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Article ; Online: Avoiding genetic racial profiling in criminal DNA profile databases.

Blindenbach, Jacob A / Jagadeesh, Karthik A / Bejerano, Gill / Wu, David J

Nature computational science

2021 Volume 1, Issue 4, Page(s) 272–279

Abstract: DNA profiling has become an essential tool for crime solving and prevention, and CODIS (Combined DNA Index System) criminal investigation databases have flourished at the national, state and even local level. However, reports suggest that the DNA ... ...

Abstract	DNA profiling has become an essential tool for crime solving and prevention, and CODIS (Combined DNA Index System) criminal investigation databases have flourished at the national, state and even local level. However, reports suggest that the DNA profiles of all suspects searched in these databases are often retained, which could result in racial profiling. Here, we devise an approach to both enable broad DNA profile searches and preserve exonerated citizens' privacy through a real-time privacy-preserving procedure to query CODIS databases. Using our approach, an agent can privately and efficiently query a suspect's DNA profile device in the field, learning only whether the profile matches against any database profile. More importantly, the central database learns nothing about the queried profile, and thus cannot retain it. Our approach paves the way to implement privacy-preserving DNA profile searching in CODIS databases and any CODIS-like system.
Language	English
Publishing date	2021-04-26
Publishing country	United States
Document type	Journal Article
ISSN	2662-8457
ISSN (online)	2662-8457
DOI	10.1038/s43588-021-00058-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Treatment-associated remodeling of the pancreatic cancer endothelium at single-cell resolution.

Shiau, Carina / Su, Jennifer / Guo, Jimmy A / Hong, Theodore S / Wo, Jennifer Y / Jagadeesh, Karthik A / Hwang, William L

Frontiers in oncology

2022 Volume 12, Page(s) 929950

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most treatment refractory and lethal malignancies. The diversity of endothelial cell (EC) lineages in the tumor microenvironment (TME) impacts the efficacy of antineoplastic therapies, which in turn ... ...

Abstract	Pancreatic ductal adenocarcinoma (PDAC) is one of the most treatment refractory and lethal malignancies. The diversity of endothelial cell (EC) lineages in the tumor microenvironment (TME) impacts the efficacy of antineoplastic therapies, which in turn remodel EC states and distributions. Here, we present a single-cell resolution framework of diverse EC lineages in the PDAC TME in the context of neoadjuvant chemotherapy, radiotherapy, and losartan. We analyzed a custom single-nucleus RNA-seq dataset derived from 37 primary PDAC specimens (18 untreated, 14 neoadjuvant FOLFIRINOX + chemoradiotherapy, 5 neoadjuvant FOLFIRINOX + chemoradiotherapy + losartan). A single-nucleus transcriptome analysis of 15,185 EC profiles revealed two state programs (ribosomal, cycling), four lineage programs (capillary, arterial, venous, lymphatic), and one program that did not overlap significantly with prior signatures but was enriched in pathways involved in vasculogenesis, stem-like state, response to wounding and hypoxia, and endothelial-to-mesenchymal transition (reactive EndMT). A bulk transcriptome analysis of two independent cohorts (
Language	English
Publishing date	2022-09-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2022.929950
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Article ; Online: Polygenic architecture of rare coding variation across 394,783 exomes.

Weiner, Daniel J / Nadig, Ajay / Jagadeesh, Karthik A / Dey, Kushal K / Neale, Benjamin M / Robinson, Elise B / Karczewski, Konrad J / O'Connor, Luke J

Nature

2023 Volume 614, Issue 7948, Page(s) 492–499

Abstract: Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have identified thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare- ... ...

Abstract	Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have identified thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes
MeSH term(s)	Humans ; Exome/genetics ; Genetic Variation/genetics ; Genome-Wide Association Study ; Multifactorial Inheritance/genetics ; Risk Factors ; United Kingdom ; Gene Frequency ; Genetic Loci/genetics ; Schizophrenia/genetics ; Bipolar Disorder/genetics
Language	English
Publishing date	2023-02-08
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-022-05684-z
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Article ; Online: Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics.

Jagadeesh, Karthik A / Dey, Kushal K / Montoro, Daniel T / Mohan, Rahul / Gazal, Steven / Engreitz, Jesse M / Xavier, Ramnik J / Price, Alkes L / Regev, Aviv

Nature genetics

2022 Volume 54, Issue 10, Page(s) 1479–1492

Abstract: Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease, but in many cases, the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is ... ...

Abstract	Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease, but in many cases, the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is important for identifying pathogenic processes and developing therapeutics. In the present study, we introduce sc-linker, a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease. The inferred disease enrichments recapitulated known biology and highlighted notable cell-disease relationships, including γ-aminobutyric acid-ergic neurons in major depressive disorder, a disease-dependent M-cell program in ulcerative colitis and a disease-specific complement cascade process in multiple sclerosis. In autoimmune disease, both healthy and disease-dependent immune cell-type programs were associated, whereas only disease-dependent epithelial cell programs were prominent, suggesting a role in disease response rather than initiation. Our framework provides a powerful approach for identifying the cell types and cellular processes by which genetic variants influence disease.
MeSH term(s)	Depressive Disorder, Major/genetics ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Human Genetics ; Humans ; Polymorphism, Single Nucleotide/genetics ; RNA ; gamma-Aminobutyric Acid
Chemical Substances	gamma-Aminobutyric Acid (56-12-2) ; RNA (63231-63-0)
Language	English
Publishing date	2022-09-29
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-022-01187-9
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Article ; Online: SAIGE-GENE+ improves the efficiency and accuracy of set-based rare variant association tests.

Zhou, Wei / Bi, Wenjian / Zhao, Zhangchen / Dey, Kushal K / Jagadeesh, Karthik A / Karczewski, Konrad J / Daly, Mark J / Neale, Benjamin M / Lee, Seunggeun

Nature genetics

2022 Volume 54, Issue 10, Page(s) 1466–1469

Abstract: Several biobanks, including UK Biobank (UKBB), are generating large-scale sequencing data. An existing method, SAIGE-GENE, performs well when testing variants with minor allele frequency (MAF) ≤ 1%, but inflation is observed in variance component set- ... ...

Abstract	Several biobanks, including UK Biobank (UKBB), are generating large-scale sequencing data. An existing method, SAIGE-GENE, performs well when testing variants with minor allele frequency (MAF) ≤ 1%, but inflation is observed in variance component set-based tests when restricting to variants with MAF ≤ 0.1% or 0.01%. Here, we propose SAIGE-GENE+ with greatly improved type I error control and computational efficiency to facilitate rare variant tests in large-scale data. We further show that incorporating multiple MAF cutoffs and functional annotations can improve power and thus uncover new gene-phenotype associations. In the analysis of UKBB whole exome sequencing data for 30 quantitative and 141 binary traits, SAIGE-GENE+ identified 551 gene-phenotype associations.
MeSH term(s)	Gene Frequency/genetics ; Genome-Wide Association Study/methods ; Phenotype ; Exome Sequencing
Language	English
Publishing date	2022-09-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-022-01178-w
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Article ; Online: Publisher Correction: SAIGE-GENE+ improves the efficiency and accuracy of set-based rare variant association tests.

Zhou, Wei / Bi, Wenjian / Zhao, Zhangchen / Dey, Kushal K / Jagadeesh, Karthik A / Karczewski, Konrad J / Daly, Mark J / Neale, Benjamin M / Lee, Seunggeun

Nature genetics

2022 Volume 54, Issue 11, Page(s) 1755

Language	English
Publishing date	2022-10-17
Publishing country	United States
Document type	Published Erratum
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-022-01220-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity.

Gazal, Steven / Weissbrod, Omer / Hormozdiari, Farhad / Dey, Kushal K / Nasser, Joseph / Jagadeesh, Karthik A / Weiner, Daniel J / Shi, Huwenbo / Fulco, Charles P / O'Connor, Luke J / Pasaniuc, Bogdan / Engreitz, Jesse M / Price, Alkes L

Nature genetics

2022 Volume 54, Issue 6, Page(s) 827–836

Abstract: Disease-associated single-nucleotide polymorphisms (SNPs) generally do not implicate target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate ... ...

Abstract	Disease-associated single-nucleotide polymorphisms (SNPs) generally do not implicate target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate in cis. Here, we developed a heritability-based framework for evaluating and combining different S2G strategies to optimize their informativeness for common disease risk. Our optimal combined S2G strategy (cS2G) included seven constituent S2G strategies and achieved a precision of 0.75 and a recall of 0.33, more than doubling the recall of any individual strategy. We applied cS2G to fine-mapping results for 49 UK Biobank diseases/traits to predict 5,095 causal SNP-gene-disease triplets (with S2G-derived functional interpretation) with high confidence. We further applied cS2G to provide an empirical assessment of disease omnigenicity; we determined that the top 1% of genes explained roughly half of the SNP heritability linked to all genes and that gene-level architectures vary with variant allele frequency.
MeSH term(s)	Genome-Wide Association Study/methods ; Phenotype ; Polymorphism, Single Nucleotide/genetics
Language	English
Publishing date	2022-06-06
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-022-01087-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 3613: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article: Identifying disease-critical cell types and cellular processes across the human body by integration of single-cell profiles and human genetics.

Jagadeesh, Karthik A / Dey, Kushal K / Montoro, Daniel T / Mohan, Rahul / Gazal, Steven / Engreitz, Jesse M / Xavier, Ramnik J / Price, Alkes L / Regev, Aviv

bioRxiv : the preprint server for biology

2021

Abstract: Genome-wide association studies (GWAS) provide a powerful means to identify loci and genes contributing to disease, but in many cases the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is ... ...

Abstract	Genome-wide association studies (GWAS) provide a powerful means to identify loci and genes contributing to disease, but in many cases the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is important for identifying pathogenic processes and developing therapeutics. Here, we introduce sc-linker, a framework for integrating single-cell RNA-seq (scRNA-seq), epigenomic maps and GWAS summary statistics to infer the underlying cell types and processes by which genetic variants influence disease. We analyzed 1.6 million scRNA-seq profiles from 209 individuals spanning 11 tissue types and 6 disease conditions, and constructed gene programs capturing cell types, disease progression, and cellular processes both within and across cell types. We evaluated these gene programs for disease enrichment by transforming them to SNP annotations with tissue-specific epigenomic maps and computing enrichment scores across 60 diseases and complex traits (average
Language	English
Publishing date	2021-11-23
Publishing country	United States
Document type	Preprint
DOI	10.1101/2021.03.19.436212
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Article: Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq.

bioRxiv : the preprint server for biology

2023

Abstract: E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the ... ...

Abstract	E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, comβVAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.
Language	English
Publishing date	2023-01-24
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.23.525198
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Article ; Online: S-CAP extends pathogenicity prediction to genetic variants that affect RNA splicing.

Jagadeesh, Karthik A / Paggi, Joseph M / Ye, James S / Stenson, Peter D / Cooper, David N / Bernstein, Jonathan A / Bejerano, Gill

Nature genetics

2019 Volume 51, Issue 4, Page(s) 755–763

Abstract: Exome analysis of patients with a likely monogenic disease does not identify a causal variant in over half of cases. Splice-disrupting mutations make up the second largest class of known disease-causing mutations. Each individual (singleton) exome ... ...

Abstract	Exome analysis of patients with a likely monogenic disease does not identify a causal variant in over half of cases. Splice-disrupting mutations make up the second largest class of known disease-causing mutations. Each individual (singleton) exome harbors over 500 rare variants of unknown significance (VUS) in the splicing region. The existing relevant pathogenicity prediction tools tackle all non-coding variants as one amorphic class and/or are not calibrated for the high sensitivity required for clinical use. Here we calibrate seven such tools and devise a novel tool called Splicing Clinically Applicable Pathogenicity prediction (S-CAP) that is over twice as powerful as all previous tools, removing 41% of patient VUS at 95% sensitivity. We show that S-CAP does this by using its own features and not via meta-prediction over previous tools, and that splicing pathogenicity prediction is distinct from predicting molecular splicing changes. S-CAP is an important step on the path to deriving non-coding causal diagnoses.
MeSH term(s)	Exome/genetics ; Genetic Variation/genetics ; Humans ; Mutation/genetics ; RNA Splicing/genetics
Language	English
Publishing date	2019-02-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-019-0348-4
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