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

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.

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

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.

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

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).

Genetics of gene expression and its effect on disease.

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.

Proteomic prediction of incident heart failure and its main subtypes.

AIM: To examine the ability of serum proteins in predicting future heart failure (HF) events, including HF with reduced or preserved ejection fraction (HFrEF or HFpEF), in relation to event time, and with or without considering established HF-associated clinical variables. METHODS AND RESULTS: In the prospective population-based Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS), 440 individuals developed HF after their first visit with a median follow-up of 5.45 years. Among them, 167 were diagnosed with HFrEF and 188 with HFpEF. A least absolute shrinkage and selection operator regression model with non-parametric bootstrap were used to select predictors from an analysis of 4782 serum proteins, and several pre-established clinical parameters linked to HF. A subset of 8-10 distinct or overlapping serum proteins predicted different future HF outcomes, and C-statistics were used to assess discrimination, revealing proteins combined with a C-index of 0.80 for all incident HF, 0.78 and 0.80 for incident HFpEF or HFrEF, respectively. In the AGES-RS, protein panels alone encompassed the risk contained in the clinical information and improved the performance characteristics of prediction models based on N-terminal pro-B-type natriuretic peptide and clinical risk factors. Finally, the protein predictors performed particularly well close to the time of an HF event, an outcome that was replicated in the Cardiovascular Health Study. CONCLUSION: A small number of circulating proteins accurately predicted future HF in the AGES-RS cohort of older adults, and they alone encompass the risk information found in a collection of clinical data. Incident HF events were predicted up to 8 years, with predictor performance significantly improving for events occurring less than 1 year ahead, a finding replicated in an external cohort study.

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

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.

A genome-wide association study of serum proteins reveals shared loci with common diseases.

With the growing number of genetic association studies, the genotype-phenotype atlas has become increasingly more complex, yet the functional consequences of most disease associated alleles is not understood. The measurement of protein level variation in solid tissues and biofluids integrated with genetic variants offers a path to deeper functional insights. Here we present a large-scale proteogenomic study in 5,368 individuals, revealing 4,035 independent associations between genetic variants and 2,091 serum proteins, of which 36% are previously unreported. The majority of both cis- and trans-acting genetic signals are unique for a single protein, although our results also highlight numerous highly pleiotropic genetic effects on protein levels and demonstrate that a protein's genetic association profile reflects certain characteristics of the protein, including its location in protein networks, tissue specificity and intolerance to loss of function mutations. Integrating protein measurements with deep phenotyping of the cohort, we observe substantial enrichment of phenotype associations for serum proteins regulated by established GWAS loci, and offer new insights into the interplay between genetics, serum protein levels and complex disease.

Coding and regulatory variants are associated with serum protein levels and disease.

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.

A proteogenomic signature of age-related macular degeneration in blood.

Age-related macular degeneration (AMD) is one of the most common causes of visual impairment in the elderly, with a complex and still poorly understood etiology. Whole-genome association studies have discovered 34 genomic regions associated with AMD. However, the genes and cognate proteins that mediate the risk, are largely unknown. In the current study, we integrate levels of 4782 human serum proteins with all genetic risk loci for AMD in a large population-based study of the elderly, revealing many proteins and pathways linked to the disease. Serum proteins are also found to reflect AMD severity independent of genetics and predict progression from early to advanced AMD after five years in this population. A two-sample Mendelian randomization study identifies several proteins that are causally related to the disease and are directionally consistent with the observational estimates. In this work, we present a robust and unique framework for elucidating the pathobiology of AMD.

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

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.

Characterizing dynamic changes in the human blood transcriptional network.

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.

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

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.

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

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.

Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes.

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.