Material S1.

Endpoint definitions and biochemical measurements

Myocardial infarction was defined on the basis of International Classification of Diseases, ninth revision

(ICD-9) code 410 or ICD-10 code I21. Coronary artery bypass surgery was identified from national

Swedish classification systems of surgical procedures and defined as procedure codes 3065, 3066, 3068,

3080, 3092, 3105, 3127, or 3158 in the Op6 system; or as procedure code FN in the KKÅ97 system.

Percutaneous intervention was identified from SCAAR.

Cigarette smoking was elicited by a self-administered questionnaire, with current cigarette smoking

defined as any use within the past year. Arterial stiffness was measured as the carotid–femoral pulse wave

velocity (PWV), using an applanation tonometry technique (SphygmoCor, Atcor Medical, Australia), as

described previously1. Measurements of fasting total cholesterol, HDL cholesterol, triglycerides, and

glucose were made according to standard procedures at the Department of Clinical Chemistry at Malmö

University Hospital. LDL cholesterol was estimated with the Friedewald equation. Creatinine (mmol/l)

was measured in plasma and analyzed with the Jaffé method, and traceable to the International

Standardization with isotope dilution mass spectrometry. The eGFR was calculated according to the

previously reported CKD-Epidemiology Collaboration creatinine equation2. C-reactive protein (CRP) was

analysed with the Tina-quant CRP latex assay (Roche Diagnostics, Basel, Switzerland).

The Framingham risk score

The Framingham risk score estimates the 10-year risk of developing cardiovascular disease. The score is

calculated by giving risk points depending on sex, age, total cholesterol, HDL-cholesterol, anti-

hypertensive treatment, systolic blood pressure and smoking. Points from Table S6-S10 are summed and

used in table S11 to estimate the 10-year risk.

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Material S2.

Analytical procedures

Metabolites were profiled in EDTA/Citrate plasma using liquid chromatography-mass spectrometry (LC-

MS) with a UPLC-QTOF-MS System (Agilent Technologies 1290 LC, 6550 MS, Agilent Technologies,

Santa Clara, CA, USA). Plasma samples stored at -80⁰C were thawed on ice before metabolite extraction

was performed by adding 120 µl extraction solvent (4⁰C) to 20 µl plasma and incubating at 4⁰C with

mixing at 1250 rpm during one hour. After incubation the samples were centrifuged for 15 minutes at

14000 x g and the supernatants were transferred to glass vials. Extraction solvent consisted of 80:20

methanol/water (Liquid Chromatography grade) and the stable isotope labeled internal standards (Table

S2). Samples were separated on an Acquity UPLC BEH Amide column (1.7µm, 2.1 * 100 mm; Waters

Corporation, Milford, MA, USA) maintained at 40 ⁰C. Solvent A: H2O with 10mM Ammonium Formate

and 0.1 % Formic acid. Solvent B: Acetonitrile with 0.1% Formic Acid. Gradient: 0-3 min, 100-95 % B;

3-6 min, 95-80 % B; 6-13 min, 80-70 % B; 13-14 min, 70-40 % B; 14-16 min, 40% B; 16-17 min, 100 %

B. The flow rate was 0.4 ml/min and the sample injection volume 2µl. The autosampler was kept at 16

⁰C. Mass spectrometry was performed in positive electrospray ionization. The sheath gas temperature was

set at 350 ⁰C and the sheath gas flow at 12 l/min. The drying gas flow was 14 l/min and was delivered at

200 ⁰C. Mass spectra were acquired at a rate of 1 spectrum/s and the mass range was 70 -1000 m/z.

Samples were analyzed in batches of 180 samples, where pooled quality control (QC) samples were

injected every 8 samples and in the beginning of each batch to ensure high repeatability and condition the

LC-column respectively.

Peak picking

Nontargeted metabolomics was performed in pooled plasma samples from the Malmö Offspring Study.

Peak picking was performed by using the Molecular feature extraction algorithm in Agilent MassHunter

Profinder B.06.00. Metabolite features (N=1906) that were present in >80 % of the pooled plasma

2

samples were extracted from analytical samples. Metabolite features were extracted using the Find by ion

algorithm in Agilent MassHunter Profinder B.06.00. The allowed ion adducts included (M+H)+ and

(M+NH4)+. Metabolite features (N=1446) that were present in > 80 % of the analytical samples were

included in further statistical analyses.

Normalization

Normalization was performed using two different methods. For metabolites where isotope-labeled

internal standards were spiked into each sample, the metabolites were quantified by calculating the area

ratio to each metabolites’ isotope labeled internal standard, followed by multiplying with the known

concentration of the internal standard. For the remaining metabolites, the measurements in the quality

control samples were used to create a correction curve to which each metabolite was normalized. First, a

low-order nonlinear locally estimated smoothing function was fitted to the metabolite signals in the

quality control samples as a function of the injection order. Using this function, a correction curve for the

analytical samples was interpolated, to which the metabolite measurements in the analytical samples were

normalized3. The α-parameter, reflecting the proportion of samples to be used when constructing the

correction curve, was set to 2/3. The normalization was performed in R 3.4.3.

3

Material S3.

Metabolite identifications

Metabolite annotation was performed for GBR metabolites by matching spectra and retention times (rt)

against an in-house metabolite library and publically available databases. Annotations followed the

Metabolomics Standard Initiative guidelines4 by defining annotation confidence levels (level 1-4) to each

metabolite feature. Level 1 confidence (identified metabolite), required accurate mass-over-charge ratio

(m/z), rt and fragmentation spectra as synthetic standards in the in-house metabolite library. Level 2

confidence (annotated metabolite), required accurate m/z and fragmentation in a public database. Level 3

confidence (annotated metabolite class), required m/z, fragmentation spectra or rt to be consistent with

previous data on metabolites from a certain class. Level 4 confidence consists of unknown metabolite

features. The annotation level for the 33 GBR metabolites can be found in Table S12. Evidence for

identification of Phenylacetylglutamine (PAG) is given in Figure S3. Synthetic metabolite standards were

purchased from Toronto Research Chemicals (New York, ON, Canada).

4

Table S1. Baseline characteristics of included and excluded participants.

Trait Included participants

(N=3799)

Excluded participants

(N=1606)

P

Age (years) 57.7 (±6.0) 57.3 (±5.8) 0.007

Sex (% female) 58.8 58.7 0.98

BMI (kg/m2) 25.7 (±3.9) 26.0 (±4.0) 0.0093

Fasting glucose (mmol/l) 5.2 (±1.4) 5.1 (±1.3) <0.001

LDL cholesterol (mmol/l) 4.2 (±1.0) 4.2 (±1.0) 0.89

HDL cholesterol (mmol/l) 1.4 (±0.4) 1.3 (±0.4) <0.001

Triglycerides (mmol/l) 1.3 (±0.6) 1.5(±1.1) <0.001

Hypertension (%) 16.3 18.3 0.12

Current Smokers (%) 27.4 26.8 0.46

Baseline characteristics of the Malmö Diet and Cancer - Cardiovascular Cohort (MDC-CC) participants stratified by included

(with fasting plasma) and excluded participants (no fasting plasma available). In MDC-CC, plasma metabolomics was performed

in 3799 participants, where citrate plasma samples were available, while the remaining 1606 participants’ plasma could not be

analyzed. Traditional risk factors are given for both groups above, where standard deviations are given in parentheses.

5

Table S2. Internal standards used in metabolomics experiments.

Metabolite Internal Standard Concentration (µM) Vendor1-Methylnicotinamide, d3 0.075 TRCAcetylcarnitine, d3 0.12 CILADMA, d6 0.30 TRCAlanine, d4 [15N] 84 CILArginine, d7 [15N]4 21 CILAsparagine, d3 [15N]2 32 CILBetaine, d3 1.6 TRCButyrylcarnitine, d3 0.025 CILCarnitine, d9 0.54 CILCholine, d13 1.3 CILCitrulline, d4 0.96 CILCotinine, d3 0.030 CILDimethylglycine, d6 1.4 TRCGlutamate, d5 [15N] 72 CILGlutamine, d5 [15N]2 33 CILHistidine, d5 [15N]3 5.5 CILIsoleucine, d10 [15N] 50 CILIsovalerylcarnitine, d9 0.029 CILLeucine, d3 [15N] 79 CILLysine, d4 [15N]2 18 CILMethionine, d8 [15N] 8.2 CILMyristoylcarnitine, d9 0.028 CILNicotinamide, d4 0.53 CILOctanoylcarnitine, d3 0.026 CILOrnithine, d6 9.0 CILPalmitoylcarnitine, d3 0.051 CILPhenylalanine, d8 [15N] 36 CILProline, d7 [15N] 19 CILPropionylcarnitine, d3 0.025 CILSerine, d3 [15N] 35 TRCTaurine, d4 19 TRCThreonine, d5 [15N] 41 CILTryptophan, d8 [15N]2 12 CILTyrosine, d7 [15N] 20 CILValine, d8 [15N] 56 CIL

Concentrations of internal standards of measured metabolites used in the Liquid chromatography-mass spectrometry analysis. TRC= Toronto Research Chemicals (New York, ON, Canada), CIL= Cambride Isotope Laboratories (Tewksbury, MA, USA)

6

Table S7. Age-contribution to the Framingham risk score.

Age Female points Male points

20 - 34 -7 -9

35 - 39 -3 -4

40 - 44 0 0

45 - 49 3 3

50 - 54 6 6

55 - 59 8 8

60 - 64 10 10

65 - 69 12 11

70 - 74 14 12

>75 16 13

The table presents the points contributed to the Framingham risk score from age.

7

Table S8. Total cholesterol-contribution to the Framingham risk score.

Total cholesterol mg/dL Female points Male points

Age interval: 20 - 39

<160 0 0

160 - 199 4 4

200 - 239 8 7

240 - 279 11 9

>=280 13 11

Age interval: 40 - 49

<160 0 0

160 - 199 3 3

200 - 239 6 5

240 - 279 8 6

>=280 10 8

Age interval: 50 - 59

<160 0 0

160 - 199 2 2

200 - 239 4 3

240 - 279 5 4

>=280 7 5

Age interval: 60 - 69

<160 0 0

160 - 199 1 1

200 - 239 2 1

240 - 279 3 2

>=280 4 3

Age interval: >70

<160 0 0

160 - 199 1 0

200 - 239 1 0

240 - 279 2 1

>=280 2 1

The table presents the points contributed to the Framingham risk score from total cholesterol levels, in different age intervals.

8

Table S9. HDL cholesterol-contribution to the Framingham risk score.

HDL cholesterol mg/dL Female pts Male pts

>=60 -1 -1

50 - 59 0 0

40 - 49 1 1

<40 2 2

The table presents the points contributed to the Framingham risk score from HDL cholesterol levels.

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Table S10. Systolic Blood Pressure-contribution to the Framingham risk score.

SBP mmHg / treated Female points Male points

<120 0 0

120 - 129 3 1

130 - 139 4 2

140 -159 5 2

>=160 6 3

SBP mmHg / untreated Female points Male points

<120 0 0

120 - 129 1 0

130 - 139 2 1

140 -159 3 1

>=160 4 2

The table presents the points contributed to the Framingham risk score from systolic blood pressure (SBP) for individuals with (treated) and without (untreated) anti-hypertensive treatment. The score contributions for male and female individuals are given separately.

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Table S11. Smoking-contribution to the Framingham risk score.

Smoking (if yes) Female points Male points

Age

20 - 39 9 8

40 - 49 7 5

50 - 59 4 3

60 - 69 2 1

> 70 1 1

Smoking (if no) 0 0

The table presents the points contributed to the Framingham risk score from smoking for male and female individuals.

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Table S12. 10-year cardiovascular risk using the Framingham risk score.

Female results Male resultsPoints Risk percentage Points Risk percentage

<0 0% <0 0%0 - 8 <1% 0 <1%9 - 12 1% 1 - 4 1%13 - 14 2% 5 - 6 2%15 3% 7 3%16 4% 8 4%17 5% 9 5%18 6% 10 6%19 8% 11 8%20 11% 12 10%21 14% 13 12%22 17% 14 16%23 22% 15 20%24 27% 16 25%>=25 >30% >=17 >30%

The table presents the 10-year cardiovascular risk using the Framingham risk score. Scores correspond to different risks for male and female individuals.

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Table S13. Annotation of gut bacteria-related metabolites.

Putative Identity Annotation level m/z Retention time (min)Phenylacetylglutamine 1 265.119 1.90Glutamate 1 148.061 8.02Hippurate 1 180.066 1.14Cystine 1 241.031 12.7Methionine-S-Oxide 1 165.055 8.49Beta-carotene 1 568.4287 0.85Arginine 1 175.120 10.70Trigonelline 1 138.055 6.26Sarcosine 1 90.055 7.25LPCO 16:1 2 480.345 4.76Urobilin 2 595.3483 1.15PC 22:5_P18:1 2 818.602 0.89N-acetylglutamine 2 189.087 8.29LysoPE 22:0 2 538.385 4.74GlnGlu 2 276.120 10.62

Metabolites that correlated with the gut microbiota (GBR metabolites) in the Malmö Offspring Study (N=776) were annotated according to the Metabolomics Standard Initiative guidelines, where level 1 is considered as identified and level 2 is considered as putatively annotated. PC = phosphatidylcholine, PE = phosphatidylethanolamine. LPCO = Lysophosphatidylcholine ether.

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Figure S1. Coefficient of variation (CV) quality control samples.

Coefficient of variation (CV) in pooled quality control samples, for all metabolites measured in Malmö Diet and Cancer – Cardiovascular Cohort and Malmö Preventive Project (MPP).

14

Figure S2. Schematic view of the study workflow.

15

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Figure S3. Fragmentation spectra for Phenylacetylglutamine.

Fragmentation spectra for Phenylacetylglutamine (PAG). Fragmentation mass spectra for PAG in a pool of plasma samples from The Malmö Offspring Study (upper panel) and from synthetic standard (lower panel).

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