Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer’s disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls.
Metabolic phenotyping was applied to both urine (
Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine.
Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients.
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The pathogenesis of Alzheimer’s disease (AD) has previously been associated with both systemic inflammation [
A secondary metabolic pathway occurs in the enzymes tryptophan hydroxylase and 5-hydroxytryptophan decarboxylase leading to the production of the key neurotransmitter serotonin [
The metabolic balance between both pathways, and therefore the subsequent bioavailability of downstream metabolites, is reported to be influenced by the homeostatic control of the IDO enzyme [
Due to the links between AD pathogenesis, systemic inflammation and serotonergic signalling, the two pathways have previously been investigated in the disease, with changes in the concentration of circulating metabolites from both pathways reported in individuals clinically diagnosed with AD compared with controls. However, such investigations have been typically limited to small pilot studies and have not covered the full range of metabolites involved in the two pathways [
Biological pathways of interest that are implicated in health and disease can be effectively investigated using a technique known as metabolic phenotyping. Frequently, the technique is now being applied to large epidemiological and clinical cohorts to investigate metabolic changes that influence population health and disease [
Here, a multi-stage metabolic phenotyping study (Fig. Study workflow. An overview of the study design and overall workflow
Study participants were from the European AddNeuroMed and the London based Dementia Case Register (DCR) projects [
Within the MCI group, cognition was monitored at follow-up visits—those who remained cognitively stable at follow-up visits were classed as stable MCI (sMCI), whilst the second group experienced cognitive decline and received a later diagnosis of AD and were classed as converting MCI (cMCI).
Serum and urine samples were collected and stored frozen in aliquots at − 80 °C until use. The samples were from baseline collections only and had not been subjected to any freeze-thaw cycles. Mass spectrometry analysis was completed on 556 urine samples. Where available, matched serum samples were then analysed, resulting in the generation of spectra from 354 serum samples. An overview of study samples can be seen in Table Participant overview Total cohort Control MCI AD Participants 556 171 209 176 Male/female 269/287 83/88 95/114 91/85 Mean age (SD) 76.24 (5.76) 75.85 (5.17) 76.33 (6.03) 76.53 (5.99) MMSE score 25.67 (4.59) 28.73 (1.92) 26.86 (2.75) 21.17 (4.87) CDR 0.56 (0.51) 0.07 (0.18) 0.49 (0.08) 1.10 (0.54) Reported SSRI medication 43 4 16 23 Participants 354 86 165 103 Male/female 165/189 44/42 71/94 50/53 Mean age 76.95 (6.13) 75.97 (5.67) 77.50 (6.49) 76.91 (5.84) MMSE score 25.57 (4.37) 28.80 (1.99) 26.73 (2.24) 21.06 (4.79) CDR 0.59 (0.54) 0.04 (0.16) 0.49 (0.11) 1.16 (0.55) Reported SSRI medication 30 1 11 18 Overview of the sample cohort used in the study.
Urine samples (
Annotated data outputs (exported in comma-separated value format) were imported into R (v.3.5.2) for statistical analysis. Samples that were greater than five standard deviations above the mean for each metabolite were removed as outliers. Shapiro-Wilk testing demonstrated that the metabolite data were not normally distributed (
In phase 2 of the study, 17 metabolites (xanthurenic acid, kynurenine, serotonin, tryptophan, 3-hydroxyanthranilic acid, kynurenic acid, 3-hydroxykynurenine, β-nicotinamide mononucleotide, picolinic acid, 5-hydroxyindoleacetic acid, nicotinic acid, quinolinic acid, dopamine, neopterin, nicotinic riboside, citrulline, indole-3-acetic acid) were fully quantified, and an additional metabolite (NAD+) was semi-quantified in serum using a previously validated UHPLC-tandem mass spectrometry (UHPLC-MS/MS) method [
Statistical analysis was completed in R (v.3.5.2). Again, samples that were greater than five standard deviations above the mean for each metabolite were removed as outliers. Shapiro-Wilk testing demonstrated that the serum metabolite data were not normally distributed (
Metabolites that reported a Holm-adjusted
Pearson correlation to investigate associations with age.
Mann-Whitney Mild cognitive impairment participant overview Total MCI sMCI cMCI Participants 209 167 42 Male/female 95/114 80/87 15/27 Mean age (SD) 76.33 (6.03) 76.17 (5.60) 76.91 (7.38) MMSE 26.86 (2.75) 26.93 (2.94) 26.55 (1.76) CDR 0.49 (0.08) 0.48 (0.09) 0.51 (0.08) Reported SSRI medication 16 12 4 Participants 165 90 75 Male/female 71/94 42/48 29/46 Mean age 77.50 (6.49) 75.98 (5.95) 79.32 (6.67) MMSE 26.73 (2.24) 26.81 (2.38) 26.63 (2.07) CDR 0.49 (0.11) 0.48 (0.10) 0.53 (0.12) Reported SSRI medication 11 8 3 Overview of the two MCI subgroups used in the study. All samples in the study were taken at baseline; however, one MCI subgroup remained stable throughout follow-up visits (sMCI), whilst the second converted to a clinical diagnosis of AD at subsequent follow-up visits (cMCI).
Pearson correlation analysis was performed to investigate the relationship of metabolites across both biofluids (serum and urine). This was performed where matched serum/urine samples from the same participant study visit were available (
The effect of SSRI medication on the study cohort was investigated by comparing metabolite levels of two AD subgroups: those prescribed SSRI medication vs no SSRI prescribed medication. Data were then re-analysed using Kruskal-Wallis testing as described above, using only study participants who did not report a prescription for SSRI medication.
Good reproducibility was obtained throughout the analysis as determined from the biological QC samples (
Kruskal-Wallis testing reported significant inter-group metabolite differences for tryptophan ( Summary of Kruskal-Wallis univariate analysis Metabolite Adjusted Dunn’s post hoc test CTL-AD CTL-MCI MCI-AD Urine 0.0495 0.1484 Urine 0.4235 0.8470 Urine 0.8738 0.8738 0.0339 0.0339 0.0625 0.0756 Serum—3-hydroxyanthranilic acid 0.0222 0.3326 Serum—kynurenic acid 0.0222 0.3326 Serum—3-hydroxykynurenine 0.0236 0.3326 Serum—β-nicotinamide mononucleotide 0.0241 0.3326 Serum—picolinic acid 0.0518 0.5701 Serum—5-hydroxyindoleacetic acid 0.0991 0.9912 Serum—nicotinic acid 0.1066 0.9912 Serum—quinolinic acid 0.1828 1.0000 Serum—NAD+ 0.2589 1.0000 Serum—dopamine 0.3926 1.0000 Serum—neopterin 0.4934 1.0000 Serum—nicotinic riboside 0.6746 1.0000 Serum citrulline 0.8351 1.0000 Serum—indole-3-acetic acid 0.8518 1.0000 Serum—kynurenine/tryptophan ratio 0.2507 1.0000
For metabolites that reported a Holm-adjusted
An overall decreasing trend in metabolite cocentrations was also observed in the direction of control > MCI > AD for each metabolite identified as differentiating control samples from those from the cognitively impaired groups (Fig. Inter-group metabolite differences. Boxplots highlighting differences between metabolite concentrations in serum and urine when comparing AD (red), MCI (blue = sMCI, yellow = cMCI) and age-matched controls (CTL—green). Boxplots are shown for metabolites in the serotonin and kynurenine pathways that reported significant differences following univariate Kruskal-Wallis tests. Figure Inter-group metabolite differences stratified by gender. Boxplots highlighting differences between metabolite concentrations in serum when comparing Alzheimer’s disease (AD), mild cognitive impairment (MCI) and age-matched controls (CTL). Boxplots were fitted with a linear model coloured by gender (red = female, blue = male). Boxplots are shown for the metabolites in the serotonin and kynurenine pathways that reported significant differences between participant groups (Supplementary Figs. S
Data quality was assessed as described in
Kruskal-Wallis testing reported significant inter-group metabolite differences for tryptophan (
For metabolites that reported a Holm-adjusted
An overall decreasing trend in serum metabolite concentrations was also observed: control > MCI > AD for each metabolite (Fig.
Univariate Pearson correlation reported a negative association between serum tryptophan concentrations and an increase in participant age (
A positive association was noted between urinary 5-hydroxyindoleacetic acid and participant age ( Metabolite associations with participant age. Plots presenting metabolite concentration change in association with participant age. The plots were fitted with a linear regression model. Plots are shown for the metabolites in the serotonin and kynurenine pathways that reported significant differences between participant groups (Supplementary Figs. S
Univariate Pearson correlation reported a significant negative association between participant MMSE score and urine kynurenine/tryptophan ratio ( Serum and urine metabolite associations with participant MMSE scores. Plots presenting metabolite concentration change in association with participant Mini-Mental State Examination (MMSE) score. The plots were fitted with a linear regression model. Plots are shown for the metabolites in the serotonin and kynurenine pathways that reported significant differences between participant groups (Supplementary Figs. S
Univariate Mann-Whitney Metabolite comparison between mild cognitive impairment subgroups. Boxplots highlighting differences between metabolite concentrations in serum when comparing two subgroups of participants with a baseline clinical diagnosis of mild cognitive impairment (MCI). The first group (blue) remained cognitively stable throughout follow-up study visits (stable MCI (sMCI)), whilst the second group (yellow) experienced a deterioration in cognition and converted to a clinical diagnosis of AD at follow-up (converting MCI (cMCI)). Boxplots are only presented for the metabolites in the serotonin and kynurenine pathways that reported significant differences between control, MCI and AD participant groups in phases 1 and 2 of the study (Supplementary Figs. S
Pearson correlation analysis comparing the metabolites across the two biofluids reported a positive correlation between urine and serum levels of tryptophan ( Metabolite associations across biofluids. Scatter plots fitted with a linear regression describing the correlation between significant serum and urine metabolites. Correlations were calculated where both biofluids from a single individual were available. Significant positive correlations were observed for serum tryptophan/urine tryptophan, serum kynurenine/urine kynurenic acid, serum xanthurenic acid/urine xanthurenic acid and serum serotonin/urine 5-indoleacetic acid; however, serum serotonin/urine serotonin did not demonstrate a significant correlation
Study participants diagnosed with AD who were prescribed SSRI medication had significantly lower levels of serotonin than AD study participants with no reported SSRI intake ( Impact of selective serotonin reuptake inhibitor (SSRI) medication. Boxplots highlighting differences between study participants from the AD study group who had been prescribed SSRI medication and those who had not. There were no significant differences (analysis by Mann-Whitney
Significantly lower serum tryptophan, kynurenine and xanthurenic acid were found in participants clinically diagnosed with AD compared with controls, whilst serum xanthurenic acid demonstrated a significant positive correlation with participant MMSE cognitive scores.
Previous literature regarding tryptophan pathway metaboltes in AD contains conflicting results. Lower levels of tryptophan, xanthurenic acid, 3-hydroxyanthranilic acid [
In addition, the metabolites kynurenic acid and quinolinic acid have been reported to be significantly higher in the cerebrospinal fluid (CSF) of individuals clinically diagnosed with AD [
Previous literature has reported associations between quinolinic acid and Alzheimer’s disease pathology [
In urine, we also found significantly lower levels of tryptophan, xanthurenic acid and kynurenic acid, and urine xanthurenic acid demonstrated a significant positive correlation with participant MMSE cognitive scores. To the best of the authors’ knowledge, comparisons of urinary kynurenines in clinical cases of AD, MCI and controls have not been previously reported. The lower levels observed of the three urinary metabolites are consistent with our findings in serum.
Mechanistically, the rate limiting enzyme in the kynurenine metabolic pathway is indoleamine 2,3-dioxygenase (IDO)—a critical enzyme in systemic inflammation expressed by key cells of the immune system, including microglia [
Our data also found no significant differences when comparing metabolite concentrations between participant groups for NAD+ and its precursors nicotinic acid, nicotinic riboside and β-nicotinamide mononucleotide. NAD is a key functional metabolite in cellular metabolism and has been hypothesised as playing a role in the disrupted energy metabolism pathways that occur in AD [
A consequence of lower tryptophan bioavailability and an increase IDO enzyme activity is a reduced capacity for serotonin biosynthesis. This is reflected in our results, with lower levels of serotonin and 5-hydroxyindole acetic acid reported in the AD group.
Despite reports of lower amounts of serotonin in cerebrospinal fluid [
However, serotonin and serotonergic signalling have previously been proposed to be disrupted in AD [
In addition, selective serotonin reuptake inhibitors (SSRIs) are under investigation as therapeutic agents in AD. SSRIs work by increasing free serotonin at the synapse or neuronal cells resulting in increased levels of free serotonin available to synaptic receptors [
SSRIs are currently licenced for use in depression, and therefore, the study contained samples collected from participants who reported prescription of SSRI medication across all of the participant groups (Table
To assess the impact of SSRI on the overall result of the study, univariate analysis was repeated only with the participants who did not take SSRI medication. In the re-analysis, serum serotonin no longer reported significant differences between AD and control groups (Table S
Tryptophan is the parent metabolite in both the serotonin and kynurenine pathways, and therefore, its bioavailability may have a downstream effect on the resultant bioavailability of key neuroactive metabolites in the circulatory system (Fig. Tryptophan pathway. Pathway map presenting the key metabolites that reported significant inter-group differences following Kruskal-Wallis tests. Post hoc Dunn tests revealed that those highlighted with red shading were significantly lower in the AD group in serum, whilst those highlighted with blue shading were significantly lower in AD in urine. The downstream metabolites are inherently more polar and are therefore fit with biological and metabolic logic that polar, downstream metabolites would be renally excreted and therefore altered in urine
As tryptophan is an essential amino acid that cannot be synthesised in mammalian systems, the bioavailability of circulatory free tryptophan is primarily influenced by the consumption of protein in the diet combined with the rate of usage in protein synthesis and the ability to absorb amino acids through the intestinal wall. In AD, the impact on bioavailability of essential amino acids is highly complex and multifactorial. Changes in appetite are well documented in AD with many occurrences of eating disturbances reported varying between both the loss and increase of appetite, as well as changes in dietary preference [
The bioavailability of tryptophan is also known to be controlled by the population and diversity of an individual’s gut microbiome [
Research investigating alterations in the composition of the gut microbiome of individuals with AD have suggested that they have differences in the prevalence of Firmicutes, Bifidobacteria and Bacteroidetes compared with controls [
Here, we report significantly lower concentrations of tryptophan with downstream ramifications for the kynurenine and serotonin pathways in individuals clinically diagnosed with AD. Lower concentrations of metabolites involved in tryptophan metabolism were observed in both the urine and serum of participants and, in general, showed a declining trend for MCI. The results reported are based on the analysis of the largest cohort study to date that has investigated tryptophan metabolism in AD. Furthermore, the tryptophan-serotonin pathway may represent an easily modifiable pathway for influencing and managing the progression of AD and alleviating serotonergic signalling disruption in AD.
Future studies that are designed to investigate associations of tryptophan metabolism pathways with additional pathological markers of AD and cognitive decline, that were unavailable for the samples used in this study (e.g. cerebral amyloid load and/or emerging circulatory blood biomarkers such as p-tau 181 [
Not applicable
CLQ, SL, JKN and EH set-up and oversaw the multi-centre collaboration. LW and EH led and designed this specific study. KC, MRL and BJ oversaw, acquired and pre-processed the raw data. LW performed the data analysis and manuscript preparation. SL, HS, IK, PM, MT and BV oversaw the sample collection and biobanking in the AddNeuroMed and DCR local centres. EDH, SGS, AH and CLQ collated the samples and corresponding clinical data prior to data acquisition. JRS, SL, EH and LW contributed to the biological interpretation of the data. All authors reviewed the manuscript and agreed to its submission.
Not applicable
The UK Dementia Research Institute (DRI) is an initiative funded by the Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. AddNeuroMed (ANM) was supported by InnoMed (Innovative Medicines in Europe), an integrated project funded by the European Union of the sixth framework priority (FP6-2004-LIFESCIHEALTH). We acknowledge support for the Dementia Case Register (DCR) and for all sample management from the NIHR Biomedical Research Centre hosted at Kings College London and the South London and Maudsley NHS Foundation Trust and funded by the National Institute for Health Research under its Biomedical Research Centres initiative. The National Phenome Centre (NPC) is supported by the Medical Research Council and National Institute for Health Research [grant number MC_PC_12025]. Infrastructure support was provided by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health or other funders.
All data generated or analysed during this study are included in this published article [and its supplementary information files].
The AddNeuroMed and Dementia Case Register study was approved by ethical review boards in each participating country (local ethical review board at University of Perugia, University of Toulouse, Aristotle University of Thessaloniki, Medical University of Lodz, University of Eastern Finland and University Hospital of Kuopio and King’s College London).
Not applicable
The authors declare that they have no competing interests.
Alzheimer’s disease
Indoleamine 2,3-dioxygenase
Mild cognitive impairment
Selective serotonin reuptake inhibitor
Tryptophan 2,3-dioxygenase
Dementia Case Register
Stable MCI
Converting MCI
Ultra-high-performance liquid chromatography quadrupole-time-of-flight mass spectrometry
Proton nuclear magnetic resonance
Ultra-high-performance liquid chromatography tandem mass spectrometry
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