Neanderthals and Denisovans has been documented in modern humans outside Africa, the contribution of archaic hominins to the genetic variation of present-day Africans remains poorly understood. We provide complementary lines of ... ...

Abstract	While introgression from Neanderthals and Denisovans has been documented in modern humans outside Africa, the contribution of archaic hominins to the genetic variation of present-day Africans remains poorly understood. We provide complementary lines of evidence for archaic introgression into four West African populations. Our analyses of site frequency spectra indicate that these populations derive 2 to 19% of their genetic ancestry from an archaic population that diverged before the split of Neanderthals and modern humans. Using a method that can identify segments of archaic ancestry without the need for reference archaic genomes, we built genome-wide maps of archaic ancestry in the Yoruba and the Mende populations. Analyses of these maps reveal segments of archaic ancestry at high frequency in these populations that represent potential targets of adaptive introgression. Our results reveal the substantial contribution of archaic ancestry in shaping the gene pool of present-day West African populations.
Mesh-Begriff(e)	Black People/genetics ; Ethnicity/genetics ; Gene Frequency ; Genetics, Population ; Humans ; Phylogeny
Sprache	Englisch
Erscheinungsdatum	2020-02-12
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2810933-8
ISSN	2375-2548 ; 2375-2548
ISSN (online)	2375-2548
ISSN	2375-2548
DOI	10.1126/sciadv.aax5097
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Advancing admixture graph estimation via maximum likelihood network orientation.

Molloy, Erin K / Durvasula, Arun / Sankararaman, Sriram

Bioinformatics (Oxford, England)

2021 Band 37, Heft Suppl_1, Seite(n) i142–i150

Abstract: Motivation: Admixture, the interbreeding between previously distinct populations, is a pervasive force in evolution. The evolutionary history of populations in the presence of admixture can be modeled by augmenting phylogenetic trees with additional ... ...

Abstract	Motivation: Admixture, the interbreeding between previously distinct populations, is a pervasive force in evolution. The evolutionary history of populations in the presence of admixture can be modeled by augmenting phylogenetic trees with additional nodes that represent admixture events. While enabling a more faithful representation of evolutionary history, admixture graphs present formidable inferential challenges, and there is an increasing need for methods that are accurate, fully automated and computationally efficient. One key challenge arises from the size of the space of admixture graphs. Given that exhaustively evaluating all admixture graphs can be prohibitively expensive, heuristics have been developed to enable efficient search over this space. One heuristic, implemented in the popular method TreeMix, consists of adding edges to a starting tree while optimizing a suitable objective function. Results: Here, we present a demographic model (with one admixed population incident to a leaf) where TreeMix and any other starting-tree-based maximum likelihood heuristic using its likelihood function is guaranteed to get stuck in a local optimum and return an incorrect network topology. To address this issue, we propose a new search strategy that we term maximum likelihood network orientation (MLNO). We augment TreeMix with an exhaustive search for an MLNO, referring to this approach as OrientAGraph. In evaluations including previously published admixture graphs, OrientAGraph outperformed TreeMix on 4/8 models (there are no differences in the other cases). Overall, OrientAGraph found graphs with higher likelihood scores and topological accuracy while remaining computationally efficient. Lastly, our study reveals several directions for improving maximum likelihood admixture graph estimation. Availability and implementation: OrientAGraph is available on Github (https://github.com/sriramlab/OrientAGraph) under the GNU General Public License v3.0. Supplementary information: Supplementary data are available at Bioinformatics online.
Mesh-Begriff(e)	Algorithms ; Humans ; Likelihood Functions ; Phylogeny ; Population Groups ; Software
Sprache	Englisch
Erscheinungsdatum	2021-07-04
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btab267
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: A statistical model for reference-free inference of archaic local ancestry.

Durvasula, Arun / Sankararaman, Sriram

PLoS genetics

2019 Band 15, Heft 5, Seite(n) e1008175

Abstract: Statistical analyses of genomic data from diverse human populations have demonstrated that archaic hominins, such as Neanderthals and Denisovans, interbred or admixed with the ancestors of present-day humans. Central to these analyses are methods for ... ...

Abstract	Statistical analyses of genomic data from diverse human populations have demonstrated that archaic hominins, such as Neanderthals and Denisovans, interbred or admixed with the ancestors of present-day humans. Central to these analyses are methods for inferring archaic ancestry along the genomes of present-day individuals (archaic local ancestry). Methods for archaic local ancestry inference rely on the availability of reference genomes from the ancestral archaic populations for accurate inference. However, several instances of archaic admixture lack reference archaic genomes, making it difficult to characterize these events. We present a statistical method that combines diverse population genetic summary statistics to infer archaic local ancestry without access to an archaic reference genome. We validate the accuracy and robustness of our method in simulations. When applied to genomes of European individuals, our method recovers segments that are substantially enriched for Neanderthal ancestry, even though our method did not have access to any Neanderthal reference genomes.
Mesh-Begriff(e)	Animals ; Genetics, Population/methods ; Genome, Human/genetics ; Genomics/methods ; Hominidae/genetics ; Humans ; Models, Statistical ; Neanderthals/genetics
Sprache	Englisch
Erscheinungsdatum	2019-05-28
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2186725-2
ISSN	1553-7404 ; 1553-7390
ISSN (online)	1553-7404
ISSN	1553-7390
DOI	10.1371/journal.pgen.1008175
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations.

Zhang, Xinjun / Kim, Bernard / Singh, Armaan / Sankararaman, Sriram / Durvasula, Arun / Lohmueller, Kirk E

Molecular biology and evolution

2023 Band 40, Heft 1

Abstract: Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for ... ...

Abstract	Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.
Mesh-Begriff(e)	Humans ; Animals ; Neanderthals/genetics ; Reproducibility of Results ; Genetics, Population ; Adaptation, Physiological ; Selection, Genetic ; Genome, Human
Sprache	Englisch
Erscheinungsdatum	2023-01-06
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	998579-7
ISSN	1537-1719 ; 0737-4038
ISSN (online)	1537-1719
ISSN	0737-4038
DOI	10.1093/molbev/msad001
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk.

Jiang, Xilin / Zhang, Martin Jinye / Zhang, Yidong / Durvasula, Arun / Inouye, Michael / Holmes, Chris / Price, Alkes L / McVean, Gil

Nature genetics

2023 Band 55, Heft 11, Seite(n) 1854–1865

Abstract: The analysis of longitudinal data from electronic health records (EHRs) has the potential to improve clinical diagnoses and enable personalized medicine, motivating efforts to identify disease subtypes from patient comorbidity information. Here we ... ...

Abstract	The analysis of longitudinal data from electronic health records (EHRs) has the potential to improve clinical diagnoses and enable personalized medicine, motivating efforts to identify disease subtypes from patient comorbidity information. Here we introduce an age-dependent topic modeling (ATM) method that provides a low-rank representation of longitudinal records of hundreds of distinct diseases in large EHR datasets. We applied ATM to 282,957 UK Biobank samples, identifying 52 diseases with heterogeneous comorbidity profiles; analyses of 211,908 All of Us samples produced concordant results. We defined subtypes of the 52 heterogeneous diseases based on their comorbidity profiles and compared genetic risk across disease subtypes using polygenic risk scores (PRSs), identifying 18 disease subtypes whose PRS differed significantly from other subtypes of the same disease. We further identified specific genetic variants with subtype-dependent effects on disease risk. In conclusion, ATM identifies disease subtypes with differential genome-wide and locus-specific genetic risk profiles.
Mesh-Begriff(e)	Humans ; Genetic Predisposition to Disease ; Biological Specimen Banks ; Genome-Wide Association Study/methods ; Population Health ; Risk Factors ; Comorbidity ; Multifactorial Inheritance/genetics ; United Kingdom/epidemiology
Sprache	Englisch
Erscheinungsdatum	2023-10-09
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-023-01522-8
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Ancient balancing selection maintains incompatible versions of the galactose pathway in yeast.

Boocock, James / Sadhu, Meru J / Durvasula, Arun / Bloom, Joshua S / Kruglyak, Leonid

Science (New York, N.Y.)

2021 Band 371, Heft 6527, Seite(n) 415–419

Abstract: Metabolic pathways differ across species but are expected to be similar within a species. We discovered two functional, incompatible versions of the galactose pathway ... ...

Abstract	Metabolic pathways differ across species but are expected to be similar within a species. We discovered two functional, incompatible versions of the galactose pathway in
Mesh-Begriff(e)	Alleles ; Galactokinase/genetics ; Galactose/metabolism ; Metabolic Networks and Pathways/genetics ; Monosaccharide Transport Proteins/genetics ; Phosphoglucomutase/genetics ; Saccharomyces cerevisiae/genetics ; Saccharomyces cerevisiae/metabolism ; Saccharomyces cerevisiae Proteins/genetics ; Selection, Genetic ; Trans-Activators/genetics
Chemische Substanzen	GAL10 protein, S cerevisiae ; GAL2 protein, S cerevisiae ; Monosaccharide Transport Proteins ; Saccharomyces cerevisiae Proteins ; Trans-Activators ; GAL1 protein, S cerevisiae (EC 2.7.1.6) ; Galactokinase (EC 2.7.1.6) ; Phosphoglucomutase (EC 5.4.2.2) ; Galactose (X2RN3Q8DNE)
Sprache	Englisch
Erscheinungsdatum	2021-01-21
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	128410-1
ISSN	1095-9203 ; 0036-8075
ISSN (online)	1095-9203
ISSN	0036-8075
DOI	10.1126/science.aba0542
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

Zhang, Martin Jinye / Durvasula, Arun / Chiang, Colby / Koch, Evan M / Strober, Benjamin J / Shi, Huwenbo / Barton, Alison R / Kim, Samuel S / Weissbrod, Omer / Loh, Po-Ru / Gazal, Steven / Sunyaev, Shamil / Price, Alkes L

Research square

2023

Abstract: The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a ...

Abstract	The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average
Sprache	Englisch
Erscheinungsdatum	2023-12-15
Erscheinungsland	United States
Dokumenttyp	Preprint
DOI	10.21203/rs.3.rs-3707248/v1
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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