Proteinarium: Multi-sample protein-protein interaction analysis and visualization tool

Armanious, David; Schuster, Jessica; Tollefson, George A.; Agudelo, Anthony; DeWan, Andrew T.; Istrail, Sorin; Padbury, Jamés F.; Uzun, Alper

doi:10.1016/j.ygeno.2020.07.028

Cited by 14 publications

(24 citation statements)

References 27 publications

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“…We compared them to term controls with no family history of preeclampsia. Then, we used Proteinarium , a multi-sample, PPI analysis and visualization tool, to identify clusters of patients with shared protein-protein interaction networks [35]. Using seed genes from each patient, Proteinarium mapped the input genes onto the PPI interactome based on STRING database to build individual networks.…”

Section: Discussionmentioning

confidence: 99%

“…We hypothesize that the genetic architecture underlying complex disorders is best explained by subsets of patients with variants in shared networks and pathways sufficient to express the phenotype. For that purpose, we analyzed our whole exome sequencing data using Proteinarium , a multisample PPI analysis and visualization tool [35]. The top 60 genes, corresponding to the most significant, differentially abundant variants between cases and controls for each patient (ranked by genotype testing p value) were used as the seed genes for input into Proteinarium.…”

Section: Methodsmentioning

confidence: 99%

“…The greater the score, the more dissimilar the networks. We computed the separation score between the networks of significant clusters identified by Proteinarium [35].…”

Section: Methodsmentioning

confidence: 99%

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Integrated Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia

Schuster

Tollefson

Zarate

et al. 2020

Preprint

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To identify clusters of patients with shared networks of genes associated with early onset severe preeclampsia from whole exome sequencing data through novel bioinformatic analysis.We performed a case-control study using whole exome sequencing (WES) on early onset preeclamptic mothers with severe features delivering < 34 weeks and mothers who delivered ≥ 37 weeks. Genotype testing identified variants that were differentially abundant between cases and controls. A Protein-Protein interaction (PPI) analysis and visualization tool, Proteinarium, was implemented to identify clusters of patients with shared networks associated with severe preeclampsia.A total of 61 early onset preeclamptic women with severe features and 82 race and ethnicity matched control women at term were sequenced. We identified 8,867 predicted deleterious variants. 21 of these variants were nominally associated with preeclampsia by genotype testing. Using Proteinarium129 out of the 143 sequenced patients were assigned to statistically significant clusters, Cluster A and B (p< 0.0001). Case dominated Cluster A contained 47 of the 61 case subjects. There were 13 unique genes in the PPI network of Cluster A compared to control dominated Cluster B. Amongst these unique genes, LAMB2, PTK2, RAC1, QSOX1, FN1, and VCAM1 have known associations with the pathogenic mechanisms of preeclampsia.Our network analysis identified genes that were unique to a large cluster of patients with shared networks that provide insights for severe preeclampsia. We also identified genes imputed from the interactome that may otherwise have not been identified by conventional analysis. Strict phenotyping of both cases and controls improved the likelihood of identifying these otherwise difficult to find genetic associations. These uniquely identified genes and their associated variants are potential candidates for developing polygenic risk scores for severe preeclampsia. These results support our hypothesis on the genetic architecture of complex diseases and are generalizable to other phenotypes.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Integrated Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia

Schuster

Tollefson

Zarate

et al. 2020

Preprint

Self Cite

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“…We compared them to term controls with no family history of preterm birth. We used Proteinarium , a multi-sample, protein-protein interaction tool, to identify clusters of patients with shared protein-protein interaction networks associated with preterm birth(13). Using seed genes from each patient, Proteinarium mapped the input genes onto the STRING PPI interactome to build individual networks.…”

Section: Discussionmentioning

confidence: 99%

“…We compared variants identified in women with 2–3 generations of preterm birth with term controls without history of preterm birth. We then used Proteinarium , a multi-sample, protein-protein interaction analysis (PPI) tool, to identify clusters of patients with shared PPI networks associated with preterm birth(13).…”

Section: Introductionmentioning

confidence: 99%

Protein Interaction Networks Define the Genetic Architecture of Preterm Birth

Uzun

Schuster

Stabila

et al. 2020

Preprint

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Rather than pathogenic variants in single genes, the likely genetic architecture of complex diseases is that subgroups of patients share variants in genes in specific networks and pathways sufficient to give rise to a shared phenotype. We combined high throughput sequencing with advanced bioinformatic approaches to identify subgroups of patients with shared networks and pathways associated with preterm birth (PTB). We previously identified genes, gene sets and haplotype blocks that were highly associated with preterm birth. We performed targeted sequencing on these genes and genomic regions on highly phenotyped patients with 2 or 3 generations of preterm birth, and term controls with no family history of preterm birth. We performed a genotype test for differential abundance of variants between cases and controls. We used the genotype association statistics for ranking purposes in order to analyze the data using a multi-sample, protein-protein interaction (PPI) tool to identify significant clusters of patients associated with preterm birth. We identified shared interaction networks of proteins among 45 preterm cases in two statistically significant clusters, p<0.001. We also found two small control-dominated clusters. For replication, we compared our data to an independent, large birth cohort. Sequence data on 60 cases and 321 controls identified 34 preterm cases with shared networks of proteins distributed in two significant clusters. Analysis of the layered PPI networks of these clusters showed significant similarity scores between the clusters from the two independent cohorts of patients. Canonical pathway analysis of the unique genes defining these clusters demonstrated enrichment in inflammatory signaling pathways, the glucocorticoid receptor, the insulin receptor, EGF and B-cell signaling, These results provide insights into the genetics of PTB and support a genetic architecture defined by subgroups of patients that share variants in genes in specific networks and pathways which are sufficient to give rise to the disease phenotype.

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Evaluating urban indoor and outdoor PM10-bound organochlorine pesticides. Air quality status and health impact

Galán-Madruga¹,

Cárdenas-Escudero

Broomandi

et al. 2023

Building and Environment

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Proteinarium: Multi-sample protein-protein interaction analysis and visualization tool

Cited by 14 publications

References 27 publications

Integrated Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia

Integrated Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia

Protein Interaction Networks Define the Genetic Architecture of Preterm Birth

Evaluating urban indoor and outdoor PM10-bound organochlorine pesticides. Air quality status and health impact

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