Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

Anoop T. Ambikan; Hong Yang; Shuba Krishnan; Sara Svensson Akusjärvi; Soham Gupta; Magda Lourda; Maike Sperk; Muhammad Arif; Cheng Zhang; Hampus Nordqvist; Sivasankaran Munusamy Ponnan; Anders Sönnerborg; Carl Johan Treutiger; Liam O'Mahony; Adil Mardinoglu; Rui Benfeitas; Ujjwal Neogi

doi:10.1016/j.cels.2022.06.006

Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

Anoop T. Ambikan, Hong Yang, Shuba Krishnan, Sara Svensson Akusjärvi, Soham Gupta, Magda Lourda, Maike Sperk, Muhammad Arif, Cheng Zhang, Hampus Nordqvist, Sivasankaran Munusamy Ponnan, Anders Sönnerborg, Carl Johan Treutiger, Liam O'Mahony, Adil Mardinoglu, Rui Benfeitas, Ujjwal Neogi^*

^*Corresponding author for this work

Centre for Host Microbiome Interactions

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.

Original language	English
Pages (from-to)	665-681.e4
Journal	Cell Systems
Volume	13
Issue number	8
DOIs	https://doi.org/10.1016/j.cels.2022.06.006
Publication status	Published - 17 Aug 2022

Keywords

COVID-19
personalized genome-scale metabolic model
similarity network fusion

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10.1016/j.cels.2022.06.006

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Ambikan, A. T., Yang, H., Krishnan, S., Svensson Akusjärvi, S., Gupta, S., Lourda, M., Sperk, M., Arif, M., Zhang, C., Nordqvist, H., Ponnan, S. M., Sönnerborg, A., Treutiger, C. J., O'Mahony, L., Mardinoglu, A., Benfeitas, R., & Neogi, U. (2022). Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity. Cell Systems, 13(8), 665-681.e4. https://doi.org/10.1016/j.cels.2022.06.006

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title = "Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity",

abstract = "The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.",

keywords = "COVID-19, personalized genome-scale metabolic model, similarity network fusion",

author = "Ambikan, {Anoop T.} and Hong Yang and Shuba Krishnan and {Svensson Akusj{\"a}rvi}, Sara and Soham Gupta and Magda Lourda and Maike Sperk and Muhammad Arif and Cheng Zhang and Hampus Nordqvist and Ponnan, {Sivasankaran Munusamy} and Anders S{\"o}nnerborg and Treutiger, {Carl Johan} and Liam O'Mahony and Adil Mardinoglu and Rui Benfeitas and Ujjwal Neogi",

note = "Funding Information: The authors would like to thank Elisabet Storg{\"a}rd and Ronnie Ask, Study Nurses, S{\"o}dersjukhuset for their excellent support with patient recruitment and all the clinicians and nurses who are the frontline warriors fighting against COVID-19. The authors acknowledge support from the National Genomics Infrastructure in Genomics Production Stockholm, funded by Science for Life Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We are thankful to the Swedish Metabolomics Centre, Ume{\aa}, Sweden, for measuring TCA-cycle intermediates by GC-QQQ-MS and providing the methodology. The study is funded by the Swedish Research Council grants 2021-00993 (U.N.), 2017-01330 (U.N.), 2018-06156 (U.N.), and 2021-03035 (S.G.) and received support from Karolinska Institutet Stiftelser och Fonder grant 2020-01554 (U.N.) and 2020-02153 (S.G.), The Center for Medical Innovation grant CIMED-FoUI-093304 (S.G.), and {\AA}ke Wiberg Stiftelse grant M20-0220 (S.G.). Conceptualization, U.N. and R.B.; methodology, A.T.A. H.Y. S.K. S.S.A. M.S. M.A. C.Z. S.M.P. A.M. R.B. and U.N.; investigation, clinical, H.N. C.J.T. and A.S.; investigation, computational and laboratory, A.T.A. H.Y. S.K. S.S.A. S.G. M.S. M.L. M.A. C.Z. A.M. R.B. and U.N.; visualization, A.T.A. H.Y. S.K. S.S.A. M.L. R.B. and U.N.; funding acquisition, S.G. and U.N.; project administration, C.J.T. A.M. R.B. and U.N.; supervision, C.J.T. A.M. R.B. and U.N.; writing—original draft, A.T.A. H.Y. S.K. S.S.A. S.G. and U.N.; writing—review & editing, M.L. M.S. M.A. C.Z. H.N. S.M.P. A.S. C.J.T. L.O.M. A.M. and R.B. The authors declare no competing interests. Funding Information: The authors would like to thank Elisabet Storg{\"a}rd and Ronnie Ask, Study Nurses, S{\"o}dersjukhuset for their excellent support with patient recruitment and all the clinicians and nurses who are the frontline warriors fighting against COVID-19. The authors acknowledge support from the National Genomics Infrastructure in Genomics Production Stockholm, funded by Science for Life Laboratory , the Knut and Alice Wallenberg Foundation and the Swedish Research Council , and SNIC / Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We are thankful to the Swedish Metabolomics Centre, Ume{\aa}, Sweden, for measuring TCA-cycle intermediates by GC-QQQ-MS and providing the methodology. The study is funded by the Swedish Research Council grants 2021-00993 (U.N.), 2017-01330 (U.N.), 2018-06156 (U.N.), and 2021-03035 (S.G.) and received support from Karolinska Institutet Stiftelser och Fonder grant 2020-01554 (U.N.) and 2020-02153 (S.G.), The Center for Medical Innovation grant CIMED-FoUI-093304 (S.G.), and {\AA}ke Wiberg Stiftelse grant M20-0220 (S.G.). Publisher Copyright: {\textcopyright} 2022 The Authors",

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doi = "10.1016/j.cels.2022.06.006",

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Ambikan, AT, Yang, H, Krishnan, S, Svensson Akusjärvi, S, Gupta, S, Lourda, M, Sperk, M, Arif, M, Zhang, C, Nordqvist, H, Ponnan, SM, Sönnerborg, A, Treutiger, CJ, O'Mahony, L, Mardinoglu, A, Benfeitas, R & Neogi, U 2022, 'Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity', Cell Systems, vol. 13, no. 8, pp. 665-681.e4. https://doi.org/10.1016/j.cels.2022.06.006

TY - JOUR

T1 - Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

AU - Ambikan, Anoop T.

AU - Yang, Hong

AU - Krishnan, Shuba

AU - Svensson Akusjärvi, Sara

AU - Gupta, Soham

AU - Lourda, Magda

AU - Sperk, Maike

AU - Arif, Muhammad

AU - Zhang, Cheng

AU - Nordqvist, Hampus

AU - Ponnan, Sivasankaran Munusamy

AU - Sönnerborg, Anders

AU - Treutiger, Carl Johan

AU - O'Mahony, Liam

AU - Mardinoglu, Adil

AU - Benfeitas, Rui

AU - Neogi, Ujjwal

N1 - Funding Information: The authors would like to thank Elisabet Storgärd and Ronnie Ask, Study Nurses, Södersjukhuset for their excellent support with patient recruitment and all the clinicians and nurses who are the frontline warriors fighting against COVID-19. The authors acknowledge support from the National Genomics Infrastructure in Genomics Production Stockholm, funded by Science for Life Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We are thankful to the Swedish Metabolomics Centre, Umeå, Sweden, for measuring TCA-cycle intermediates by GC-QQQ-MS and providing the methodology. The study is funded by the Swedish Research Council grants 2021-00993 (U.N.), 2017-01330 (U.N.), 2018-06156 (U.N.), and 2021-03035 (S.G.) and received support from Karolinska Institutet Stiftelser och Fonder grant 2020-01554 (U.N.) and 2020-02153 (S.G.), The Center for Medical Innovation grant CIMED-FoUI-093304 (S.G.), and Åke Wiberg Stiftelse grant M20-0220 (S.G.). Conceptualization, U.N. and R.B.; methodology, A.T.A. H.Y. S.K. S.S.A. M.S. M.A. C.Z. S.M.P. A.M. R.B. and U.N.; investigation, clinical, H.N. C.J.T. and A.S.; investigation, computational and laboratory, A.T.A. H.Y. S.K. S.S.A. S.G. M.S. M.L. M.A. C.Z. A.M. R.B. and U.N.; visualization, A.T.A. H.Y. S.K. S.S.A. M.L. R.B. and U.N.; funding acquisition, S.G. and U.N.; project administration, C.J.T. A.M. R.B. and U.N.; supervision, C.J.T. A.M. R.B. and U.N.; writing—original draft, A.T.A. H.Y. S.K. S.S.A. S.G. and U.N.; writing—review & editing, M.L. M.S. M.A. C.Z. H.N. S.M.P. A.S. C.J.T. L.O.M. A.M. and R.B. The authors declare no competing interests. Funding Information: The authors would like to thank Elisabet Storgärd and Ronnie Ask, Study Nurses, Södersjukhuset for their excellent support with patient recruitment and all the clinicians and nurses who are the frontline warriors fighting against COVID-19. The authors acknowledge support from the National Genomics Infrastructure in Genomics Production Stockholm, funded by Science for Life Laboratory , the Knut and Alice Wallenberg Foundation and the Swedish Research Council , and SNIC / Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We are thankful to the Swedish Metabolomics Centre, Umeå, Sweden, for measuring TCA-cycle intermediates by GC-QQQ-MS and providing the methodology. The study is funded by the Swedish Research Council grants 2021-00993 (U.N.), 2017-01330 (U.N.), 2018-06156 (U.N.), and 2021-03035 (S.G.) and received support from Karolinska Institutet Stiftelser och Fonder grant 2020-01554 (U.N.) and 2020-02153 (S.G.), The Center for Medical Innovation grant CIMED-FoUI-093304 (S.G.), and Åke Wiberg Stiftelse grant M20-0220 (S.G.). Publisher Copyright: © 2022 The Authors

PY - 2022/8/17

Y1 - 2022/8/17

N2 - The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.

AB - The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.

KW - COVID-19

KW - personalized genome-scale metabolic model

KW - similarity network fusion

UR - http://www.scopus.com/inward/record.url?scp=85135506746&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2022.06.006

DO - 10.1016/j.cels.2022.06.006

M3 - Article

AN - SCOPUS:85135506746

SN - 2405-4712

VL - 13

SP - 665-681.e4

JO - Cell Systems

JF - Cell Systems

IS - 8

ER -

Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

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Keywords

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