Justin Cope - Academia.edu (original) (raw)

Papers by Justin Cope

medRxiv (Cold Spring Harbor Laboratory), May 31, 2024

Research Square (Research Square), Jun 4, 2021

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing-the use of an already existing drug for a new indication-could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we matched critically ill COVID-19 cases with healthy controls and screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index. Significant differences in traits that have been associated with critically ill COVID-19 status in prior literature, such as alanine aminotransferase, body mass index, C-reactive protein, and neutrophil cell count, were further investigated. In-depth statistical analysis of COVID-19 associated traits and their genetics using regression modeling and propensity score stratification identified cyclin-dependent kinase 6 (CDK6) as a more promising drug target for the selective treatment of critically ill COVID-19 patients than the previously reported interleukin 6. Four existing CDK6 inhibitors-abemaciclib, ribociclib, trilaciclib, and palbociclib-have been approved for the treatment of breast cancer. Clinical evidence for CDK6 inhibitors in treating critically ill COVID-19 patients has been reported. Further clinical investigations are ongoing.

medRxiv (Cold Spring Harbor Laboratory), May 20, 2021

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by pee... more doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

medRxiv (Cold Spring Harbor Laboratory), Jul 23, 2021

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the stat... more Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the state of the art in the prediction of susceptibility to complex traits or diseases, yet their predictive performance is limited for various reasons, not least of which is their failure to incorporate the effects of gene-gene interactions. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson's Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson's disease. For instance, the model revealed an interaction of previously described drug target candidate genes TMEM175 and GAPDHP25. These results demonstrate that interaction-based machine learning models can improve genetic prediction models and might provide an answer to the missing heritability problem.

Research Square (Research Square), Mar 23, 2022

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing-the use of an already existing drug for a new indication-could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mild or no symptoms after SARS-CoV-2 infection. Using data from the UK Biobank, we describe a workflow to find evidence for high neutrophil cell count and high concentrations of blood triglycerides as predictors of the immune overreaction in critical illness due to COVID-19. Based on these findings, we identified the enzyme CDK6 as a potential drug target to prevent in high risk individuals with high neutrophil cell count the immune overreaction in critical illness due to COVID-19. Three existing CDK4/6 inhibitors-abemaciclib, ribociclib, and palbociclib-have been approved for the treatment of breast cancer. Clinical evidence for CDK4/6 inhibitors in treating critically ill COVID-19 patients has been reported. Further clinical investigations are ongoing.

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing -- the use of an already existing drug for a new indication -- could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mild or no symptoms after SARS-CoV-2 infection. Using data from the UK Biobank, we describe a workflow to find evidence for high neutrophil cell count and high concentrations of blood triglycerides as predictors of the immune overreaction in c...

BackgroundDespite recent development of vaccines and monoclonal antibodies to prevent SARS-CoV-2 ... more BackgroundDespite recent development of vaccines and monoclonal antibodies to prevent SARS-CoV-2 infection, treatment of critically ill COVID-19 patients remains an important goal. In principle, genome-wide association studies (GWAS) could shortcut the clinical evidence needed to repurpose drugs - the use of an existing drug for a new indication. However, it has been shown that the genes found in GWA studies usually do not encode an established drug target and the causal role for disease, a key requirement for drug efficacy, is unclear. We report here an alternative method for finding and testing causal target candidates for drug repurposing.MethodsRather than focusing on the genetics of the disease, we looked for disease-causing traits by searching for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mil...

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing – the use of an already existing drug for a new indication – could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we matched critically ill COVID-19 cases with healthy controls and screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index. Significant differences in traits that have been associated with critically ill COVID-19 status in prior literature, such as alanine aminotransferase, body mass index, C-reactive protein, and neutrophil cell count, were further investigated. In-depth statistical analysis of COVID-19 associated traits and their genet...

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are state of... more Polygenic risk scores (PRS) aggregating results from genome-wide association studies are state of the art to predict the susceptibility to complex traits or diseases. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson’s Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI = [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI = [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson’s Disease. For instance, the model...

Anscombe (1964) presents influential arguments that 'before' and 'after' cannot denote converse r... more Anscombe (1964) presents influential arguments that 'before' and 'after' cannot denote converse relations, despite intuitions to the contrary. These arguments, I claim, rely on ambiguity of certain 'before'- and 'after'-sentences, ambiguity that arises from the interaction of tense and aspect with the temporal ordering relations denoted by 'before' and 'after'. To account for this ambiguity, I adopt a Discourse Representation Theory-based analysis of tense and aspect (Kamp & Reyle 2011) and apply it to a set of examples that exhibit the variety of readings available for 'before'- and 'after'-sentences. I argue that certain readings of stative 'after'-sentences support the existence of an inceptive coercion operator, equivalent in effect to the aspectual verb 'begin'. This operator has much in common with 'earliest', an operator proposed by Beaver & Condoravdi (2003), but it is motivated by independent aspectual considerations. I conclude with a discussion of areas for future research.

L'interface langage-cognition: Actes du 19e Congrès International des Linguistes, 2013

medRxiv (Cold Spring Harbor Laboratory), May 31, 2024

Research Square (Research Square), Jun 4, 2021

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing-the use of an already existing drug for a new indication-could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we matched critically ill COVID-19 cases with healthy controls and screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index. Significant differences in traits that have been associated with critically ill COVID-19 status in prior literature, such as alanine aminotransferase, body mass index, C-reactive protein, and neutrophil cell count, were further investigated. In-depth statistical analysis of COVID-19 associated traits and their genetics using regression modeling and propensity score stratification identified cyclin-dependent kinase 6 (CDK6) as a more promising drug target for the selective treatment of critically ill COVID-19 patients than the previously reported interleukin 6. Four existing CDK6 inhibitors-abemaciclib, ribociclib, trilaciclib, and palbociclib-have been approved for the treatment of breast cancer. Clinical evidence for CDK6 inhibitors in treating critically ill COVID-19 patients has been reported. Further clinical investigations are ongoing.

medRxiv (Cold Spring Harbor Laboratory), May 20, 2021

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by pee... more doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

medRxiv (Cold Spring Harbor Laboratory), Jul 23, 2021

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the stat... more Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the state of the art in the prediction of susceptibility to complex traits or diseases, yet their predictive performance is limited for various reasons, not least of which is their failure to incorporate the effects of gene-gene interactions. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson's Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson's disease. For instance, the model revealed an interaction of previously described drug target candidate genes TMEM175 and GAPDHP25. These results demonstrate that interaction-based machine learning models can improve genetic prediction models and might provide an answer to the missing heritability problem.

Research Square (Research Square), Mar 23, 2022

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing-the use of an already existing drug for a new indication-could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mild or no symptoms after SARS-CoV-2 infection. Using data from the UK Biobank, we describe a workflow to find evidence for high neutrophil cell count and high concentrations of blood triglycerides as predictors of the immune overreaction in critical illness due to COVID-19. Based on these findings, we identified the enzyme CDK6 as a potential drug target to prevent in high risk individuals with high neutrophil cell count the immune overreaction in critical illness due to COVID-19. Three existing CDK4/6 inhibitors-abemaciclib, ribociclib, and palbociclib-have been approved for the treatment of breast cancer. Clinical evidence for CDK4/6 inhibitors in treating critically ill COVID-19 patients has been reported. Further clinical investigations are ongoing.

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing -- the use of an already existing drug for a new indication -- could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mild or no symptoms after SARS-CoV-2 infection. Using data from the UK Biobank, we describe a workflow to find evidence for high neutrophil cell count and high concentrations of blood triglycerides as predictors of the immune overreaction in c...

BackgroundDespite recent development of vaccines and monoclonal antibodies to prevent SARS-CoV-2 ... more BackgroundDespite recent development of vaccines and monoclonal antibodies to prevent SARS-CoV-2 infection, treatment of critically ill COVID-19 patients remains an important goal. In principle, genome-wide association studies (GWAS) could shortcut the clinical evidence needed to repurpose drugs - the use of an existing drug for a new indication. However, it has been shown that the genes found in GWA studies usually do not encode an established drug target and the causal role for disease, a key requirement for drug efficacy, is unclear. We report here an alternative method for finding and testing causal target candidates for drug repurposing.MethodsRather than focusing on the genetics of the disease, we looked for disease-causing traits by searching for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mil...

Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infect... more Despite the recent development of vaccines and monoclonal antibodies preventing SARS-CoV-2 infection, treating critically ill COVID-19 patients still remains a top goal. In principle, drug repurposing – the use of an already existing drug for a new indication – could provide a shortcut to a treatment. However, drug repurposing is often very speculative due to lack of clinical evidence. We report here on a methodology to find and test drug target candidates for drug repurposing. Using UK Biobank data, we matched critically ill COVID-19 cases with healthy controls and screened for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index. Significant differences in traits that have been associated with critically ill COVID-19 status in prior literature, such as alanine aminotransferase, body mass index, C-reactive protein, and neutrophil cell count, were further investigated. In-depth statistical analysis of COVID-19 associated traits and their genet...

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are state of... more Polygenic risk scores (PRS) aggregating results from genome-wide association studies are state of the art to predict the susceptibility to complex traits or diseases. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson’s Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI = [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI = [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson’s Disease. For instance, the model...

Anscombe (1964) presents influential arguments that 'before' and 'after' cannot denote converse r... more Anscombe (1964) presents influential arguments that 'before' and 'after' cannot denote converse relations, despite intuitions to the contrary. These arguments, I claim, rely on ambiguity of certain 'before'- and 'after'-sentences, ambiguity that arises from the interaction of tense and aspect with the temporal ordering relations denoted by 'before' and 'after'. To account for this ambiguity, I adopt a Discourse Representation Theory-based analysis of tense and aspect (Kamp & Reyle 2011) and apply it to a set of examples that exhibit the variety of readings available for 'before'- and 'after'-sentences. I argue that certain readings of stative 'after'-sentences support the existence of an inceptive coercion operator, equivalent in effect to the aspectual verb 'begin'. This operator has much in common with 'earliest', an operator proposed by Beaver & Condoravdi (2003), but it is motivated by independent aspectual considerations. I conclude with a discussion of areas for future research.

L'interface langage-cognition: Actes du 19e Congrès International des Linguistes, 2013