An integrative systems biology study to understand immune aging in people living with HIV
Author: Mikaeloff, Flora
Date: 2023-06-02
Location: Alfred Nobels allé 8, lecture hall 4Y, Karolinska Institutet, Flemingsberg
Time: 10.00
Department: Inst för laboratoriemedicin / Dept of Laboratory Medicine
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Thesis (5.491Mb)
Abstract
Antiretroviral therapy (ART) reduces viral replication, restores T helper cells and improves
the survival of people living with HIV (PWH), transforming a life-threatening disease into a
manageable chronic infection. Nevertheless, PWH under ART shows aging-related
diseases such as bone abnormalities, non-HIV-associated cancers, and cardiovascular
and neurocognitive diseases. The complex immune metabolic dysregulation leading to
these comorbidities is called immune aging. The main question raised by my thesis was,
what are the complex mechanisms responsible for immune aging in HIV? Using advanced
system biology and machine learning tools, I used multi-omics-based patient
stratification to identify biologic perturbations associated with immune aging in PWH.
First, we investigated PWH with Metabolic Syndrome (MetS), a relatively common agingrelated disease in HIV-1. In paper I, we identified the dysregulation of glutamate metabolism in PWH with MetS using plasma metabolomics and measure of cell transporters by flow cytrometry. Then, we investigated the mechanisms of differing PWH on long-term successful ART from HIV-negative controls (HC). In paper II, we identified the dysregulation of amino acids and, more specifically, glutaminolysis (i.e., lysis of glutamine to glutamate) in PWH compared to HC using metabolomics in two independent cohorts to avoid the potential cohort biases. We identified five neurosteroids to be lower in PWH and potentially create neurological impairments in PWH. The glutaminolysis inhibition in chronically infected HIV-1 promonocytic (U1) cells induced apoptosis and latency reversal which could clear HIV reservoirs.
The first two papers universally clarified our knowledge about dysregulated metabolic traits following a prolonged ART in PWH. However, we observed heterogeneity among the clinically defined PWH. Therefore, we focused more on the multi-omics data-driven approaches to stratify the at-risk group who were either dysregulated metabolically atrisk PWH (paper III) or immunometabolic at-risk group (paper IV) and clarified the biological aging process by measuring transcriptomics age (paper V).
In paper III, we found three groups of PWH based on multi-omics integration of lipidomics, metabolomics, and microbiome. The severe at-risk metabolic complications showed increased weight-related comorbidities and di- and triglycerides compared to the other clusters. At-risk and HC-like groups displayed similar metabolic profiles but were different from HC. An increase in Prevotella was linked to the overrepresentation of men having sex with men (MSM) in the at-risk group. The microbiome-associated metabolites (MAM) appeared dysregulated in all HIV groups compared to controls. We improved this clustering by adding transcriptomics and proteomics data for a refined immunometabolic at-risk-related clustering in PWH. In paper IV, immune-driven HC-like and at-risk groups were clustered based on metabolomics, transcriptomics, and proteomics. Several biomarkers from central carbon metabolism (CCM) and senescence-associated proteins were linked to the at-risk phenotype based on random forest, structural causal modeling, and co-expression networks. Senescent protein changes were associated with a deficiency in macrophage function based on single-cell data, cell profiling, flow cytometry, and proteomics from macrophage data and in vitro validation. We also developed personalized and group-level genome-scale metabolic models (GSMM) and confirmed the implication of metabolites from CCM and polyamides in at-risk phenotypes. Finally, we investigated the accelerated aging process (AAP) in PWH. In paper V, we calculated the biological age of PWH using transcriptomics data and grouped patients into aging groups; The decelerated aging process (DAP) group was linked with higher age, European origin, and a higher proportion of tenofovir disoproxil fumarate /alafenamide (TDF/TAF). AAP had a downregulation of metabolic pathways and an upregulation of inflammatory pathways.
In conclusion, my thesis identifies underlying mechanisms of immune aging using system biology tools in three independent cohorts of PWH for mechanistic studies and to improve their care and achieve healthy aging.
First, we investigated PWH with Metabolic Syndrome (MetS), a relatively common agingrelated disease in HIV-1. In paper I, we identified the dysregulation of glutamate metabolism in PWH with MetS using plasma metabolomics and measure of cell transporters by flow cytrometry. Then, we investigated the mechanisms of differing PWH on long-term successful ART from HIV-negative controls (HC). In paper II, we identified the dysregulation of amino acids and, more specifically, glutaminolysis (i.e., lysis of glutamine to glutamate) in PWH compared to HC using metabolomics in two independent cohorts to avoid the potential cohort biases. We identified five neurosteroids to be lower in PWH and potentially create neurological impairments in PWH. The glutaminolysis inhibition in chronically infected HIV-1 promonocytic (U1) cells induced apoptosis and latency reversal which could clear HIV reservoirs.
The first two papers universally clarified our knowledge about dysregulated metabolic traits following a prolonged ART in PWH. However, we observed heterogeneity among the clinically defined PWH. Therefore, we focused more on the multi-omics data-driven approaches to stratify the at-risk group who were either dysregulated metabolically atrisk PWH (paper III) or immunometabolic at-risk group (paper IV) and clarified the biological aging process by measuring transcriptomics age (paper V).
In paper III, we found three groups of PWH based on multi-omics integration of lipidomics, metabolomics, and microbiome. The severe at-risk metabolic complications showed increased weight-related comorbidities and di- and triglycerides compared to the other clusters. At-risk and HC-like groups displayed similar metabolic profiles but were different from HC. An increase in Prevotella was linked to the overrepresentation of men having sex with men (MSM) in the at-risk group. The microbiome-associated metabolites (MAM) appeared dysregulated in all HIV groups compared to controls. We improved this clustering by adding transcriptomics and proteomics data for a refined immunometabolic at-risk-related clustering in PWH. In paper IV, immune-driven HC-like and at-risk groups were clustered based on metabolomics, transcriptomics, and proteomics. Several biomarkers from central carbon metabolism (CCM) and senescence-associated proteins were linked to the at-risk phenotype based on random forest, structural causal modeling, and co-expression networks. Senescent protein changes were associated with a deficiency in macrophage function based on single-cell data, cell profiling, flow cytometry, and proteomics from macrophage data and in vitro validation. We also developed personalized and group-level genome-scale metabolic models (GSMM) and confirmed the implication of metabolites from CCM and polyamides in at-risk phenotypes. Finally, we investigated the accelerated aging process (AAP) in PWH. In paper V, we calculated the biological age of PWH using transcriptomics data and grouped patients into aging groups; The decelerated aging process (DAP) group was linked with higher age, European origin, and a higher proportion of tenofovir disoproxil fumarate /alafenamide (TDF/TAF). AAP had a downregulation of metabolic pathways and an upregulation of inflammatory pathways.
In conclusion, my thesis identifies underlying mechanisms of immune aging using system biology tools in three independent cohorts of PWH for mechanistic studies and to improve their care and achieve healthy aging.
List of papers:
I. Gelpi M*, Mikaeloff F*, Knudsen AD, Benfeitas R, Krishnan S, Svenssson Akusjärvi S, Høgh J, Murray DD, Ullum H, Neogi U†, Nielsen SD. (2021) The central role of the glutamate metabolism in long-term antiretroviral treated HIV-infected individuals with metabolic syndrome. Aging (Albany NY). 2021 Oct 11;13(19):22732-22751. (Equal contribution).
Fulltext (DOI)
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II. Mikaeloff F, Svensson Akusjärvi S, Ikomey GM, Krishnan S, Sperk M, Gupta S, Magdaleno GDV, Escós A, Lyonga E, Okomo MC, Tagne CT, Babu H, Lorson CL, Végvári Á, Banerjea AC, Kele J, Hanna LE, Singh K, de Magalhães JP, Benfeitas R, Neogi U†. (2022) Trans cohort metabolic reprogramming towards glutaminolysis in long-term successfully treated HIV-infection. Communications Biology. 2022 Jan 11;5(1):27.
Fulltext (DOI)
Pubmed
View record in Web of Science®
III. Mikaeloff F†, Gelpi M, Benfeitas R, Knudsen AD, Vestad B, Høgh J, Hov JR, Benfield T, Murray D, Giske CG, Mardinoglu A, Trøseid M, Nielsen SD, Neogi U† (2023) Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection. Elife. 2023 Feb 16;12:e82785.
Fulltext (DOI)
Pubmed
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IV. Mikaeloff F, Gelpi M, Escós A, Olofsson A, Svensson Akusjärvi S, Schuster S, Nikouyan N, Knudsen AD, Vestad B, Høgh J, Hov JR, Benfield T, Murray D, Trøseid M, Gupta S, Pawar V, Benfeitas R, Vegvary A, O’Mahony L, Savai R, Björkström N, Lourda M, de Magalhães JP, Mardinoglu A, Weiß S, Karlsson A, Nielsen SD, Neogi U†. Integrative systems analysis-based risk stratification for metabolic complications in well-treated HIV-infected individuals. [Manuscript]
V. Mikaeloff F†, Gelpi M, Escos A, Knudsen AD, Høgh J, Benfield T, de Magalhães JP, Nielsen SD, Neogi U†. Transcriptomics age acceleration in prolonged treated HIV infection. [Manuscript]
I. Gelpi M*, Mikaeloff F*, Knudsen AD, Benfeitas R, Krishnan S, Svenssson Akusjärvi S, Høgh J, Murray DD, Ullum H, Neogi U†, Nielsen SD. (2021) The central role of the glutamate metabolism in long-term antiretroviral treated HIV-infected individuals with metabolic syndrome. Aging (Albany NY). 2021 Oct 11;13(19):22732-22751. (Equal contribution).
Fulltext (DOI)
Pubmed
View record in Web of Science®
II. Mikaeloff F, Svensson Akusjärvi S, Ikomey GM, Krishnan S, Sperk M, Gupta S, Magdaleno GDV, Escós A, Lyonga E, Okomo MC, Tagne CT, Babu H, Lorson CL, Végvári Á, Banerjea AC, Kele J, Hanna LE, Singh K, de Magalhães JP, Benfeitas R, Neogi U†. (2022) Trans cohort metabolic reprogramming towards glutaminolysis in long-term successfully treated HIV-infection. Communications Biology. 2022 Jan 11;5(1):27.
Fulltext (DOI)
Pubmed
View record in Web of Science®
III. Mikaeloff F†, Gelpi M, Benfeitas R, Knudsen AD, Vestad B, Høgh J, Hov JR, Benfield T, Murray D, Giske CG, Mardinoglu A, Trøseid M, Nielsen SD, Neogi U† (2023) Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection. Elife. 2023 Feb 16;12:e82785.
Fulltext (DOI)
Pubmed
View record in Web of Science®
IV. Mikaeloff F, Gelpi M, Escós A, Olofsson A, Svensson Akusjärvi S, Schuster S, Nikouyan N, Knudsen AD, Vestad B, Høgh J, Hov JR, Benfield T, Murray D, Trøseid M, Gupta S, Pawar V, Benfeitas R, Vegvary A, O’Mahony L, Savai R, Björkström N, Lourda M, de Magalhães JP, Mardinoglu A, Weiß S, Karlsson A, Nielsen SD, Neogi U†. Integrative systems analysis-based risk stratification for metabolic complications in well-treated HIV-infected individuals. [Manuscript]
V. Mikaeloff F†, Gelpi M, Escos A, Knudsen AD, Høgh J, Benfield T, de Magalhães JP, Nielsen SD, Neogi U†. Transcriptomics age acceleration in prolonged treated HIV infection. [Manuscript]
Institution: Karolinska Institutet
Supervisor: Neogi, Ujjwal
Co-supervisor: Benfeitas, Rui; Gabriel, Erin
Issue date: 2023-05-10
Rights:
Publication year: 2023
ISBN: 978-91-8017-002-4
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