Publications by authors named "John R Lamb"

21 Publications

  • Page 1 of 1

Serum levels of ACE2 are higher in patients with obesity and diabetes.

Obes Sci Pract 2021 Apr 16;7(2):239-243. Epub 2020 Dec 16.

Icelandic Heart Association Kopavogur Iceland.

Objective: As severity of outcome in COVID-19 is disproportionately higher among individuals with obesity, smokers, patients with hypertension, kidney disease, chronic pulmonary disease, coronary heart disease (CHD), and/or type 2 diabetes (T2D), serum levels of ACE2, the cellular entry point for the coronavirus SARS-CoV-2, were examined in these high-risk groups.

Methods: Associations of ACE2 levels to smokers and patients with hypertension, T2D, obesity, CHD, or COPD were investigated in a single center population-based study of 5457 Icelanders from the Age, Gene/Environment Susceptibility Reykjavík Study (AGES-RS) of the elderly (mean age 75 ± 6 years), using multiple linear regression analysis.

Results: Serum levels of ACE2 were higher in smokers and individuals with T2D and/or obesity while they were unaffected in the other patient groups.

Conclusion: ACE2 levels are higher in some patient groups with comorbidities linked to COVID-19 including obesity and T2D and as such may have an emerging role as a circulating biomarker for severity of outcome in the disease.
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http://dx.doi.org/10.1002/osp4.472DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019273PMC
April 2021

It's in Our Blood: A Glimpse of Personalized Medicine.

Trends Mol Med 2021 01 25;27(1):20-30. Epub 2020 Sep 25.

Icelandic Heart Association, IS-201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland. Electronic address:

Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.
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http://dx.doi.org/10.1016/j.molmed.2020.09.003DOI Listing
January 2021

ACE2 levels are altered in comorbidities linked to severe outcome in COVID-19.

medRxiv 2020 Jun 5. Epub 2020 Jun 5.

Aims: Severity of outcome in COVID-19 is disproportionately higher among the obese, males, smokers, those suffering from hypertension, kidney disease, coronary heart disease (CHD) and/or type 2 diabetes (T2D). We examined if serum levels of ACE2, the cellular entry point for the coronavirus SARS-CoV-2, were altered in these high-risk groups.

Methods: Associations of serum ACE2 levels to hypertension, T2D, obesity, CHD, smokers and males in a single center population-based study of 5457 Icelanders from the Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS) of the elderly (mean age 75+/-6 years).

Results: Smokers, males, and individuals with T2D or obesity have altered serum levels of ACE2 that may influence productive infection of SARS-CoV-2 in these high-risk groups.

Conclusion: ACE2 levels are upregulated in some patient groups with comorbidities linked to COVID-19 and as such may have an emerging role as a circulating biomarker for severity of outcome in COVID-19.
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http://dx.doi.org/10.1101/2020.06.04.20122044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276056PMC
June 2020

Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes.

Diabetes 2020 08 8;69(8):1843-1853. Epub 2020 May 8.

Faculty of Medicine, University of Iceland, Reykjavik, Iceland

The increasing prevalence of type 2 diabetes poses a major challenge to societies worldwide. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach, measuring serum levels of 4,137 proteins in 5,438 elderly Icelanders, and identified 536 proteins associated with prevalent and/or incident type 2 diabetes. We validated a subset of the observed associations in an independent case-control study of type 2 diabetes. These protein associations provide novel biological insights into the molecular mechanisms that are dysregulated prior to and following the onset of type 2 diabetes and can be detected in serum. A bidirectional two-sample Mendelian randomization analysis indicated that serum changes of at least 23 proteins are downstream of the disease or its genetic liability, while 15 proteins were supported as having a causal role in type 2 diabetes.
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http://dx.doi.org/10.2337/db19-1070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372075PMC
August 2020

Tau overexpression exacerbates neuropathology after repeated mild head impacts in male mice.

Neurobiol Dis 2020 02 23;134:104683. Epub 2019 Nov 23.

Department of General Medical Biology, Genomics Institute for the Novartis Research Foundation, San Diego, CA 92121, USA. Electronic address:

Repeated mild traumatic brain injury (rmTBI) can lead to development of chronic traumatic encephalopathy (CTE), which is characterized by progressive neurodegeneration with presence of white matter damage, gliosis and hyper-phosphorylated tau. While animal models of rmTBI have been documented, few characterize the molecular pathogenesis and expression profiles of relevant injured brain regions. Additionally, while the usage of transgenic tau mice in rmTBI is prevalent, the effects of tau on pathological outcomes has not been well studied. Here we characterized a 42-impact closed-head rmTBI paradigm on 3-4 month old male C57BL/6 (WT) and Tau-overexpressing mice (Tau58.4). This injury paradigm resulted in chronic gliosis, T-cell infiltration, and demyelination of the optic nerve and associated white matter tracts at 1-month post-injury. At 3-months post-injury, Tau58.4 mice showed progressive neuroinflammation and neurodegeneration in multiple brain regions compared to WT mice. Corresponding to histopathology, RNAseq of the optic nerve tract at 1-month post-injury showed significant upregulation of inflammatory pathways and downregulation of myelin synthetic pathways in both genotypes. However, Tau58.4 mice showed additional changes in neurite development, protein processing, and cell stress. Comparisons with published transcriptomes of human Alzheimer's Disease and CTE revealed common signatures including neuroinflammation and downregulation of protein phosphatases. We next investigated the demyelination and T-cell infiltration phenotypes to determine whether these offer potential avenues for therapeutic intervention. Tau58.4 mice were treated with the histamine H3 receptor antagonist GSK239512 for 1-month post-injury to promote remyelination of white matter lesions. This restored myelin gene expression to sham levels but failed to repair the histopathologic lesions. Likewise, injured T-cell-deficient Rag2/Il2rg (R2G2) mice also showed evidence for inflammation and loss of myelin. However, unlike immune-competent mice, R2G2 mice had altered myeloid cell gene expression and fewer demyelinated lesions. Together this data shows that rmTBI leads to chronic white matter inflammatory demyelination and axonal loss exacerbated by human tau overexpression but suggests that immune-suppression and remyelination alone are insufficient to reverse damage.
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http://dx.doi.org/10.1016/j.nbd.2019.104683DOI Listing
February 2020

Co-regulatory networks of human serum proteins link genetics to disease.

Science 2018 08 2;361(6404):769-773. Epub 2018 Aug 2.

Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Iceland.

Proteins circulating in the blood are critical for age-related disease processes; however, the serum proteome has remained largely unexplored. To this end, 4137 proteins covering most predicted extracellular proteins were measured in the serum of 5457 Icelanders over 65 years of age. Pairwise correlation between proteins as they varied across individuals revealed 27 different network modules of serum proteins, many of which were associated with cardiovascular and metabolic disease states, as well as overall survival. The protein modules were controlled by cis- and trans-acting genetic variants, which in many cases were also associated with complex disease. This revealed co-regulated groups of circulating proteins that incorporated regulatory control between tissues and demonstrated close relationships to past, current, and future disease states.
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http://dx.doi.org/10.1126/science.aaq1327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190714PMC
August 2018

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.

Mol Syst Biol 2014 Jul 30;10:743. Epub 2014 Jul 30.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017).
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http://dx.doi.org/10.15252/msb.20145304DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299500PMC
July 2014

Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease.

Cell 2013 Apr;153(3):707-20

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

The genetics of complex disease produce alterations in the molecular interactions of cellular pathways whose collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer's disease (LOAD), we constructed gene-regulatory networks in 1,647 postmortem brain tissues from LOAD patients and nondemented subjects, and we demonstrate that LOAD reconfigures specific portions of the molecular interaction structure. Through an integrative network-based approach, we rank-ordered these network structures for relevance to LOAD pathology, highlighting an immune- and microglia-specific module that is dominated by genes involved in pathogen phagocytosis, contains TYROBP as a key regulator, and is upregulated in LOAD. Mouse microglia cells overexpressing intact or truncated TYROBP revealed expression changes that significantly overlapped the human brain TYROBP network. Thus the causal network structure is a useful predictor of response to gene perturbations and presents a framework to test models of disease mechanisms underlying LOAD.
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http://dx.doi.org/10.1016/j.cell.2013.03.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3677161PMC
April 2013

A comprehensive characterization of genome-wide copy number aberrations in colorectal cancer reveals novel oncogenes and patterns of alterations.

PLoS One 2012 31;7(7):e42001. Epub 2012 Jul 31.

Oncology Research, Pfizer Worldwide Research and Development, San Diego, California, United States of America.

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p<0.01). Focal aberrations identified by the GISTIC method confirmed amplifications of oncogenes including EGFR, ERBB2, CCND1, MET, and MYC, and deletions of tumor suppressors including TP53, APC, and SMAD4, and gene expression was highly concordant with copy number aberration for these genes. Novel amplicons included putative oncogenes such as WNK1 and HNF4A, which also showed high concordance between copy number and expression. Survival analysis associated a specific patient segment featured by chromosome 20 q gains to an improved overall survival, which might be due to higher expression of genes such as EEF1B2 and PTK6. The CNA clustering also grouped tumors characterized by a poor prognosis BRAF-mutant-like signature derived from mRNA data from this cohort. We further revealed non-random correlation between CNAs among unlinked loci, including positive correlation between 20 q gain and 8 q gain, and 20 q gain and chromosome 18 loss, consistent with co-selection of these CNAs. These results reinforce the non-random nature of somatic CNAs in stage-II/III CRC and highlight loci and genes that may play an important role in driving the development and outcome of this disease.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042001PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409212PMC
January 2013

Inferring causal genomic alterations in breast cancer using gene expression data.

BMC Syst Biol 2011 Aug 1;5:121. Epub 2011 Aug 1.

Sage Bionetworks, Seattle, WA 98109, USA.

Background: One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies.

Results: We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments.

Conclusions: To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data.
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http://dx.doi.org/10.1186/1752-0509-5-121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162519PMC
August 2011

Predictive genes in adjacent normal tissue are preferentially altered by sCNV during tumorigenesis in liver cancer and may rate limiting.

PLoS One 2011 5;6(7):e20090. Epub 2011 Jul 5.

Rosetta Inpharmatics, LLC, Seattle, Washington, United States of America.

Background: In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear.

Methodology/principal Findings: Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ∼250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU.

Conclusions/significance: This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0020090PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3130029PMC
December 2011

microRNA-122 as a regulator of mitochondrial metabolic gene network in hepatocellular carcinoma.

Mol Syst Biol 2010 Aug;6:402

Rosetta Inpharmatics LLC, a wholly-owned subsidiary of Merck and Co., Inc., Seattle, WA, USA.

Tumorigenesis involves multistep genetic alterations. To elucidate the microRNA (miRNA)-gene interaction network in carcinogenesis, we examined their genome-wide expression profiles in 96 pairs of tumor/non-tumor tissues from hepatocellular carcinoma (HCC). Comprehensive analysis of the coordinate expression of miRNAs and mRNAs reveals that miR-122 is under-expressed in HCC and that increased expression of miR-122 seed-matched genes leads to a loss of mitochondrial metabolic function. Furthermore, the miR-122 secondary targets, which decrease in expression, are good prognostic markers for HCC. Transcriptome profiling data from additional 180 HCC and 40 liver cirrhotic patients in the same cohort were used to confirm the anti-correlation of miR-122 primary and secondary target gene sets. The HCC findings can be recapitulated in mouse liver by silencing miR-122 with antagomir treatment followed by gene-expression microarray analysis. In vitro miR-122 data further provided a direct link between induction of miR-122-controlled genes and impairment of mitochondrial metabolism. In conclusion, miR-122 regulates mitochondrial metabolism and its loss may be detrimental to sustaining critical liver function and contribute to morbidity and mortality of liver cancer patients.
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http://dx.doi.org/10.1038/msb.2010.58DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2950084PMC
August 2010

Complexity in common diseases: big biology for all.

Sci Transl Med 2010 Mar;2(25):25cm11

Oncology Research Unit, Pfizer, San Diego, CA 92121, USA. [email protected] zer.com

The Commentary of Mills and Sykes in Science Translational Medicine presented their thesis on the advent of high-throughput technologies and the dangers they may represent for the future of biomedical research. In response, we argue that true progress on the diagnosis and treatment of common human diseases will require the advent of big biology and its deep integration with focused research as practiced in both academic and industrial institutions.
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http://dx.doi.org/10.1126/scitranslmed.3000882DOI Listing
March 2010

Characterizing dynamic changes in the human blood transcriptional network.

PLoS Comput Biol 2010 Feb 12;6(2):e1000671. Epub 2010 Feb 12.

Department of Genetics, Rosetta Inpharmatics, LLC, a wholly owned subsidiary of Merck & Co., Inc., Seattle, Washington, USA.

Gene expression data generated systematically in a given system over multiple time points provides a source of perturbation that can be leveraged to infer causal relationships among genes explaining network changes. Previously, we showed that food intake has a large impact on blood gene expression patterns and that these responses, either in terms of gene expression level or gene-gene connectivity, are strongly associated with metabolic diseases. In this study, we explored which genes drive the changes of gene expression patterns in response to time and food intake. We applied the Granger causality test and the dynamic Bayesian network to gene expression data generated from blood samples collected at multiple time points during the course of a day. The simulation result shows that combining many short time series together is as powerful to infer Granger causality as using a single long time series. Using the Granger causality test, we identified genes that were supported as the most likely causal candidates for the coordinated temporal changes in the network. These results show that PER1 is a key regulator of the blood transcriptional network, in which multiple biological processes are under circadian rhythm regulation. The fasted and fed dynamic Bayesian networks showed that over 72% of dynamic connections are self links. Finally, we show that different processes such as inflammation and lipid metabolism, which are disconnected in the static network, become dynamically linked in response to food intake, which would suggest that increasing nutritional load leads to coordinate regulation of these biological processes. In conclusion, our results suggest that food intake has a profound impact on the dynamic co-regulation of multiple biological processes, such as metabolism, immune response, apoptosis and circadian rhythm. The results could have broader implications for the design of studies of disease association and drug response in clinical trials.
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http://dx.doi.org/10.1371/journal.pcbi.1000671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2820517PMC
February 2010

The effect of food intake on gene expression in human peripheral blood.

Hum Mol Genet 2010 Jan;19(1):159-69

Rosetta Inpharmatics, LLC, Merck & Co., Inc., Seattle, WA 98109, USA.

Human gene expression traits have been shown to be dependent on gender, age and time of day in blood and other tissues. However, other factors that may impact gene expression have not been systematically explored. For example, in studies linking blood gene expression to obesity related traits, whether the fasted or fed state will be the most informative is an open question. Here, we employed a two-arm cross-over design to perform a genome-wide survey of gene expression in human peripheral blood to address explicitly this type of question. We were able to distinguish expression changes due to individual and time-specific effects from those due to food intake. We demonstrate that the transcriptional response to food intake is robust by constructing a classifier from the gene expression traits with >90% accuracy classifying individuals as being in the fasted or fed state. Gene expression traits that were best able to discriminate the fasted and fed states were more heritable and achieved greater coherence with respect to pathways associated with metabolic traits. The connectivity structure among gene expression traits was explored in the context of coexpression networks. Changes in the connectivity structure were observed between the fasted and fed states. We demonstrate that differential expression and differential connectivity are two complementary ways to characterize changes between fasted and fed states. Both gene sets were significantly enriched for genes associated with obesity related traits. Our results suggest that the pair of fasted/fed blood expression profiles provide more comprehensive information about an individual's metabolic states.
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http://dx.doi.org/10.1093/hmg/ddp476DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2792154PMC
January 2010

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Nat Genet 2009 Apr 8;41(4):415-23. Epub 2009 Mar 8.

Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.
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http://dx.doi.org/10.1038/ng.325DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2837947PMC
April 2009

Genetics of gene expression and its effect on disease.

Nature 2008 Mar 16;452(7186):423-8. Epub 2008 Mar 16.

deCODE genetics, 101 Reykjavik, Iceland.

Common human diseases result from the interplay of many genes and environmental factors. Therefore, a more integrative biology approach is needed to unravel the complexity and causes of such diseases. To elucidate the complexity of common human diseases such as obesity, we have analysed the expression of 23,720 transcripts in large population-based blood and adipose tissue cohorts comprehensively assessed for various phenotypes, including traits related to clinical obesity. In contrast to the blood expression profiles, we observed a marked correlation between gene expression in adipose tissue and obesity-related traits. Genome-wide linkage and association mapping revealed a highly significant genetic component to gene expression traits, including a strong genetic effect of proximal (cis) signals, with 50% of the cis signals overlapping between the two tissues profiled. Here we demonstrate an extensive transcriptional network constructed from the human adipose data that exhibits significant overlap with similar network modules constructed from mouse adipose data. A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.
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http://dx.doi.org/10.1038/nature06758DOI Listing
March 2008

In vivo characterization of the nonessential budding yeast anaphase-promoting complex/cyclosome components Swm1p, Mnd2p and Apc9p.

Genetics 2005 Jul 23;170(3):1045-62. Epub 2005 May 23.

Program in Biochemistry, Cellular, and Molecular Biology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.

We have examined the in vivo requirement of two recently identified nonessential components of the budding yeast anaphase-promoting complex, Swm1p and Mnd2p, as well as that of the previously identified subunit Apc9p. swm1Delta mutants exhibit synthetic lethality or conditional synthetic lethality with other APC/C subunits and regulators, whereas mnd2Delta mutants are less sensitive to perturbation of the APC/C. swm1Delta mutants, but not mnd2Delta mutants, exhibit defects in APC/C substrate turnover, both during the mitotic cell cycle and in alpha-factor-arrested cells. In contrast, apc9Delta mutants exhibit only minor defects in substrate degradation in alpha-factor-arrested cells. In cycling cells, degradation of Clb2p, but not Pds1p or Clb5p, is delayed in apc9Delta. Our findings suggest that Swm1p is required for full catalytic activity of the APC/C, whereas the requirement of Mnd2p for APC/C function appears to be negligible under standard laboratory conditions. Furthermore, the role of Apc9p in APC/C-dependent ubiquitination may be limited to the proteolysis of a select number of substrates.
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http://dx.doi.org/10.1534/genetics.104.040105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1451159PMC
July 2005

Identification of biomarkers for tumor endothelial cell proliferation through gene expression profiling.

Mol Cancer Ther 2005 Mar;4(3):413-25

Merck & Co., Inc., 770 Sumneytown Pike, WP26-462, West Point, PA 19486, USA.

Extensive efforts are under way to identify antiangiogenic therapies for the treatment of human cancers. Many proposed therapeutics target vascular endothelial growth factor (VEGF) or the kinase insert domain receptor (KDR/VEGF receptor-2/FLK-1), the mitogenic VEGF receptor tyrosine kinase expressed by endothelial cells. Inhibition of KDR catalytic activity blocks tumor neoangiogenesis, reduces vascular permeability, and, in animal models, inhibits tumor growth and metastasis. Using a gene expression profiling strategy in rat tumor models, we identified a set of six genes that are selectively overexpressed in tumor endothelial cells relative to tumor cells and whose pattern of expression correlates with the rate of tumor endothelial cell proliferation. In addition to being potential targets for antiangiogenesis tumor therapy, the expression patterns of these genes or their protein products may aid the development of pharmacodynamic assays for small molecule inhibitors of the KDR kinase in human tumors.
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http://dx.doi.org/10.1158/1535-7163.MCT-04-0209DOI Listing
March 2005

Genetics of gene expression surveyed in maize, mouse and man.

Nature 2003 Mar;422(6929):297-302

Rosetta Inpharmatics, LLC, 12040 115th Avenue N.E., Kirkland, Washington 98034, USA.

Treating messenger RNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been pursued in gene-specific ways. Transcript abundances often serve as a surrogate for classical quantitative traits in that the levels of expression are significantly correlated with the classical traits across members of a segregating population. The correlation structure between transcript abundances and classical traits has been used to identify susceptibility loci for complex diseases such as diabetes and allergic asthma. One study recently completed the first comprehensive dissection of transcriptional regulation in budding yeast, giving a detailed glimpse of a genome-wide survey of the genetics of gene expression. Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at cellular biochemical processes. Here we describe comprehensive genetic screens of mouse, plant and human transcriptomes by considering gene expression values as quantitative traits. We identify a gene expression pattern strongly associated with obesity in a murine cross, and observe two distinct obesity subtypes. Furthermore, we find that these obesity subtypes are under the control of different loci.
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http://dx.doi.org/10.1038/nature01434DOI Listing
March 2003

Cell-based assays for identification of novel double-strand break-inducing agents.

J Natl Cancer Inst 2002 Jan;94(2):88-94

Program in Molecular Pharmacology, Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Background: We are developing cell-based assays to identify anticancer agents that are selectively toxic to cells with defined mutations. As a test, we used a three-stage strategy to screen compounds from the National Cancer Institute's repository for agents that are selectively toxic to double-strand break repair-deficient yeast cells.

Methods: Compounds identified in the screen were further analyzed by use of yeast and vertebrate cell-based and in vitroassays to distinguish between topoisomerase I and II poisons.

Results: Of the more than 85 000 compounds screened, 126 were selectively toxic to yeast deficient in DNA double-strand break repair. Eighty-seven of these 126 compounds were structurally related to known topoisomerase poisons, and 39 were not. Twenty-eight of the 39 were characterized, and we present data for eight of the compounds. Among these eight compounds, we identified two novel topoisomerase II poisons (NSC 327929 and NSC 638432) that were equipotent to etoposide in biochemical tests and in cells, five (NSC 63599, NSC 65601, NSC 380271, NSC 651646, and NSC 668370) with topoisomerase I-dependent toxicity in yeast that induced DNA damage and toxicity in mammalian cells, and one (NSC 610898) that directly bound to DNA and induced strand breaks.

Conclusions: Cell-based assays can be used to identify molecules that are selectively toxic to cells with a predetermined genetic background, including mutations in genes involved in the cell cycle and its checkpoints, for which there are currently no selectively toxic compounds.
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http://dx.doi.org/10.1093/jnci/94.2.88DOI Listing
January 2002
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