Publications by authors named "Stephen B Montgomery"

108 Publications

Compound heterozygous variants in progressive myoclonus epilepsy.

J Neurogenet 2021 Mar-Jun;35(2):74-83. Epub 2021 May 10.

NIH Undiagnosed Diseases Program, Common Fund, Office of the Director, NIH and National Human Genome Research Institute, NIH, Bethesda, MD, USA.

KCTD7 is a member of the potassium channel tetramerization domain-containing protein family and has been associated with progressive myoclonic epilepsy (PME), characterized by myoclonus, epilepsy, and neurological deterioration. Here we report four affected individuals from two unrelated families in which we identified compound heterozygous single nucleotide variants through exome sequencing. RNAseq was used to detect a non-annotated splicing junction created by a synonymous variant in the second family. Whole-cell patch-clamp analysis of neuroblastoma cells overexpressing the patients' variant alleles demonstrated aberrant potassium regulation. While all four patients experienced many of the common clinical features of PME, they also showed variable phenotypes not previously reported, including dysautonomia, brain pathology findings including a significantly reduced thalamus, and the lack of myoclonic seizures. To gain further insight into the pathogenesis of the disorder, zinc finger nucleases were used to generate knockout zebrafish. homozygous mutants showed global dysregulation of gene expression and increased transcription of , which has previously been correlated with seizure activity in animal models. Together these findings expand the known phenotypic spectrum of -associated PME, report a new animal model for future studies, and contribute valuable insights into the disease.
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http://dx.doi.org/10.1080/01677063.2021.1892095DOI Listing
May 2021

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease.

Cell 2021 May 16;184(10):2633-2648.e19. Epub 2021 Apr 16.

Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University, Stanford, CA 94305, USA. Electronic address:

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.
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http://dx.doi.org/10.1016/j.cell.2021.03.050DOI Listing
May 2021

Functional and structural analysis of cytokine-selective IL6ST defects that cause recessive hyper-IgE syndrome.

J Allergy Clin Immunol 2021 Mar 23. Epub 2021 Mar 23.

Translational Gastroenterology Unit, University of Oxford, Oxford, United Kingdom; Department of Paediatrics, University of Oxford, Oxford, United Kingdom; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, United Kingdom.

Background: Biallelic variants in IL6ST, encoding GP130, cause a recessive form of hyper-IgE syndrome (HIES) characterized by high IgE level, eosinophilia, defective acute phase response, susceptibility to bacterial infections, and skeletal abnormalities due to cytokine-selective loss of function in GP130, with defective IL-6 and IL-11 and variable oncostatin M (OSM) and IL-27 levels but sparing leukemia inhibitory factor (LIF) signaling.

Objective: Our aim was to understand the functional and structural impact of recessive HIES-associated IL6ST variants.

Methods: We investigated a patient with HIES by using exome, genome, and RNA sequencing. Functional assays assessed IL-6, IL-11, IL-27, OSM, LIF, CT-1, CLC, and CNTF signaling. Molecular dynamics simulations and structural modeling of GP130 cytokine receptor complexes were performed.

Results: We identified a patient with compound heterozygous novel missense variants in IL6ST (p.Ala517Pro and the exon-skipping null variant p.Gly484_Pro518delinsArg). The p.Ala517Pro variant resulted in a more profound IL-6- and IL-11-dominated signaling defect than did the previously identified recessive HIES IL6ST variants p.Asn404Tyr and p.Pro498Leu. Molecular dynamics simulations suggested that the p.Ala517Pro and p.Asn404Tyr variants result in increased flexibility of the extracellular membrane-proximal domains of GP130. We propose a structural model that explains the cytokine selectivity of pathogenic IL6ST variants that result in recessive HIES. The variants destabilized the conformation of the hexameric cytokine receptor complexes, whereas the trimeric LIF-GP130-LIFR complex remained stable through an additional membrane-proximal interaction. Deletion of this membrane-proximal interaction site in GP130 consequently caused additional defective LIF signaling and Stüve-Wiedemann syndrome.

Conclusion: Our data provide a structural basis to understand clinical phenotypes in patients with IL6ST variants.
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http://dx.doi.org/10.1016/j.jaci.2021.02.044DOI Listing
March 2021

Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics.

Nat Genet 2021 03 4;53(3):313-321. Epub 2021 Mar 4.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.

Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.
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http://dx.doi.org/10.1038/s41588-021-00800-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944648PMC
March 2021

Exploiting the GTEx resources to decipher the mechanisms at GWAS loci.

Genome Biol 2021 Jan 26;22(1):49. Epub 2021 Jan 26.

Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.
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http://dx.doi.org/10.1186/s13059-020-02252-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836161PMC
January 2021

Evaluating the Genomic Parameters Governing rAAV-Mediated Homologous Recombination.

Mol Ther 2021 03 26;29(3):1028-1046. Epub 2020 Nov 26.

Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA. Electronic address:

Recombinant adeno-associated virus (rAAV) vectors have the unique ability to promote targeted integration of transgenes via homologous recombination at specified genomic sites, reaching frequencies of 0.1%-1%. We studied genomic parameters that influence targeting efficiencies on a large scale. To do this, we generated more than 1,000 engineered, doxycycline-inducible target sites in the human HAP1 cell line and infected this polyclonal population with a library of AAV-DJ targeting vectors, with each carrying a unique barcode. The heterogeneity of barcode integration at each target site provided an assessment of targeting efficiency at that locus. We compared targeting efficiency with and without target site transcription for identical chromosomal positions. Targeting efficiency was enhanced by target site transcription, while chromatin accessibility was associated with an increased likelihood of targeting. ChromHMM chromatin states characterizing transcription and enhancers in wild-type K562 cells were also associated with increased AAV-HR efficiency with and without target site transcription, respectively. Furthermore, the amenability of a site to targeting was influenced by the endogenous transcriptional level of intersecting genes. These results define important parameters that may not only assist in designing optimal targeting vectors for genome editing, but also provide new insights into the mechanism of AAV-mediated homologous recombination.
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http://dx.doi.org/10.1016/j.ymthe.2020.11.025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934627PMC
March 2021

Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases.

Nat Genet 2020 11 26;52(11):1158-1168. Epub 2020 Oct 26.

Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.

Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer's and Parkinson's diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson's disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.
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http://dx.doi.org/10.1038/s41588-020-00721-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606627PMC
November 2020

Transcriptomic signatures across human tissues identify functional rare genetic variation.

Science 2020 09 10;369(6509). Epub 2020 Sep 10.

University of Mississippi Medical Center, Jackson, MS, USA.

Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.
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http://dx.doi.org/10.1126/science.aaz5900DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646251PMC
September 2020

The impact of sex on gene expression across human tissues.

Science 2020 09;369(6509)

Department of Statistics, University of Chicago, Chicago, IL, USA.

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.
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http://dx.doi.org/10.1126/science.aba3066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136152PMC
September 2020

Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx.

Genome Biol 2020 09 11;21(1):233. Epub 2020 Sep 11.

Department of Genetics, Stanford University, Stanford, CA, USA.

Background: Population structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the v8 release also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes the impact of population structure on GWAS colocalization.

Results: Here, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. We perform genome-wide cis-eQTL mapping using admixed samples in seven tissues, adjusted by either global or local ancestry. Consistent with previous work, we observe improved power with local ancestry adjustment. At loci where the two adjustments produce different lead variants, we observe 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up.

Conclusions: We provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.
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http://dx.doi.org/10.1186/s13059-020-02113-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488497PMC
September 2020

Discovery and quality analysis of a comprehensive set of structural variants and short tandem repeats.

Nat Commun 2020 06 10;11(1):2928. Epub 2020 Jun 10.

Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.

Structural variants (SVs) and short tandem repeats (STRs) are important sources of genetic diversity but are not routinely analyzed in genetic studies because they are difficult to accurately identify and genotype. Because SVs and STRs range in size and type, it is necessary to apply multiple algorithms that incorporate different types of evidence from sequencing data and employ complex filtering strategies to discover a comprehensive set of high-quality and reproducible variants. Here we assemble a set of 719 deep whole genome sequencing (WGS) samples (mean 42×) from 477 distinct individuals which we use to discover and genotype a wide spectrum of SV and STR variants using five algorithms. We use 177 unique pairs of genetic replicates to identify factors that affect variant call reproducibility and develop a systematic filtering strategy to create of one of the most complete and well characterized maps of SVs and STRs to date.
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http://dx.doi.org/10.1038/s41467-020-16481-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287045PMC
June 2020

Properties of structural variants and short tandem repeats associated with gene expression and complex traits.

Nat Commun 2020 06 10;11(1):2927. Epub 2020 Jun 10.

Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.

Structural variants (SVs) and short tandem repeats (STRs) comprise a broad group of diverse DNA variants which vastly differ in their sizes and distributions across the genome. Here, we identify genomic features of SV classes and STRs that are associated with gene expression and complex traits, including their locations relative to eGenes, likelihood of being associated with multiple eGenes, associated eGene types (e.g., coding, noncoding, level of evolutionary constraint), effect sizes, linkage disequilibrium with tagging single nucleotide variants used in GWAS, and likelihood of being associated with GWAS traits. We identify a set of high-impact SVs/STRs associated with the expression of three or more eGenes via chromatin loops and show that they are highly enriched for being associated with GWAS traits. Our study provides insights into the genomic properties of structural variant classes and short tandem repeats that are associated with gene expression and human traits.
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http://dx.doi.org/10.1038/s41467-020-16482-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286898PMC
June 2020

Molecular Choreography of Acute Exercise.

Cell 2020 05;181(5):1112-1130.e16

Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.
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http://dx.doi.org/10.1016/j.cell.2020.04.043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299174PMC
May 2020

FAM13A affects body fat distribution and adipocyte function.

Nat Commun 2020 03 19;11(1):1465. Epub 2020 Mar 19.

Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.

Genetic variation in the FAM13A (Family with Sequence Similarity 13 Member A) locus has been associated with several glycemic and metabolic traits in genome-wide association studies (GWAS). Here, we demonstrate that in humans, FAM13A alleles are associated with increased FAM13A expression in subcutaneous adipose tissue (SAT) and an insulin resistance-related phenotype (e.g. higher waist-to-hip ratio and fasting insulin levels, but lower body fat). In human adipocyte models, knockdown of FAM13A in preadipocytes accelerates adipocyte differentiation. In mice, Fam13a knockout (KO) have a lower visceral to subcutaneous fat (VAT/SAT) ratio after high-fat diet challenge, in comparison to their wild-type counterparts. Subcutaneous adipocytes in KO mice show a size distribution shift toward an increased number of smaller adipocytes, along with an improved adipogenic potential. Our results indicate that GWAS-associated variants within the FAM13A locus alter adipose FAM13A expression, which in turn, regulates adipocyte differentiation and contribute to changes in body fat distribution.
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http://dx.doi.org/10.1038/s41467-020-15291-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081215PMC
March 2020

A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation.

Cell Host Microbe 2020 01 17;27(1):140-153.e9. Epub 2019 Dec 17.

Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine (Hematology, Blood and Marrow Transplantation) Stanford University, Stanford, CA 94305, USA. Electronic address:

Mobile genetic elements (MGEs) contribute to bacterial adaptation and evolution; however, high-throughput, unbiased MGE detection remains challenging. We describe MGEfinder, a bioinformatic toolbox that identifies integrative MGEs and their insertion sites by using short-read sequencing data. MGEfinder identifies the genomic site of each MGE insertion and infers the identity of the inserted sequence. We apply MGEfinder to 12,374 sequenced isolates of 9 prevalent bacterial pathogens, including Mycobacterium tuberculosis, Staphylococcus aureus, and Escherichia coli, and identify thousands of MGEs, including candidate insertion sequences, conjugative transposons, and prophage elements. The MGE repertoire and insertion rates vary across species, and integration sites often cluster near genes related to antibiotic resistance, virulence, and pathogenicity. MGE insertions likely contribute to antibiotic resistance in laboratory experiments and clinical isolates. Additionally, we identified thousands of mobility genes, a subset of which have unknown function opening avenues for exploration. Future application of MGEfinder to commensal bacteria will further illuminate bacterial adaptation and evolution.
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http://dx.doi.org/10.1016/j.chom.2019.10.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952549PMC
January 2020

Genetic regulation of gene expression and splicing during a 10-year period of human aging.

Genome Biol 2019 11 4;20(1):230. Epub 2019 Nov 4.

Department of Pathology, Stanford University School of Medicine, Stanford, USA.

Background: Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age.

Results: We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age.

Conclusions: These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.
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http://dx.doi.org/10.1186/s13059-019-1840-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827221PMC
November 2019

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

Cell 2019 10;179(4):984-1002.e36

Wellcome Sanger Institute, Hinxton, Cambridge, UK.

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.
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http://dx.doi.org/10.1016/j.cell.2019.10.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202134PMC
October 2019

Atheroprotective roles of smooth muscle cell phenotypic modulation and the TCF21 disease gene as revealed by single-cell analysis.

Nat Med 2019 08 29;25(8):1280-1289. Epub 2019 Jul 29.

Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.

In response to various stimuli, vascular smooth muscle cells (SMCs) can de-differentiate, proliferate and migrate in a process known as phenotypic modulation. However, the phenotype of modulated SMCs in vivo during atherosclerosis and the influence of this process on coronary artery disease (CAD) risk have not been clearly established. Using single-cell RNA sequencing, we comprehensively characterized the transcriptomic phenotype of modulated SMCs in vivo in atherosclerotic lesions of both mouse and human arteries and found that these cells transform into unique fibroblast-like cells, termed 'fibromyocytes', rather than into a classical macrophage phenotype. SMC-specific knockout of TCF21-a causal CAD gene-markedly inhibited SMC phenotypic modulation in mice, leading to the presence of fewer fibromyocytes within lesions as well as within the protective fibrous cap of the lesions. Moreover, TCF21 expression was strongly associated with SMC phenotypic modulation in diseased human coronary arteries, and higher levels of TCF21 expression were associated with decreased CAD risk in human CAD-relevant tissues. These results establish a protective role for both TCF21 and SMC phenotypic modulation in this disease.
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http://dx.doi.org/10.1038/s41591-019-0512-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274198PMC
August 2019

Identifying causal variants and genes using functional genomics in specialized cell types and contexts.

Hum Genet 2020 Jan 17;139(1):95-102. Epub 2019 Jul 17.

Department of Pathology, Stanford University, Stanford, USA.

A central goal in human genetics is the identification of variants and genes that influence the risk of polygenic diseases. In the past decade, genome-wide association studies (GWAS) have identified tens of thousands of genetic loci associated with various diseases. Since the majority of such loci lie within non-coding regions and have many candidate variants in linkage disequilibrium, it has been challenging to accurately identify specific causal variants and genes. To aid in their discovery a variety of statistical and experimental approaches have been developed. These approaches often borrow information from functional genomics assays such as ATAC-seq, ChIP-seq and RNA-seq to annotate functional variants and identify regulatory relationships between variants and genes. While such approaches are powerful, given the diversity of cell types and environments, it is paramount to select disease-relevant contexts for follow-up analyses. In this review, we discuss the latest developments, challenges, and best practices for determining the causal mechanisms of polygenic disease risk variants with functional genomics data from specialized cell types.
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http://dx.doi.org/10.1007/s00439-019-02044-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6942616PMC
January 2020

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure.

Nat Commun 2019 06 24;10(1):2760. Epub 2019 Jun 24.

Division of Cardiology, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure.
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http://dx.doi.org/10.1038/s41467-019-10591-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6591478PMC
June 2019

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts.

Nat Med 2019 06 3;25(6):911-919. Epub 2019 Jun 3.

Department of Computer Science, Stanford University, Stanford, CA, USA.

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases. This includes muscle biopsies from patients with undiagnosed rare muscle disorders, and cultured fibroblasts from patients with mitochondrial disorders. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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http://dx.doi.org/10.1038/s41591-019-0457-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6634302PMC
June 2019

Genetic analyses of human fetal retinal pigment epithelium gene expression suggest ocular disease mechanisms.

Commun Biol 2019 20;2:186. Epub 2019 May 20.

2Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305 USA.

The retinal pigment epithelium (RPE) serves vital roles in ocular development and retinal homeostasis but has limited representation in large-scale functional genomics datasets. Understanding how common human genetic variants affect RPE gene expression could elucidate the sources of phenotypic variability in selected monogenic ocular diseases and pinpoint causal genes at genome-wide association study (GWAS) loci. We interrogated the genetics of gene expression of cultured human fetal RPE (fRPE) cells under two metabolic conditions and discovered hundreds of shared or condition-specific expression or splice quantitative trait loci (e/sQTLs). Co-localizations of fRPE e/sQTLs with age-related macular degeneration (AMD) and myopia GWAS data suggest new candidate genes, and mechanisms by which a common allele contributes to both increased AMD risk and decreased myopia risk. Our study highlights the unique transcriptomic characteristics of fRPE and provides a resource to connect e/sQTLs in a critical ocular cell type to monogenic and complex eye disorders.
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http://dx.doi.org/10.1038/s42003-019-0430-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527609PMC
April 2020

Abundant associations with gene expression complicate GWAS follow-up.

Nat Genet 2019 05;51(5):768-769

Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.

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http://dx.doi.org/10.1038/s41588-019-0404-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904208PMC
May 2019

Identification of 22 novel loci associated with urinary biomarkers of albumin, sodium, and potassium excretion.

Kidney Int 2019 05 12;95(5):1197-1208. Epub 2019 Mar 12.

Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Electronic address:

Urine biomarkers reflecting kidney function and handling of dietary sodium and potassium are strongly associated with several common diseases including chronic kidney disease, cardiovascular disease, and diabetes mellitus. Knowledge about the genetic determinants of these biomarkers may shed light on pathophysiological mechanisms underlying the development of these diseases. We performed genome-wide association studies of urinary albumin: creatinine ratio (UACR), urinary potassium: creatinine ratio (UK/UCr), urinary sodium: creatinine ratio (UNa/UCr) and urinary sodium: potassium ratio (UNa/UK) in up to 218,450 (discovery) and 109,166 (replication) unrelated individuals of European ancestry from the UK Biobank. Further, we explored genetic correlations, tissue-specific gene expression, and possible genes implicated in the regulation of these biomarkers. After replication, we identified 19 genome-wide significant independent loci associated with UACR, 6 each with UK/UCr and UNa/UCr, and 4 with UNa/UK. In addition to 22 novel associations, we confirmed several established associations, including between the CUBN locus and microalbuminuria. We detected high pairwise genetic correlation across the urinary biomarkers, and between their levels and several physiological measurements. We highlight GIPR, a potential diabetes drug target, as possibly implicated in the genetic control of urinary potassium excretion, and NRBP1, a locus associated with gout, as plausibly involved in sodium and albumin excretion. Overall, we identified 22 novel genome-wide significant associations with urinary biomarkers and confirmed several previously established associations, providing new insights into the genetic basis of these traits and their connection to chronic diseases.
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http://dx.doi.org/10.1016/j.kint.2018.12.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535090PMC
May 2019

Diagnosing rare diseases after the exome.

Cold Spring Harb Mol Case Stud 2018 12 17;4(6). Epub 2018 Dec 17.

Department of Pathology, Stanford University, Stanford, California 94305, USA.

High-throughput sequencing has ushered in a diversity of approaches for identifying genetic variants and understanding genome structure and function. When applied to individuals with rare genetic diseases, these approaches have greatly accelerated gene discovery and patient diagnosis. Over the past decade, exome sequencing has emerged as a comprehensive and cost-effective approach to identify pathogenic variants in the protein-coding regions of the genome. However, for individuals in whom exome-sequencing fails to identify a pathogenic variant, we discuss recent advances that are helping to reduce the diagnostic gap.
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http://dx.doi.org/10.1101/mcs.a003392DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6318767PMC
December 2018

Functional regulatory mechanism of smooth muscle cell-restricted LMOD1 coronary artery disease locus.

PLoS Genet 2018 11 16;14(11):e1007755. Epub 2018 Nov 16.

Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.

Recent genome-wide association studies (GWAS) have identified multiple new loci which appear to alter coronary artery disease (CAD) risk via arterial wall-specific mechanisms. One of the annotated genes encodes LMOD1 (Leiomodin 1), a member of the actin filament nucleator family that is highly enriched in smooth muscle-containing tissues such as the artery wall. However, it is still unknown whether LMOD1 is the causal gene at this locus and also how the associated variants alter LMOD1 expression/function and CAD risk. Using epigenomic profiling we recently identified a non-coding regulatory variant, rs34091558, which is in tight linkage disequilibrium (LD) with the lead CAD GWAS variant, rs2820315. Herein we demonstrate through expression quantitative trait loci (eQTL) and statistical fine-mapping in GTEx, STARNET, and human coronary artery smooth muscle cell (HCASMC) datasets, rs34091558 is the top regulatory variant for LMOD1 in vascular tissues. Position weight matrix (PWM) analyses identify the protective allele rs34091558-TA to form a conserved Forkhead box O3 (FOXO3) binding motif, which is disrupted by the risk allele rs34091558-A. FOXO3 chromatin immunoprecipitation and reporter assays show reduced FOXO3 binding and LMOD1 transcriptional activity by the risk allele, consistent with effects of FOXO3 downregulation on LMOD1. LMOD1 knockdown results in increased proliferation and migration and decreased cell contraction in HCASMC, and immunostaining in atherosclerotic lesions in the SMC lineage tracing reporter mouse support a key role for LMOD1 in maintaining the differentiated SMC phenotype. These results provide compelling functional evidence that genetic variation is associated with dysregulated LMOD1 expression/function in SMCs, together contributing to the heritable risk for CAD.
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http://dx.doi.org/10.1371/journal.pgen.1007755DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6268002PMC
November 2018

Proficiency Testing of Standardized Samples Shows Very High Interlaboratory Agreement for Clinical Next-Generation Sequencing-Based Oncology Assays.

Arch Pathol Lab Med 2019 04 30;143(4):463-471. Epub 2018 Oct 30.

From the Departments of Pathology and Laboratory Medicine & Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill (Dr Merker); the Departments of Pathology (Drs Devereaux and Montgomery, and Mr Smail) and Genetics (Dr Montgomery), Stanford University School of Medicine, and the Biomedical Informatics Program (Mr Smail), Stanford University, Stanford, California; the Department of Pathology, Massachusetts General Hospital (Dr Iafrate), and the Department of Pathology, Brigham and Women's Hospital (Drs Kim and Lindeman), Harvard University, Boston; the Departments of Pathology and Clinical Laboratory Genetics, The University Health Network and the University of Toronto, Toronto, Ontario, Canada (Dr Kamel-Reid); the Department of Pathology, Walter Reed National Military Medical Center, Bethesda, Maryland (Dr Moncur); PierianDx, St Louis, Missouri (Dr Nagarajan); the Department of Global Medical Affairs, Roche, Tucson, Arizona (Dr Portier); the Departments of Hematopathology (Dr Routbort) and Pathology, Genomic Medicine, and Translational Molecular Pathology (Dr Lazar), he University of Texas MD Anderson Cancer Center, Houston (Dr Routbort); the Department of Pathology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia (Dr Surrey); and Proficiency Testing, College of American Pathologists, Northfield, Illinois (Ms Vasalos).

Context.—: Next-generation sequencing-based assays are being increasingly used in the clinical setting for the detection of somatic variants in solid tumors, but limited data are available regarding the interlaboratory performance of these assays.

Objective.—: To examine proficiency testing data from the initial College of American Pathologists (CAP) Next-Generation Sequencing Solid Tumor survey to report on laboratory performance.

Design.—: CAP proficiency testing results from 111 laboratories were analyzed for accuracy and associated assay performance characteristics.

Results.—: The overall accuracy observed for all variants was 98.3%. Rare false-negative results could not be attributed to sequencing platform, selection method, or other assay characteristics. The median and average of the variant allele fractions reported by the laboratories were within 10% of those orthogonally determined by digital polymerase chain reaction for each variant. The median coverage reported at the variant sites ranged from 1922 to 3297.

Conclusions.—: Laboratories demonstrated an overall accuracy of greater than 98% with high specificity when examining 10 clinically relevant somatic single-nucleotide variants with a variant allele fraction of 15% or greater. These initial data suggest excellent performance, but further ongoing studies are needed to evaluate the performance of lower variant allele fractions and additional variant types.
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http://dx.doi.org/10.5858/arpa.2018-0336-CPDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6910717PMC
April 2019

Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci.

Am J Hum Genet 2018 09 23;103(3):377-388. Epub 2018 Aug 23.

Cardiovascular Institute, Stanford School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA. Electronic address:

Coronary artery disease (CAD) is the leading cause of death globally. Genome-wide association studies (GWASs) have identified more than 95 independent loci that influence CAD risk, most of which reside in non-coding regions of the genome. To interpret these loci, we generated transcriptome and whole-genome datasets using human coronary artery smooth muscle cells (HCASMCs) from 52 unrelated donors, as well as epigenomic datasets using ATAC-seq on a subset of 8 donors. Through systematic comparison with publicly available datasets from GTEx and ENCODE projects, we identified transcriptomic, epigenetic, and genetic regulatory mechanisms specific to HCASMCs. We assessed the relevance of HCASMCs to CAD risk using transcriptomic and epigenomic level analyses. By jointly modeling eQTL and GWAS datasets, we identified five genes (SIPA1, TCF21, SMAD3, FES, and PDGFRA) that may modulate CAD risk through HCASMCs, all of which have relevant functional roles in vascular remodeling. Comparison with GTEx data suggests that SIPA1 and PDGFRA influence CAD risk predominantly through HCASMCs, while other annotated genes may have multiple cell and tissue targets. Together, these results provide tissue-specific and mechanistic insights into the regulation of a critical vascular cell type associated with CAD in human populations.
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http://dx.doi.org/10.1016/j.ajhg.2018.08.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128252PMC
September 2018

Large-Scale Phenome-Wide Association Study of Variants Demonstrates Protection Against Ischemic Stroke.

Circ Genom Precis Med 2018 07;11(7):e002162

Stanford Cardiovascular Institute (E.I.)

Background: inhibition is a potent new therapy for hypercholesterolemia and cardiovascular disease. Although short-term clinical trial results have not demonstrated major adverse effects, long-term data will not be available for some time. Genetic studies in large biobanks offer a unique opportunity to predict drug effects and provide context for the evaluation of future clinical trial outcomes.

Methods: We tested the association of the missense variant rs11591147 with predefined phenotypes and phenome-wide, in 337 536 individuals of British ancestry in the UK Biobank, with independent discovery and replication. Using a Bayesian statistical method, we leveraged phenotype correlations to evaluate the phenome-wide impact of inhibition with higher power at a finer resolution.

Results: The T allele of rs11591147 showed a protective effect on hyperlipidemia (odds ratio, 0.63±0.04; =2.32×10), coronary heart disease (odds ratio, 0.73±0.09; =1.05×10), and ischemic stroke (odds ratio, 0.61±0.18; =2.40×10) and was associated with increased type 2 diabetes mellitus risk adjusted for lipid-lowering medication status (odds ratio, 1.24±0.10; =1.98×10). We did not observe associations with cataracts, heart failure, atrial fibrillation, and cognitive dysfunction. Leveraging phenotype correlations, we observed evidence of a protective association with cerebral infarction and vascular occlusion. These results explore the effects of direct inhibition; off-target effects cannot be predicted using this approach.

Conclusions: This result represents the first genetic evidence in a large cohort for the protective effect of inhibition on ischemic stroke and corroborates exploratory evidence from clinical trials. inhibition was not associated with variables other than those related to LDL (low-density lipoprotein) cholesterol, atherosclerosis, and type 2 diabetes mellitus, suggesting that other effects are either small or absent.
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http://dx.doi.org/10.1161/CIRCGEN.118.002162DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050027PMC
July 2018