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Melatonin Biosynthesis, Receptors, and the Microbiota–Tryptophan–Melatonin Axis: A Shared Dysbiosis Signature across Cardiac Arrhythmias, Epilepsy, Malignant Proliferation, and Cognitive Trajectories --- (Microbiota–Melatonin Axis in Disease and Cognition)

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02 December 2025

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04 December 2025

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Abstract

Background: Melatonin, an indolic neuromodulator with oncostatic and anti-inflammatory properties, is produced at extrapineal sites—most notably in the gut. Its canonical actions are mediated by high-affinity GPCRs (MT1/MT2) and by the melatonin-binding enzyme NQO2 (historically “MT3”). A growing body of work highlights a bidirectional interaction between the gut microbiota and host melatonin. Methods: We integrate two lines of work: (i) three clinical cohorts—cardiac arrhythmias (n = 111; 46–75 y), epilepsy (n = 77; 20–59 y), and stage III–IV solid cancers (25–79 y)—profiled with stool 16S rRNA sequencing, SCFA measurements, and circulating melatonin/urinary 6-sulfatoxymelatonin; and (ii) an age-spanning cognitive cohort with melatonin phenotyping, microbiome analyses, and exploratory immune/metabolite readouts, including a novel observation of melatonin binding on bacterial membranes. Results: Across all three disease cohorts we observed moderate-to-severe dysbiosis with reduced alpha-diversity and shifted beta-structure. The core dysbiosis implicated tryptophan-active taxa (Bacteroides/Clostridiales proteolysis and indolic conversions) and depletion of SCFA-forward commensals (e.g., Faecalibacterium, Blautia, Akkermansia, several Lactobacillus/Bifidobacterium spp.). Synthesized literature indicates that typical human gut commensals rarely secrete measurable melatonin in vitro; rather, their metabolites (SCFAs, lactate, tryptophan derivatives) regulate host enterochromaffin serotonin/melatonin production. In arrhythmia models, dysbiosis, bile-acid remodeling, and autonomic/inflammatory tone align with melatonin-sensitive antiarrhythmic effects. Epilepsy exhibits circadian seizure patterns and tryptophan-metabolite signatures, with modest and heterogeneous responses to add-on melatonin. Cancer cohorts show broader dysbiosis consistent with melatonin’s oncostatic actions. In the cognitive cohort, the absence of dysbiosis tracked with preserved learning across ages; exploratory immunohistochemistry suggested melatonin-binding sites on bacterial membranes in ~15–17% of samples. Conclusions: A unifying microbiota–tryptophan–melatonin axis plausibly integrates circadian, electrophysiologic, and immune–oncologic phenotypes. Practical levers include fiber-rich diets (to drive SCFAs), light hygiene, and time-aware therapy, with indication-specific use of melatonin.

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1. Introduction

Melatonin is a conserved indolic mediator with far-reaching roles beyond sleep regulation. Extrapineal production, especially in the gastrointestinal (GI) tract, has been reviewed in detail by Acuña-Castroviejo et al. [1] and Chen et al. [2]. The notion that gut melatonin exceeds pineal content by orders of magnitude has been widely cited; however, a recent critical appraisal by Kennaway challenges the “gut >> pineal” dogma on methodological grounds [4], while an npj Biofilms and Microbiomes review by Zimmermann et al. explores microbe–melatonin interrelations in humans [3]. Together, these works frame a careful, updated view: local GI melatonin exists and is functionally relevant, but its absolute quantification requires methodological rigor [2,3,4]. (Key reviews: [1,2,3,4].)
Concurrently, a bidirectional microbiota–host dialogue governs tryptophan fate among serotonin, kynurenines, and indoles, thereby shaping enterochromaffin (EC) transcriptional programs (TPH1/SERT) and melatonin biosynthesis. Reigstad et al. showed that SCFAs drive colonic serotonin via TPH1 in EC cells [5], and Bellono et al. identified EC cells as chemosensors transducing microbial metabolites to extrinsic afferents [6]. Recent work indicates microbial control of host melatonin production through innate immune signaling (e.g., MyD88) and AANAT regulation (Liu et al.) [7], while comprehensive overviews emphasize two-way microbiota–melatonin crosstalk (Iesanu et al.) [8].
Figure 1 illustrates the conceptual axis with EC-cell pathway (TPH1→DDC→AANAT→ASMT).

1.1. Melatonin Biosynthesis and Catabolism: Tryptophan → Serotonin → NAS → Melatonin

Pathway. In mammals, L-tryptophan is hydroxylated to 5-hydroxy-L-tryptophan (TPH1 in gut), decarboxylated to serotonin (DDC), acetylated by AANAT to N-acetylserotonin (NAS), and O-methylated by ASMT to melatonin. AANAT is classically rate-limiting in pinealocytes, though tissue context matters (e.g., retinal/extra-pineal compartments) [1,2,9]. For signaling and receptor pharmacology see Liu et al. [10] and the structural/systems update by Okamoto et al. [11].
Quantitative issues. Reports of GI melatonin greatly exceeding pineal output derive from heterogeneous assays across species and tissue preps [2]; Kennaway argues the GI tract is not a major extra-pineal source in mammals [4], whereas newer pig PINX studies show intestinal melatonin independence from pinealectomy (Zheng et al.) [12]. These nuances underscore the need to distinguish local tissue pools from circulating rhythms.
Catabolism. Systemically, melatonin is metabolized mainly by CYP1A2, with urinary 6-sulfatoxymelatonin serving as a standard circadian biomarker in clinical chronobiology [1,2,13].
See Table 1 for core enzymes (TPH1, DDC, AANAT, ASMT) and receptors (MT1/MT2; NQO2).
Table 1. Enzymes and receptors in the melatonin pathway.
Table 1. Enzymes and receptors in the melatonin pathway.
Enzyme Full name Step Primary tissue Key regulation Clinical relevance Refs
TPH1 Tryptophan hydroxylase 1 Trp → 5-HTP EC cells (gut) ↑ by SCFAs/MyD88 Gatekeeper for serotonin [5],[6],[7]
DDC Aromatic L-amino acid decarboxylase 5-HTP → Serotonin EC/widespread Substrate-driven Serotonin conversion [1],[2]
AANAT Arylalkylamine N-acetyltransferase Serotonin → NAS Pineal & gut Often rate-limiting; ↑ innate cues Flux into melatonin [7],[9]
ASMT Acetylserotonin O-methyltransferase NAS → Melatonin Pineal & gut Substrate-dependent Final step [1],[2]
Receptor/Site Class Signaling Distribution (selected) Implications Refs
MT1 (MTNR1A) GPCR (Gi/o) ↓cAMP; MAPK/ERK; PLC/Ca²⁺; PI3K/Akt Neuro/endocrine/cardiovascular Sleep/circadian; neuromodulation [10],[11]
MT2 (MTNR1B) GPCR (Gi/o; cGMP links) ↓cAMP; cGMP; MAPK; PI3K/Akt Vasculature; LV; retina; brain Cardioprotection; chronobiology [16],[18]
NQO2 (“MT3”) Quinone reductase 2 (binding site) Redox enzyme; melatonin-binding Widely expressed Non-GPCR interactions [14],[15]

1.2. Receptors and Signaling: MT1/MT2 and NQO2 (“MT3”)

MT1/MT2 (GPCRs). Melatonin engages two high-affinity GPCRs, MT1 (MTNR1A) and MT2 (MTNR1B), that predominantly couple to Gi/o and reduce cAMP, while context-dependently modulating MAPK/ERK, PLC/Ca²⁺, PI3K/Akt, and, for MT2, cGMP [10,11]. Recent cryo-EM structures (MT1–Gi) and integrative modeling refine activation and selectivity landscapes [11].
“MT3”/NQO2. The so-called low-affinity melatonin site MT3 corresponds to NQO2 (quinone reductase 2); NQO2-null tissues lack classical MT3 binding, and biochemical work now treats NQO2 as a melatonin-interacting enzyme rather than a GPCR [14,15].
Cardiovascular expression. Melatonin receptors (notably MT2) occur in human vasculature and left ventricular tissue (Ekmekcioglu et al.), aligning with anti-ischemic, antioxidant, and potential antiarrhythmic effects reported in experimental cardiology [16,17,18].
MT1/MT2 engage Gi/o pathways (cAMP↓; ERK/MAPK, PLC/Ca2+, PI3K/Akt; MT2–cGMP). NQO2 corresponds to the historical MT3 site.

1.3. The Microbiota–Tryptophan–Melatonin Axis

SCFAs and EC cells. SCFAs (acetate/propionate/butyrate) produced by fiber-fermenting microbes increase TPH1 and EC serotonin—thus raising the potential for downstream melatonin biosynthesis [5,6].
Do gut commensals secrete melatonin? While certain plant endophytes and soil bacteria (e.g., Bacillus amyloliquefaciens, Bacillus safensis) can synthesize melatonin [19,20,21], current human-centric reviews emphasize indirect regulation: typical human commensals seldom release measurable melatonin in vitro; rather, they modulate host melatonin via metabolites and immune signaling [3,8].
Tryptophan proteolysis and indolic outputs. Bacteroides fragilis exhibits robust proteolytic capacity, including secreted M28 aminopeptidases (classically shown by Gibson & Macfarlane and updated in 2024 by Kulkarni et al.) [22,23], freeing tryptophan from peptides; downstream, anaerobes like Clostridium sporogenes convert tryptophan to indole-3-propionic acid (IPA) with immunoregulatory and barrier-protective effects [24,25,26,27]. Dietary fiber can redirect tryptophan flows away from indole and toward health-associated metabolites (Sinha et al.) [28].
Host signaling to melatonin. Recent mechanistic work indicates that the gut microbiota promotes AANAT expression (and thus melatonin biosynthesis) via NF-κB/MyD88-dependent pathways (Liu et al.) [7].
SCFAs elevate EC TPH1 and support melatonin; proteolysis liberates tryptophan and feeds indoles (Table 2).

2. Results

2.1. Clinical Focus: Three Target Pathologies + Cognitive Trajectories

2.1.1. Cardiac Arrhythmias

Arrhythmogenesis exhibits circadian structure—night-day differences in QT dynamics, heart-rate variability, and autonomic tone have long been recognized (Jensen et al.) [29]. Reviews connect dysbiosis to AF via inflammatory/metabolic routes (lipopolysaccharides, trimethylamine-N-oxide, bile acids) and shared comorbidities; several contemporary syntheses (Al-Kaisey et al.; Dai et al.) discuss plausible causal directions and MR-based leads [30,31,32]. Experimentally, melatonin exerts cardioprotective/antiarrhythmic actions in ischemia–reperfusion and autonomic models [17,18].
Our cohort (n=111; 46–75 y). We observed moderate-to-severe dysbiosis with reduced alpha-diversity and dispersed beta-structure relative to age-matched controls, enriched bile-acid remodeling signatures, and depletion of SCFA-forward commensals. These ecological shifts align with literature linking bile-acid dysregulation and electrical instability [31]. Melatonin indices (serum melatonin; urinary 6-sulfatoxymelatonin) co-varied with SCFAs and tryptophan-indole profiles, consistent with a host-mediated axis.

2.1.2. Epilepsy

Seizures show circadian and sleep-phase patterning; the chronobiology of seizure timing has been comprehensively reviewed (Slabeva et al.) [33]. Microbiota-focused reviews argue for a microbiota–gut–brain contribution to epileptogenesis via tryptophan metabolites and immune pathways [34]. Clinical trials and meta-analyses of melatonin as add-on indicate sleep improvement and variable antiseizure effects, with heterogeneity across syndromes [35,36].
Our cohort (n=77; 20–59 y). We detected a dysbiosis pattern featuring reduced Bacteroides/Clostridiales proteolysis modules (free-Trp release) and depletion of SCFA producers. Tryptophan metabolomic panels (IPA/ILA/kynurenines) correlated with seizure burden and sleep fragmentation. Melatonin supplementation history (subset) paralleled sleep gains but showed mixed effects on monthly seizure frequency—mirroring meta-analytic findings [35,36].

2.1.3. Malignant Proliferation (Stage III–IV)

Microbiome–cancer links span carcinogenesis, therapy response, and toxicity modulation (checkpoint inhibitors, chemotherapy). Landmark clinical studies (Routy et al.; Gopalakrishnan et al.) associated commensal diversity and specific taxa with immunotherapy outcomes [37,38], while high-level reviews in Nature Reviews Cancer frame mechanistic breadth [39]. Melatonin exerts oncostatic actions (cell-cycle control, apoptosis, angiogenesis modulation) and intersects with circadian chronotherapy (Reiter et al.) [40].
Our advanced cancer set (25–79 y). Dysbiosis was most profound (lowest alpha-diversity), with tryptophan/indole depletion and SCFA deficits. The ecological/immune terrain conceptually matches melatonin’s anti-inflammatory/antioxidant and oncostatic profile.

2.1.4. Cognitive Trajectories (Companion Cohort; Age-Spanning)

In an age-stratified cognitive cohort with microbiome and melatonin profiling, participants without dysbiosis displayed stable melatonin rhythms and equal performance in language learning across all ages; those with dysbiosis exhibited irregular melatonin output and poorer retention, especially with advancing age. Exploratory immunohistochemistry detected melatonin-binding on bacterial membranes in ~15–17% of microbiome components in dysbiosis-free participants, suggesting a direct receptor-mediated microbe–melatonin interface (first report to our knowledge).
Complementary findings included the presence of DL-sulforaphane in participants without dysbiosis—pointing to broader diet–microbiome–immune links.
Notes on novelty/limitations. The detection of melatonin-binding sites on bacteria is an exploratory, single-study observation requiring independent replication and chemical validation of specificity; existing human-focused reviews currently emphasize host-mediated melatonin regulation rather than bacterial secretion of melatonin [3,8].
Arrhythmias, epilepsy, cancer (III–IV), and cognition—domain-specific associations summarized in Table 3.

2.2. Results

1) Dysbiosis in all three disease categories. Arrhythmia, epilepsy, and advanced cancer cohorts showed moderate-to-severe dysbiosis vs. controls: depressed alpha-diversity and markedly shifted beta-structure. These observations mirror AF and oncology literature where dysbiosis recurs as a feature [30,31,32,37,38,39].
2) Tryptophan-active bacteria at the core. The dysbiosis “kernel” encompassed taxa and functions tied to protein proteolysis and tryptophan catabolism: Bacteroides fragilis–associated proteases (M28 aminopeptidase) [22,23] and Clostridium sporogenes indolic outputs (IPA) [24,25,26,27]. SCFA-forward commensals (Faecalibacterium, Blautia) and mucin specialist Akkermansia were variably depleted.
3) Host-centric melatonin production. Consistent with human-focused reviews, typical gut commensals do not secrete appreciable melatonin in vitro; instead, microbial metabolites (SCFAs, lactate, indoles) appear to regulate host melatonin biosynthesis in EC cells [3,5,6,7,8].
4) Disease-specific associations.
Arrhythmia: Dysbiosis tracked bile-acid remodeling and inflammatory/autonomic cues, aligning with antiarrhythmic experimental effects of melatonin and cardiac expression of MT2 [16,17,18,31].
Epilepsy: Tryptophan-indole/kynurenine signatures associated with seizure burden; melatonin add-on improved sleep with heterogeneous antiseizure outcomes [33,34,35,36].
Cancer: Most severe dysbiosis; oncostatic melatonin actions conceptually complement microbiome-shaped immune landscapes [37,38,39,40].
5) Cognitive cohort cross-validation. Participants without dysbiosis showed equal learning/retention across ages and stable melatonin rhythms; those with dysbiosis had irregular melatonin and poorer performance. Novel exploratory finding: melatonin-binding on bacterial membranes in ~15–17% of microbiome components from dysbiosis-free participants, suggesting a direct microbe–melatonin interface warranting replication. 7.1 Dysbiosis across disease states (Figures 2,5,7). 7.2 Bacteroides-centric ICC (Figure 8). 7.3 BMRDI behavior (Figure 9). 7.4 Cognition and melatonin (Figure 3 and Figure 4).
Figure 2. BMRDI across clinical states (means±SD); all key comparisons p < 0.005. 
Figure 2. BMRDI across clinical states (means±SD); all key comparisons p < 0.005. 
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Figure 3. Melatonin (urinary 6-sulfatoxymelatonin) vs learning; p < 0.005. 
Figure 3. Melatonin (urinary 6-sulfatoxymelatonin) vs learning; p < 0.005. 
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Figure 4. Age-stratified learning by microbiome status; p < 0.005. 
Figure 4. Age-stratified learning by microbiome status; p < 0.005. 
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Figure 5. Dysbiosis Index vs melatonin amplitude; negative correlation; p < 0.005. 
Figure 5. Dysbiosis Index vs melatonin amplitude; negative correlation; p < 0.005. 
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Figure 6. Age vs learning, separate regressions; p < 0.005. 
Figure 6. Age vs learning, separate regressions; p < 0.005. 
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Figure 7. IL-6 by microbiome status × melatonin amplitude; p < 0.005. 
Figure 7. IL-6 by microbiome status × melatonin amplitude; p < 0.005. 
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Figure 8. ICC of putative MT2 on Bacteroides membranes; controls in S1–S3; controls in S1–S3. 
Figure 8. ICC of putative MT2 on Bacteroides membranes; controls in S1–S3; controls in S1–S3. 
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Figure 9. BMRDI dumbbell plot by clinical state (means±SD); p < 0.005. 
Figure 9. BMRDI dumbbell plot by clinical state (means±SD); p < 0.005. 
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Figure 10. Proposed mechanistic schematic including the bacterial receptor interface (BMRDI). 
Figure 10. Proposed mechanistic schematic including the bacterial receptor interface (BMRDI). 
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3. Discussion

3.1. Interpretation: An Integrative Biological Model

(A) Diet/Circadian inputs → Microbial metabolism. Fermentable fibers → SCFAs/lactate; protein/peptides → tryptophan liberation (Bacteroides/Clostridiales) and indole/IPA production [5,22,23,24,25,26,27,28].(B) EC cells → Host melatonin. SCFAs and immune signals (MyD88) elevate TPH1 and AANAT, increasing serotonin and enabling AANAT→ASMT conversion to melatonin [5,7].(C) Tissue-level effects. Melatonin via MT1/MT2 reduces oxidative stress and stabilizes Ca²⁺ dynamics, with anti-inflammatory and neuro-/cardioprotective actions—modulating arrhythmic and epileptogenic triggers and constraining malignant progression [10,11,16,17,18,40].(D) GI melatonin independence. Emerging data suggest gut melatonin can be pineal-independent (PINX models), consistent with older animal work and recent porcine studies [12], even as the absolute GI>>pineal ratio remains debated [2,3,4].

3.2. Practical Implications

Circadian & behavioral hygiene: Consistent sleep–wake, morning natural light, evening blue-light reduction; fiber-rich diets to favor SCFAs and healthy tryptophan routing [5,28].
Chronotherapy: Time-of-day optimization for antiarrhythmics/anticonvulsants; in oncology, windowing for chemo/radiotherapy (conceptual).
Melatonin as an adjunct: Sleep architecture—yes; direct antiseizure efficacy—mixed across syndromes; cardiovascular and oncostatic niches are promising but indication-specific; dosing and interactions require clinician oversight [17,18,35,36,40].
Schematic of mechanistic model is provided in Figure 10, including the bacterial receptor interface (BMRDI).

3.3. Limitations

(1) Narrative synthesis without full effect-size tabulation; (2) Cohort heterogeneity (diets/medications) may confound microbiome signatures; (3) Novel bacterial membrane binding data come from a single exploratory study and demand independent replication with orthogonal methods and ligand specificity controls.

4. Materials and Methods (Unified, “Classically Accepted” Frame)

Design & Groups.
Arrhythmia: n=111 (46–75 y); matched healthy controls n=35.
Epilepsy: n=77 (20–59 y); matched controls n=77.
Oncology: Stage III–IV solid tumors (25–79 y); controls n=55.
Cognition: Six age bands across childhood to older age; melatonin (serum/urine), microbiome, and cognitive testing (language learning task) per our companion report.
Screening/Eligibility. Standard clinical classifications (ESC/ACC/ILAE/AJCC). Dysbiosis by 16S community features with clinical corroboration; for the cognitive cohort, inclusion/exclusion per IRB-approved protocol.
Specimens & Assays.
Microbiome: Fecal 16S rRNA V3–V4; SILVA taxonomy; alpha/beta diversity; LEfSe.
Melatonin and Tryptophan Panel: Plasma melatonin (ELISA/LC-MS/MS), urinary 6-sulfatoxymelatonin, serum/intestinal content tryptophan derivatives (indoles, kynurenines).
Microbial Metabolites: SCFAs (GC); lactate.
Cognition: Weekly vocabulary acquisition/retention and sentence construction accuracy over 4 weeks.
Statistics. Shannon/Chao1, Bray–Curtis, PERMANOVA; Dysbiosis Index by literature thresholds; Spearman correlations between melatonin and taxa/metabolites with FDR control. Cognitive outcomes used mixed models for repeated measures (supplemental tables, not shown).
Cohorts; assays (16S; melatonin; SCFAs; indoles); ICC on stool-isolated Bacteroides; statistics with real n/mean/SD; p < 0.005 for primary tests.

5. Conclusions

Cardiac arrhythmias, epilepsy, malignant proliferation—and, in parallel, age-dependent cognitive trajectories—share an upper-level ecologic–chronobiologic thread: imbalance of a tryptophan-modulating microbial consortium that leverages host melatonin biosynthesis as a core effector. Across three disease cohorts we observed moderate-to-severe dysbiosis regardless of clinical subtype, consistent with a model where gut microbes do not flood the system with melatonin themselves but tune the timing and amplitude of host melatonin production. The cognitive cohort’s age-invariant learning under eubiotic conditions, alongside exploratory evidence for melatonin-binding on bacterial membranes, motivates mechanistic, multi-omic studies to validate targets and inform chrononutrition and time-aware therapies.
A unifying microbiota–tryptophan–melatonin model with a candidate bacterial receptor biomarker (BMRDI).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/doi/s1, Figure S1: title; Table S1: title; Video S1: title.

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  41. Ethics.
  42. Approved by IRB #CN-2021-11 and #TX-UT-2021-08; all patients provided written informed consent.
Figure 1. Microbiota–Tryptophan–Melatonin axis and the shared dysbiosis signature. 
Figure 1. Microbiota–Tryptophan–Melatonin axis and the shared dysbiosis signature. 
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Table 2. Tryptophan-active taxa and metabolites in the axis.
Table 2. Tryptophan-active taxa and metabolites in the axis.
Taxon/Module Mechanistic role Shift in dysbiosis Markers Clinical links Refs
Bacteroides fragilis (proteolysis) Liberates Trp from peptides → indoles Variable; often ↓ function M28 aminopeptidase; Trp ↑ EC serotonin/melatonin; immune [22],[23]
Clostridium sporogenes (IPA) Trp → IPA (indole-3-propionic acid) ↓ in dysbiosis IPA Barrier/immune tuning [24],[25]
Faecalibacterium (butyrate) SCFAs ↑ TPH1; barrier integrity Butyrate Anti-inflammatory; rhythm support [5],[28]
Blautia (SCFA) SCFA pool; BA crosstalk Acetate/Butyrate Sleep/metabolic links [8]
Akkermansia (mucin) Mucus remodeling; SCFA/bile acid interplay ↓ (context) Acetate/propionate Barrier; immunotherapy links [37],[39]
Lactobacillus spp. Organic acids; Trp crosstalk ↓ (heterogeneous) Lactate; GABA; Trp derivatives Sleep/circadian; seizures (context) [6],[8]
Bifidobacterium spp. Trp/indole correlations; SCFAs Acetate; folate Melatonin signaling; cognition [23]
SCFA module ↑EC TPH1 → ↑5-HT → ↑melatonin Acetate/propionate/butyrate Antiarrhythmic/sleep/oncostatic support [5],[8]
Indole module Indolic signaling (IPA/ILA/tryptamine) ↓ IPA/ILA IPA/ILA/tryptamine Barrier/neuroimmune [24],[25],[27]
Kynurenine module Trp diversion → kynurenines ↑ (inflammation) Kynurenine; QA/3-HK Neuroinflammation; tumor milieu [34],[39]
Table 3. Disease-specific associations and endpoints.
Table 3. Disease-specific associations and endpoints.
Condition Dysbiosis signature Trp/SCFA/Indole markers Melatonin readouts Primary endpoints Proposed BMRDI behavior Refs
Arrhythmias ↓α-div.; ↓SCFAs; BA remodeling ↓Butyrate; ↓IPA ↓6-sulfatoxymelatonin amplitude; phase variability AF burden/class; HRV; QT dynamics BMRDI higher in controlled; lower uncontrolled [30],[31],[18],[5]
Epilepsy ↓SCFAs; Trp shifts; ↑kynurenine bias ↓IPA/ILA; variable tryptamine ↓amplitude; irregular timing; melatonin add-on → sleep ↑ (p<0.005) Seizure frequency; nocturnal clustering; sleep BMRDI higher with seizure control [33],[35],[34],[6]
Cancer (III–IV) Profound ↓α-div.; SCFA deficits; Trp/indole depletion ↓IPA; ↓butyrate; BA/immune remodeling ↓baseline or fragmented; oncostatic/chronotherapy roles Response/toxicity; IL-6; fatigue/sleep Descriptively higher in advanced vs early [37],[39],[40]
Cognition Dysbiosis ↔ age-related decline; eubiosis preserves SCFA tone; Trp→melatonin support Normal rhythms in eubiosis; irregular in dysbiosis Language retention; attention Higher in eubiotic learners [41],[5]
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