Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection

  1. Flora Mikaeloff  Is a corresponding author
  2. Marco Gelpi
  3. Rui Benfeitas
  4. Andreas D Knudsen
  5. Beate Vestad
  6. Julie Høgh
  7. Johannes R Hov
  8. Thomas Benfield
  9. Daniel Murray
  10. Christian G Giske
  11. Adil Mardinoglu
  12. Marius Trøseid
  13. Susanne D Nielsen
  14. Ujjwal Neogi  Is a corresponding author
  1. The Systems Virology Lab, Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institute, Sweden
  2. Copenhagen University Hospital Rigshospitalet, Denmark
  3. National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Sweden
  4. Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Norway
  5. Norwegian PSC Research Center, Oslo University Hospital Rikshospitalet, Norway
  6. Institute of Clinical Medicine, University of Oslo, Norway
  7. Department of Infectious Diseases, Copenhagen University Hospital – Amager and Hvidovre, Denmark
  8. Centre of Excellence for Health, Immunity and Infections (CHIP), Rigshospitalet, University of Copenhagen, Denmark
  9. Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet, Sweden
  10. Science for Life Laboratory, KTH - Royal Institute of Technology, Sweden
  11. Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, United Kingdom
  12. Institute of Clinical Medicine, Norway
7 figures, 3 tables and 4 additional files

Figures

Figure 1 with 1 supplement
Similarity network fusion-based PWH stratification using lipidomics, metabolomics, and microbiome integration.

(A) Scatter plot showing the maximization of Eigen gap and the minimization of rotation cost for optimizing the number of clusters. (B) Concordance matrix between the combined network (SNF) and each omics network based on NMI calculation (0=no mutual information, 1=perfect correlation). (C) SNF-combined similarity network colored by clusters (SNF-1/HC-like=blue, SNF-2/severe at-risk=yellow, SNF-3/mild at-risk=grey) obtained after spectral clustering. Edges' color indicates the strength of the similarity (black = strong, grey = weak). (D) PCA plot of samples based on fused network. Samples are colored by condition.

Figure 1—figure supplement 1
PCA plot of samples after prior standardization based on (a) Lipidomics (b) Metabolomics (c) Microbiome.

Variance proportions are written on each component axis. Samples are colored by condition (Ctrl = green, SNF-1=blue, SNF-2=yellow, SNF-3=grey).

Figure 2 with 1 supplement
Lipidomics and metabolomics, characterization of the PWH clusters.

(A) Boxplots of DAG from untargeted lipid classes separated by groups. Significant stars are displayed for each comparison with *FDR <0.05, **FDR <0.01, ***FDR <0.001 (limma). (B) Boxplots of TAG from untargeted lipid classes separated by groups. (C) PCA plot of samples after prior standardization based on significant metabolites between at least one pairwise comparison (limma, FDR <0.05). Variance proportions are written on each component axis. Samples are colored by condition. (D) Circular heatmap of the top 159 metabolites (FDR <0.005). Metabolites are represented as slices and labeled around the plot. LogFold Change from significant metabolites between groups is displayed in the first six outer layers. The 7th to 9th layers represents the coefficient of correlation between metabolites and BMI, metabolites and age (Spearman, p <0.1, absolute R>0.15) and the p-value from significant associations between metabolites and gender (χ2, p<0.1). The inner layer represents the pathway of each metabolite. (E) PCA plot based on metabolites differing clusters adjusted for transmission mode and CD4 count.

Figure 2—source data 1

Table of differential lipid abundance analysis SNFs by lipids classes by clusters and corrected for transmission mode and CD4 count.

https://cdn.elifesciences.org/articles/82785/elife-82785-fig2-data1-v3.xlsx
Figure 2—figure supplement 1
Boxplots of untargeted lipid classes separated by groups.

Color is based on groups (Ctrl = green, SNF-1=blue, SNF-2=yellow, SNF-3=grey). p Values are displayed for each comparison (Mann Withney U Test).

Figure 3 with 2 supplements
Transmission mode drove cluster differences in microbiome data.

(A) Boxplots of alpha diversity indices (Observed, ACE, Chao1, Fisher) separated by HIV cluster. Significant stars are shown for each comparison (Mann-Whitney U test). (B) Non-metric multidimensional scaling (NMDS) plot of Bray-Curtis distances. Samples are colored by clusters. Boxplots based on NMDS1 and NMDS2 are represented. (C) Barplot represents the relative abundance of bacteria at the family level for each patient. Patient information is displayed above the barplot, including cluster, metabolic syndrome (MetS: yes/no), hypertension (yes/no), transmission mode, and gender. (D) Barplot showing the top microbial families by representing their coefficient from PERMANOVA between SNF-1 and SNF-2. (E) Barplot showing the top microbial families between SNF-1 and SNF-3. (F) LEfSe cladogram representing cluster-specific microbial communities to HC-like and to at-risk groups (SNF-2/SNF-3). Top families from PERMANOVA are labeled. (G) Boxplot of relative abundance at family level for Bacteroides (top) and Prevotella (bottom). Significant stars are shown for significant comparisons (Mann-Whitney U test).

Figure 3—source data 1

Alpha diversity indices statistics.

https://cdn.elifesciences.org/articles/82785/elife-82785-fig3-data1-v3.xlsx
Figure 3—source data 2

Permutational multivariate analysis of variance at the family level.

https://cdn.elifesciences.org/articles/82785/elife-82785-fig3-data2-v3.xlsx
Figure 3—figure supplement 1
Boxplots of alpha diversity indices (se.chao1,Simpson, Shannon, se.ACE, InvSimpson) separated by HIV-cluster.

Color is based on groups (Ctrl = green, SNF-1=blue, SNF-2=yellow, SNF-3=grey).

Figure 3—figure supplement 2
Non-metric multidimensional scaling (NMDS) plot of Bray-Curtis distances.

Samples are colored by (A) Transmission mode (B) Central obesity (C) Metabolic Syndrome (D) Hypertension.

Figure 4 with 2 supplements
Factor analysis highlights the essential features for cluster separation and potential microbiome-derived metabolites importance (A) Barplot of total variance explained by MOFA model per view.

(B) Variance decomposition plot. The percentage of variance is explained by each factor for each view. (C) External covariate association with factors plot. Association is represented with log10 adjusted p-values from Pearson correlation. (D) Heatmap representing levels of microbial communities, metabolites, and lipids with the higher absolute weight in MOFA factors associated with cluster (F1, F2, F3, F5, F8). Samples are labeled according to the study groups. Data were Z-score transformed. The type of data (lipid, metabolite, microbe) is displayed on the right. (E) Top 20 features with higher absolute weight in MOFA factors associated with cluster (F1, F2, F3, F5, F8) from lipidome, metabolome, and microbiome. Microbiome-derived metabolites and bacterial phylum of interest are colored in blue and red, respectively. (F) MOFA features differing clusters and interactions extracted from the three-layers consensus co-expression network. Microbiome-derived metabolites are labeled.

Figure 4—figure supplement 1
Correlation matrix of MOFA factors.

Size and transparency are proportional to the absolute coefficient of correlation. Color is displayed as a gradient-based coefficient of correlation from –1 (red) to 1 (blue).

Figure 4—figure supplement 2
Cytoscape consensus co-expression network.

Color and label are based on communities.

Microbiome-associated metabolites are affected in HIV clusters (A) Heatmap representing abundances of microbiome-derived metabolites differing in at least one comparison.

Data were Z-score transformed. Significant logFC (limma, FDR <0.05) of pairwise comparisons between conditions, groups, and under groups of microbiome-derived metabolites are displayed on the right. (B) Cytoscape network showing significant positive and negative associations between clinical parameters and microbiome-derived metabolites (univariate linear regression, FDR <0.05). Clinical parameters are colored based on categories. (C) Co-expression network of metabolomics data in PWH. Metabolites are grouped by communities, and microbiome-derived metabolites are labeled and colored based on the subgroup. (D) The subset of microbiome-derived metabolites from the co-expression network. Non-significant metabolites in all comparisons are displayed with transparency. Significant microbiome-derived metabolites between at least two conditions are labeled.

Figure 5—source data 1

Univariate linear regression between clinical parameters and microbiome-derived metabolites differing groups.

https://cdn.elifesciences.org/articles/82785/elife-82785-fig5-data1-v3.xlsx
Author response image 1
Venn diagram of metabolites significantly different between clusters in noncorrected limma model (left) and model corrected for transmission mode and CD4 count (right).
Author response image 2
Venn diagram of lipids significantly different between clusters in noncorrected limma model (left) and model corrected for transmission mode and CD4 count (right).

Tables

Table 1
Patient characteristics.
Complete CohortSNF-1SNF- 2SNF-3P values
At-risk ClassificationHC-likeSevere at riskMild
N97194434
Age in years, Median (IQR)54 (48–63)60 (48–68)54 (48–62)54 (51–60)0.75
Gender, Male, N (%)84 (87)15 (79)40 (91)29 (85)0.36
Ethnicity Caucasian, N (%)79 (81)15 (79)38 (87)26 (77)0.49
Mode of transmission, N (%)
Homosexual/bisexual
Heterosexual
Other/unknown
63 (65)
26 (27)
8 (8)
9 (47)
7 (37)
3 (16)
36 (81)
6 (14)
2 (5)
18 (53)
13 (38)
3 (9)
0.017
CD4 Nadir, cells/mL, Median (IQR)235 (123–320)240 (127–330)240 (145–365)223 (42–290)0.49
CD4 at ART Initiation, cells/mL, Median (IQR)287 (155–410)270 (120–360)318 (192–463)240 (108–320)0.11
Viral Load at ART initiation, log copies/mL, Median (IQR)5.02 (4.34–5.61)4.87 (4.32–5.5)5.11 (4.74–5.61)4.94 (4.2–5.55)0.35
CD4 at sampling, cells/mL, Median(IQR)713 (570–900)680 (540–958)762 (689–923)610 (475–819)0.015
CD8 at sampling, cells/mL, Median (IQR)775 (600–1100)780 (630–879)894 (638–1300)700 (530–870)0.054
Viral load (<50 copies/mL), N (%)97 (100)19 (100)44 (100)34 (100)1
Duration of treatment in years, median (IQR)15 (9–18)15 (13–18)15 (8–18)14 (7–17)0.73
Current Treatment, 1st drug, N (%)
ABC
TDF/TAF
Other
31 (32)
42 (43)
24 (25)
8 (42)
8 (42)
3 (16)
13 (30)
19 (43)
12 (27)
10 (29)
15 (44)
9 (27)
0.84
Current Treatment, 3rd drug, N (%)
NNRTI
PI/r
INSTI
Other
38 (39)
18 (19)
15 (15)
26 (27)
8 (42)
4 (21)
4 (21)
3 (16)
14 (32)
11 (25)
6 (14)
13 (29)
16 (47)
3 (9)
5 (15)
10 (29)
0.45
BMI, Mean (SD)24 (22–27)22 (19–25)26 (23–28)24 (22–27)0.003
VAT, Median (IQR)89 (36–142)41 (19–106)127 (79–196)69 (26–100)0.0001
SAT, Median (IQR)111 (70–167)69 (33–115)117 (82–174)119 (83–190)0.02
MetS, N (%)43 (44)6 (32)31 (70)6 (17)0.000009
Central obesity, N(%)57 (59)8 (42)32 (73)17 (50)0.033
Waist circumference (cm)94 (87–101)90 (84–95)100 (91–105)90 (87–97)0.0007
Hypertension, N (%)49 (51)5 (26)23 (52)21 (62)0.04
Appendix 1—table 1
List of parameters used in the study.
DescriptionTypeDefinition
Ethnicity defined as in the Danish HIV cohortlogical1: caucasian, 2: asian, 3: black, 4: other 5: inuit
Origin defined as in the Danish HIV cohortlogical1: Denmark, 2: Other Scandinavian country 3: Other European country, 4: Turkia, 5: Pakistan, India and Sri Lanka, 6: Arabian countries / Iran, 7: Other (Africa, Asia, Greenland)
Mode of HIV transmissionlogical1.Homo/biseksuel, 2. IV drug use, 3.homoseksuel+misbrug4.hæmofili 5.blodtransfusion 6.heteroseksuel, 7. andet 8. unknown 9.perinatal
Genderlogical0: female, 1:male
Computed agenumericUnit: years
Body mass indexnumericUnit: kg/m2
Physical activity in spare timelogical1: Inactive 2: Slightly active 3: Moderately active 4: Very active
Meat intake (Beef)numericTimes per week in average
Meat intake (Poultry)numericTimes per week in average
Choice of fat for preparing warm disheslogical0: None, 1: Butter, 2: Spreadable (Kærgården), 3: Shortening (Stegemargarine), 4: Vegetable margarine (Plantemargarine), 5: Olive oil, 6: Other oil, 7: Other
Vegetable intakelogical0: Never 1: 1–3/month, 2: 1–2/week, 3: 3–4/week, 4: 5–6/week, 5: 1/day, 6: 2–3/day, 7:>3 /day
Fruit intake (whole fruit/portion of fruit)logical0: Never, 1: 1–3/month, 2: 1–2/week, 3: 3–4/week, 4: 5–6/week, 5: 1/day, 6: 2–3/day, 7:>3 /day
*Weekly alcohol consumptionnumericUnit:gram
Cumulative smokingnumericUnit: Pack years in current and previous smokers
Current Smokinglogical0: No, 1: Yes
Current CD4 count (closest to date of inclusion)numericcell / ul
Current CD8 countnumericcell / ul
Ratio CD4/CD8numericx
CD4_nadirnumericcell / ul
CD4 at ART initiationnumericcell / ul
Current viral loadnumericcopies / ul
VL at ART initiationnumericcopies / ul
Log10 of VL at ART initiationnumericx
SNF clusterslogical1:SNF-1, 2: SNF-2, 3: SNF-3
Duration of current cARTnumericUnit: months
Duration of current cARTnumericUnit: years
Duration of previous cARTnumericUnit: months
3rd DruglogicalNNRTI, PI/r,INSTI, Other/unknow
1st druglogicalABC, TDF/TAF, Other/unknown
Subcutaneous adipose tissue (SAT)numericsquared centimeters
Visceral adipose tissue (VAT)numericsquared centimeters
Waist circumferencenumericUnit: cm
Systolic blood pressure, right armnumericUnit: mm mercury
Diastolic blood pressure, right armnumericUnit: mm mercury
Metabolic syndrome (MetS)*logical0: No, 1: Yes
Central obesitylogical0: No,1: Yes
hypertension (*JNC7 definition)logical0: No, 1: Yes
Diabeteslogical0: No, 1: Yes
Estimated glomerular function rate (eGFR)numericUnit: reads mL/min/1.73 m2
Alanine aminotransferase (ALAT)numericUnit:Units per liter
Antihypertensiveslogical0: No, 1: Yes
Appendix 2—table 1
List of microbiome-derived metabolites.
BIOCHEMICALSUPER.PATHWAYSUB.PATHWAYgroupunder_group
butyrate/isobutyrate (4:0)LipidShort Chain Fatty Acidproduced_by_intestinal_bacteriaShort Chain Fatty Acid
N-acetylputrescineAmino AcidPolyamine Metabolismproduced_by_intestinal_bacteriaPolyamines
spermidineAmino AcidPolyamine Metabolismproduced_by_intestinal_bacteriaPolyamines
spermineAmino AcidPolyamine Metabolismproduced_by_intestinal_bacteriaPolyamines
1-methyl-4-imidazoleacetateAmino AcidHistidine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
1-methyl-5-imidazoleacetateAmino AcidHistidine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
1-ribosyl-imidazoleacetate*Amino AcidHistidine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
1H-indole-7-acetic acidXenobioticsBacterial/Fungalproduced_by_intestinal_bacteriaIndole derivatives
2,3-dihydroxy-2-methylbutyrateAmino AcidLeucine, Isoleucine and Valine Metabolismproduced_by_intestinal_bacteriaButyrate derivates
2-aminobutyrateAmino AcidGlutathione Metabolismproduced_by_intestinal_bacteriaButyrate derivates
2-hydroxybutyrate/2-hydroxyisobutyrateAmino AcidGlutathione Metabolismproduced_by_intestinal_bacteriaButyrate derivates
2-hydroxyphenylacetateAmino AcidPhenylalanine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
2-oxindole-3-acetateXenobioticsFood Component/Plantproduced_by_intestinal_bacteriaIndole derivatives
2 R,3R-dihydroxybutyrateLipidFatty Acid, Dihydroxyproduced_by_intestinal_bacteriaButyrate derivates
2 S,3R-dihydroxybutyrateLipidFatty Acid, Dihydroxyproduced_by_intestinal_bacteriaButyrate derivates
3,4-dihydroxybutyrateLipidFatty Acid, Dihydroxyproduced_by_intestinal_bacteriaButyrate derivates
3-(3-hydroxyphenyl)propionateXenobioticsBenzoate Metabolismproduced_by_intestinal_bacteriaPropionate derivates
3-(3-hydroxyphenyl)propionate sulfateXenobioticsBenzoate Metabolismproduced_by_intestinal_bacteriaPropionate derivates
3-aminoisobutyrateNucleotidePyrimidine Metabolism, Thymine containingproduced_by_intestinal_bacteriaButyrate derivates
3-carboxy-4-methyl-5-pentyl-2-furanpropionate (3-CMPFP)LipidFatty Acid, Dicarboxylateproduced_by_intestinal_bacteriaPropionate derivates
3-formylindoleXenobioticsFood Component/Plantproduced_by_intestinal_bacteriaIndole derivatives
3-hydroxy-2-ethylpropionateAmino AcidLeucine, Isoleucine and Valine Metabolismproduced_by_intestinal_bacteriaPropionate derivates
3-hydroxybutyrate (BHBA)LipidKetone Bodiesproduced_by_intestinal_bacteriaButyrate derivates
3-hydroxyisobutyrateAmino AcidLeucine, Isoleucine and Valine Metabolismproduced_by_intestinal_bacteriaButyrate derivates
3-indoleglyoxylic acidXenobioticsFood Component/Plantproduced_by_intestinal_bacteriaIndole derivatives
3-methyl-2-oxobutyrateAmino AcidLeucine, Isoleucine and Valine Metabolismproduced_by_intestinal_bacteriaButyrate derivates
3-phenylpropionate (hydrocinnamate)XenobioticsBenzoate Metabolismproduced_by_intestinal_bacteriaPropionate derivates
3-ureidopropionateNucleotidePyrimidine Metabolism, Uracil containingproduced_by_intestinal_bacteriaPropionate derivates
4-imidazoleacetateAmino AcidHistidine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
6-hydroxyindole sulfateXenobioticsChemicalproduced_by_intestinal_bacteriaIndole derivatives
7-hydroxyindole sulfateAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
acetoacetateLipidKetone Bodiesproduced_by_intestinal_bacteriaAcetate derivates
alpha-ketobutyrateAmino AcidMethionine, Cysteine, SAM and Taurine Metabolismproduced_by_intestinal_bacteriaButyrate derivates
citalopram propionate*XenobioticsDrug - Psychoactiveproduced_by_intestinal_bacteriaPropionate derivates
gamma-glutamyl-2-aminobutyratePeptideGamma-glutamyl Amino Acidproduced_by_intestinal_bacteriaButyrate derivates
guanidinoacetateAmino AcidCreatine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
hydantoin-5-propionateAmino AcidHistidine Metabolismproduced_by_intestinal_bacteriaPropionate derivates
imidazole propionateAmino AcidHistidine Metabolismproduced_by_intestinal_bacteriaPropionate derivates
iminodiacetate (IDA)XenobioticsChemicalproduced_by_intestinal_bacteriaAcetate derivates
indole-3-carboxylateAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
indoleacetateAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
indoleacetoylcarnitine*Amino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
indoleacetylglutamineAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
indolelactateAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
indolepropionateAmino AcidTryptophan Metabolismproduced_by_intestinal_bacteriaIndole derivatives
methyl indole-3-acetateXenobioticsFood Component/Plantproduced_by_intestinal_bacteriaIndole derivatives
phenylacetateAmino AcidPhenylalanine Metabolismproduced_by_intestinal_bacteriaAcetate derivates
taurineAmino AcidMethionine, Cysteine, SAM and Taurine Metabolismproduced_by_host_modified_by_bacteriaTaurine
deoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
deoxycholic acid 12-sulfate*LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
deoxycholic acid glucuronideLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycocholenate sulfate*LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycodeoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycodeoxycholate 3-sulfateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycohyocholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycolithocholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycolithocholate sulfate*LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycoursodeoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
glycoursodeoxycholic acid sulfate (1)LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
hyocholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
isoursodeoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
lithocholate sulfate (1)LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurochenodeoxycholic acid 3-sulfateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurocholenate sulfate*LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurodeoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurodeoxycholic acid 3-sulfateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurohyocholate*LipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
taurolithocholate 3-sulfateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism
ursodeoxycholateLipidSecondary Bile Acid Metabolismproduced_by_host_modified_by_bacteriaSecondary Bile Acid Metabolism

Additional files

Supplementary file 1

Table of differential lipid abundance analysis on individual lipids abundances between clusters corrected for transmission mode and CD4 count.

https://cdn.elifesciences.org/articles/82785/elife-82785-supp1-v3.xlsx
Supplementary file 2

False discovery rate after differential metabolite analysis between the groups.

https://cdn.elifesciences.org/articles/82785/elife-82785-supp2-v3.xlsx
Supplementary file 3

Table of differential metabolite abundance analysis after adjustment of the CD4 count at sampling and route of transmission.

https://cdn.elifesciences.org/articles/82785/elife-82785-supp3-v3.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/82785/elife-82785-mdarchecklist1-v3.docx

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  1. Flora Mikaeloff
  2. Marco Gelpi
  3. Rui Benfeitas
  4. Andreas D Knudsen
  5. Beate Vestad
  6. Julie Høgh
  7. Johannes R Hov
  8. Thomas Benfield
  9. Daniel Murray
  10. Christian G Giske
  11. Adil Mardinoglu
  12. Marius Trøseid
  13. Susanne D Nielsen
  14. Ujjwal Neogi
(2023)
Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
eLife 12:e82785.
https://doi.org/10.7554/eLife.82785