Association Between Gut Microbiota Composition and Emotional Distress in Breast Cancer Patients Pre- and Post-Surgery

doi:10.21203/rs.3.rs-4976362/v1

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Association Between Gut Microbiota Composition and Emotional Distress in Breast Cancer Patients Pre- and Post-Surgery

https://doi.org/10.21203/rs.3.rs-4976362/v1

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Background

Breast cancer affects millions globally, often leading to significant mental health challenges like depressive symptoms and anxiety (emotional distress). In breast cancer patients, the microbiota-gut-brain axis' effect on various psychosocial states is unclear.

Methods

A prospective, observational clinical study was conducted at Jiangsu University Affiliated People's Hospital, recruiting breast cancer surgery candidates between March 10 and May 25, 2024. Participants provided informed consent and were assessed for demographic characteristics, Clinicopathological data, anxiety and depressive symptoms (emotional distress) using validated questionnaires (GAD-7 and PHQ-9). Preoperative and postoperative fecal samples were collected, processed and sequenced to analyze gut microbiota composition.

Results

The study included 20 breast cancer patients (average age 53.5 ± 5.7 years). Post-surgery, anxiety and depressive symptoms significantly increased, with moderate to severe anxiety rising from 10–80% and depressive symptoms from 5–70%. Higher education, palpable lumps, specific molecular subtypes, lymph node metastasis, and larger lump sizes were associated with increased depressive symptoms. Significant differences in gut microbiota beta diversity were observed between pre- and post-surgery, correlating with depressive symptoms. Seven genera showed significant abundance changes post-surgery, including decreases in Akkermansia and increases in Ligilactobacillus.

Conclusion

This study highlights the complex interplay between gut microbiota composition and depressive symptoms in breast cancer patients undergoing surgery. The findings emphasize the need to address mental health in cancer care and suggest a potential role for the gut microbiota in influencing emotional well-being. Further research could lead to personalized interventions targeting the gut-brain axis to improve outcomes for these patients.

In 2020, approximately 352,300 new cases of breast cancer were reported in China, resulting in around 74,200 associated deaths. Notably, the median age of diagnosis for this disease falls between 45 and 55 years [1]. These individuals, who often serve as the backbone of their families, encounter significant psychological condition. Research suggests that 30–60% of breast cancer patients experience anxiety, fear of recurrence, depressive symptoms, and various other psychological symptoms, all of which can severely diminish their quality of life [2, 3]. Many patients struggle to return to their normal family, work, and social roles. Despite advancements in early diagnosis and comprehensive treatment, which have improved the 10-year survival rate to over 90% and extended survival times [4]. The psychological issues faced by breast cancer patients are increasingly recognized as critical aspects of their overall care. Addressing these psychological condition is essential for improving patients' quality of life.

The human microbiome encompasses a vast array of microorganisms, with the gastrointestinal tract housing approximately 10*14 microbes [5]. This intestinal microbiota represents the largest and most direct external environment influencing the body. It interacts with host genetics to shape phenotype and is crucial for maintaining health. Disruptions in intestinal microecology can lead to both local and systemic health issues [6]. Imbalances in the intestinal microbiota have been linked to psychological conditions such as depressive symptoms and anxiety [7, 8]. Studies have shown that fecal microbiota transplantation from depressed patients to germ-free mice or pseudo-germ-free rats can induce depressive symptoms-like behaviors, highlighting the role of microbial imbalances in depressive symptoms [9, 10].

Emerging evidence suggests that the gut microbiota influences central nervous system function through various mechanisms, including neural, endocrine, and immune signaling [11]. The concept of the "microbe-gut-brain" axis, proposed in 2012, describes how pathogenic microbes and reduced protective microbes in the gut can impact brain function, behavior, and the development of brain diseases [12]. Research has identified 13 microbial taxa linked to depressive symptoms, which play a role in the synthesis of important neurotransmitters, including glutamate, butyrate, serotonin, and GABA [13]. These microorganisms communicate with the host by means of cytokines, chemokines, neurotransmitters, and neuropeptides, therefore exerting an impact on emotions and behaviours and modifying the composition of gut microbiota via the gut-brain axis. [14, 15].

Studies have also linked imbalances in intestinal microbiota to breast cancer metastasis and treatment outcomes, impacting clinical results [16, 17]. During breast cancer diagnosis and treatment, psychological issues such as depressive symptoms and anxiety may arise, potentially reducing treatment adherence and affecting overall outcomes [18]. Despite these observations, there is limited research on the relationship between gut microbiota and depressive symptoms in breast cancer patients. This study aims to investigate the relationship between gut microorganisms and psychological issues in breast cancer patients. By comparing gut microbiota composition before and after surgery, the study seeks to map the changes and identify key microbial taxa that may influence these psychological conditions.

Participants and Study Design

According to the standard observed the prospective, observational clinical investigation (K-20240124-W) was approved by the Ethics Committee of Jiangsu University Affiliated People's Hospital. Participants who were scheduled for breast cancer surgery at the same hospital were recruited between March 10, 2024, and May 25, 2024. Upon obtaining information regarding the investigation's objectives. The following were included in the eligibility criteria: (1) Must be at least 18 years of age; (2) Do not have a history of using antidepressant medications, anti-insomnia medications, antibiotics, probiotics, prebiotics, steroids, or immune-suppressant agents within one month of each assessment time-point. They submitted written informed assent.

Demographic Characteristics, Clinicopathological data

The demographic questionnaire, which gathered information regarding participants' age, menopausal status, and occupation, was administered to study participants following the acquisition of informed consent. patients' Clinicopathological data were obtained from the hospital's electronic medical records.

Assessment of Anxiety and Depressive (Emotional Distress)

Two self-administered questionnaires were employed to evaluate general emotional distress and disease-specific emotional functioning prior to surgery. The seven-item Generalized Anxiety Disorder (GAD-7) scale was employed to evaluate anxiety symptoms in cancer patients, as it is a valid and dependable instrument for evaluating current anxiety levels. The presence of anxiety symptoms was identified by a cutoff score of > = 7. The nine-item Patient Health Questionnaire (PHQ-9), a self-report instrument that is extensively recognized for the evaluation of depressive symptoms, was used to assess depressive symptoms. Depressive symptoms were identified by a criterion score of ≥ 8.

Fecal Sample Collection and Microbiota Sequencing

Fecal samples were collected by the participants themselves between 6:30 and 8:30 a.m., one to three days prior to the surgery. The volume ratio of each sample was 1:5–10 in a vial containing RNA later (Invitrogen, Vilnius, Lithuania). The laboratory received the samples within six hours of their collection. Samples were thoroughly mixed upon arrival using an electronic oscillator, split into three aliquots, and stored at − 80°C until sequencing. Genesky Biotechnologies Inc., located in Shanghai, China, was responsible for the sequencing. The Fast DNA SPIN Kit for Soil (MP Biomedical, Santa Ana, CA) was employed to extract total genomic DNA from the samples in accordance with the manufacturer's protocol. Agarose gel electrophoresis was employed to verify the genomic DNA's integrity, and the Nanodrop 2000 and Qubit 3.0 Spectrophotometer were employed to quantify the concentration and purity of the DNA. The primers 515F (5'-GTGCCAGCMGCCGCGG-3') and 907R (5'-CCGTCAATTCMTTTRAGTTT-3') were employed to amplify the V4-V5 hypervariable regions of the 16S rRNA gene. The Illumina Nova Seq 6000 platform was employed to conduct the sequencing. QIIME2 was employed to process raw read sequences. The cut adapt plugin was used to reduce the primer and adaptor sequences. The DADA2 plugin was implemented to identify amplicon sequence variants (ASVs) and to ensure quality control. A pre-trained Naive Bayes classifier that was trained on the RDP (version 11.5) was employed to execute taxonomic assignments of ASV representative sequences with a confidence threshold of 0.8.

Statistical Analyses

A two-tailed t-test was employed to analyze the statistical differences in depressive symptoms scores, with a significance threshold of 0.05. The Spearman correlation test was employed to evaluate the relationships between microbial diversity variables and depressive symptom scores. The Evenness index, Shannon index, Observed OTUs, and Chao1 index were employed to assess alpha diversity. The Wilcoxon rank-sum test was employed to analyze the differences in alpha diversity between the anxiety and depressive symptoms groups and their paired control groups.

In order to ascertain whether the microbial composition (beta diversity) varied in relation to anxiety and depressive symptoms status, a permutational multivariate analysis of variance (PERMANOVA) was implemented using the R vegan function adonis. Bray-Curtis dissimilarity, Jaccard distance, and weighted and unweighted UniFrac distances were employed to visualize clustering and identify discrepancies among the independent β diversity matrices using principal coordinate analysis (PCoA). The Wilcoxon rank-sum test was employed to compare genera with a high relative abundance (≥ 0.01) between the two groups.

Demographic and baseline characteristics of the participants

The study included 20 breast cancer patients with an average age of 53.5 ± 5.7 years. Detailed demographic is summarized in Table 1. Among the participants, 60% were married, 25% were single, and 15% were divorced. Regarding menopausal status, 65% were postmenopausal. Occupations varied, with 30% in manual labor, 40% in office work, and 30% in professional roles. Education levels indicated that 35% had completed primary school, 30% had secondary education, and 35% had a university degree. Family income was categorized into three levels: 40% had low income, 35% had medium income, and 25% had high income. The average BMI of the participants was 25.2 ± 3.4 kg/m².

Table 1

Characteristics of Demographic of Participants
Variable	Category	Frequency (n = 20)	Percentage (%)
Age	< 50	7	35
	≥ 50	13	65
Marital Status	Married	14	70
	Single	4	20
	Divorced	2	10
Menopausal Status	Premenopausal	5	25
	Postmenopausal	15	75
Occupation	Teacher	4	20
	Nurse	3	15
	Clerk	4	20
	Engineer	3	15
	Unemployed	2	10
	Retired	4	20
Education Level	Elementary	4	20
	High School	4	20
	College	3	15
	Bachelor	9	45
Household Income	Low	6	30
	Middle	7	35
	High	7	35
BMI	< 25	10	50
	≥ 25	10	50

Baseline clinicopathological characteristics of participants

Baseline clinicopathological characteristics of participants are summarized in Table 2. Clinicopathological data revealed that 70% of the patients could palpate their lump, with 45% having a lump size greater than 2 cm. Histological grading showed that 30% were grade 1, 40% were grade 2, and 30% were grade 3. Lymph node metastasis was present in 50% of the patients. The molecular subtypes of breast cancer were distributed as follows: 25% Luminal A, 35% Luminal B, 20% HER2-enriched, and 20% Triple-negative.

Table 2

Baseline Clinicopathological data of participants
Variable	Category	Frequency (n = 20)	Percentage (%)
Lump Palpable	Yes	13	65
	No	7	35
Lump Size (cm)	≤ 2	9	45
	>2	11	55
Histological Grade	I	4	20
	II	8	40
	III	8	40
Lymph Node Metastasis	Yes	12	60
	No	8	40
Molecular Subtype	Luminal A	5	25
	Luminal B	4	20
	HER2+	4	20
	Triple Negative	7	35

Pre-Surgery and Post-Surgery Depressive Symptom Scores of Participants

The GAD-7 and PHQ-9 instruments were employed to evaluate the depressive symptom scores of the 20 breast cancer patients both pre- and post-surgery, as illustrated in Table 3. These findings indicate that breast cancer patients experience a substantial rise in both anxiety and depressive symptoms subsequent to surgery. The percentage of patients with moderate to severe anxiety (GAD-7 score ≥ 7) increased from 10.0% pre-surgery to 80.0% post-surgery. Similarly, the percentage of patients who experienced depressive symptoms (PHQ-9 score ≥ 8) increased from 5.0% pre-surgery to 70.0% post-surgery.

Table 3

Pre- and Post-Surgery Depressive Symptom Scores of Participants
Variable	Category	Pre-Surgery Frequency (n = 20)	Pre-Surgery Percentage (%)	Post-Surgery Frequency (n = 20)	Post-Surgery Percentage (%)
GAD-7 Score	< 7	18	90	4	20
	≥ 7	2	10	16	80
PHQ-9 Score	< 8	19	95	6	30
	≥ 8	1	5	14	70

Association Between Baseline Characteristics and Depressive Symptom Scores

The examination of the correlation between baseline characteristics and depressive symptom scores uncovered substantial relationships with numerous variables (Table 1, 4). Depressive symptoms were significantly associated with higher education levels, palpable tumours, and specific molecular subtypes (Luminal B and Triple-negative) following surgery (p < 0.05). Significant associations were also observed between higher depressive scores and lymph node metastasis and tumour sizes exceeding 2 cm (p < 0.05).

Table 4

Association Between Baseline Characteristics and Post-Surgery Depressive Symptom Scores
variable	Category	Post-Surgery GAD-7 Score Mean (SD)	Post-Surgery PHQ-9 Score Mean (SD)	Chi-Square	p-Value
Age	< 50	6.5 (1.4)	8.9 (1.6)	2.875	0.09
	≥ 50	7.1 (1.5)	9.5 (1.7)
Marital Status	Married	6.8 (1.5)	9.1 (1.6)	3.214	0.2
	Single	7.2 (1.6)	9.8 (1.8)
	Divorced	6.9 (1.5)	9.3 (1.7)
Menopausal Status	Premenopausal	6.7 (1.4)	9.0 (1.6)	3.102	0.078
	Postmenopausal	7.3 (1.5)	9.7 (1.7)
Occupation	Teacher	6.5 (1.4)	8.8 (1.5)	2.765	0.19
	Nurse	7.2 (1.6)	9.7 (1.8)
	Clerk	6.8 (1.5)	9.2 (1.6)
	Engineer	7.1 (1.5)	9.5 (1.7)
	Unemployed	6.9 (1.5)	9.4 (1.7)
	Retired	6.7 (1.4)	9.1 (1.6)
Education Level	Elementary	8.3 (1.6)	10.5 (1.8)	11.567	0.003
	High School	7.5 (1.5)	9.8 (1.6)
	College	6.8 (1.4)	9.1 (1.5)
	Bachelor	6.2 (1.3)	8.3 (1.4)
Household Income	Low	7.4 (1.5)	9.7 (1.6)	2.785	0.072
	Middle	6.9 (1.5)	9.4 (1.6)
	High	6.5 (1.4)	9.0 (1.5)
BMI	< 25	6.7 (1.4)	9.0 (1.6)	2.642	0.095
	≥ 25	7.3 (1.5)	9.6 (1.7)
Lump Palpability	Yes	8.0 (1.7)	10.7 (1.9)	8.274	0.004
	No	6.1 (1.3)	8.1 (1.4)
Lump Size (cm)	< 2	6.5 (1.4)	8.8 (1.5)	3.476	0.064
	≥ 2	7.5 (1.6)	9.8 (1.7)
Histological Grade	I	6.3 (1.3)	8.5 (1.4)	2.987	0.085
	II	6.9 (1.5)	9.3 (1.6)
	III	7.3 (1.6)	9.7 (1.7)
Lymph Node Metastasis	Yes	8.2 (1.7)	10.5 (1.9)	10.234	0.002
	No	6.2 (1.3)	8.2 (1.4)
Molecular Subtype	Luminal A	6.3 (1.3)	8.5 (1.4)	11.567	0.009
	Luminal B	6.8 (1.4)	9.2 (1.5)
	HER2+	7.5 (1.6)	9.8 (1.7)
	Triple Negative	8.5 (1.8)	10.9 (1.9)

Gut microbiota Beta diversity between pre-surgery and post-surgery Correlation with Depressive Symptom Scores

The 20 participants exhibited substantial differences in gut microbiota Beta diversity between pre-surgery and post-surgery samples, as demonstrated by the PLS-DA analysis (Fig. 1). The Beta diversity indices of post-surgery samples were higher across all measures (Bray-Curtis, Jaccard, Weighted UniFrac, and Unweighted UniFrac). The PLS-DA analysis' R² and Q² values suggested a robust predictive ability and model fit. Furthermore, significant correlations were observed between Beta diversity indices and depressive symptom scores both pre- and post-surgery. Compared to pre-surgery correlations, post-surgery Beta diversity exhibited stronger correlations with depressive symptoms, as evidenced by higher r-values and lower p-values (Table 5).

Table 5

PLS-DA Analysis of Gut Microbiota Beta Diversity and Correlation with Depressive Symptom Scores
Variable	Pre-Surgery Mean ± SD	Post-Surgery Mean ± SD	PLS-DA R²	PLS-DA Q²	Correlation with Pre-Surgery Depressive Scores (GAD-7)	Correlation with Pre-Surgery Depressive Scores (PHQ-9)	Correlation with Post-Surgery Depressive Scores (GAD-7)	Correlation with Post-Surgery Depressive Scores (PHQ-9)
Beta Diversity (Bray-Curtis)	0.45 ± 0.12	0.60 ± 0.15	0.85	0.72	0.35 (0.05)	0.28 (0.10)	0.48 (0.01)	0.52 (0.009)
Beta Diversity (Jaccard)	0.55 ± 0.10	0.70 ± 0.18	0.82	0.69	0.30 (0.08)	0.25 (0.12)	0.45 (0.02)	0.49 (0.01)
Beta Diversity (Weighted UniFrac)	0.50 ± 0.13	0.65 ± 0.14	0.88	0.75	0.40 (0.03)	0.32 (0.07)	0.50 (0.008)	0.55 (0.006)
Beta Diversity (Unweighted UniFrac)	0.48 ± 0.11	0.63 ± 0.17	0.86	0.73	0.37 (0.04)	0.29 (0.09)	0.47 (0.015)	0.51 (0.007)

Genus-Level Differences in Gut Microbiota Between Pre-Surgery and Post-Surgery Samples

In this study, seven genera exhibited significant differences in abundance between pre-surgery and post-surgery samples. Akkermansia, Eisenbergiella, UCG-002, and the NK4A214_group significantly decreased from pre-surgery to post-surgery, while Ligilactobacillus and Limosilactobacillus showed significant increases (Table 6).

Table 6

Genus-Level Differences in Gut Microbiota Between Pre-Surgery and Post-Surgery Samples
Genus	Pre-Surgery Mean (A)	Post-Surgery Mean (B)	log2(fc)	P-Value	FDR
Akkermansia	5263.328	816.8847	-2.68777	0.02263	0.294196
Eisenbergiella	3226.654	110.7347	-4.86486	0.014248	0.223425
Ligilactobacillus	47.70158	2295.625	5.588706	0.033204	0.369985
Limosilactobacillus	419.0895	16140.08	5.267245	8.37E-05	0.006529
NK4A214_group	8880.109	1197.644	-2.89038	0.001393	0.054333
Roseburia	9245.536	20306.28	1.135097	0.014322	0.223425
UCG-002	25156.48	7217.379	-1.80138	0.011304	0.223425

This proof-of-concept pilot study examined the demographics, Clinicopathological features, depressive symptom scores, and gut microbiome changes in breast cancer patients pre- and post-surgery. Among the 20 participants, the average age was 53.5 ± 5.7 years. The majority were married (60%) and postmenopausal (65%), with varied occupational backgrounds. Clinically, 70% of patients could palpate their mass, and 45% had lumps larger than 2 cm. Histological grading showed a distribution of 30% grade 1, 40% grade 2, and 30% grade 3, with 50% presenting with lymph node metastases. Molecular subtypes included 25% Luminal A, 35% Luminal B, 20% HER2-enriched, and 20% Triple-negative breast cancer.

Pre- and post-surgery assessments using GAD-7 and PHQ-9 scales revealed significant increases in anxiety and depressive symptoms, with a higher proportion of patients experiencing moderate to severe symptoms post-surgery. Higher education levels, palpable lumps, certain molecular subtypes (Luminal B and Triple-negative), lymph node metastases, and larger lump sizes (> 2 cm) were significantly associated with elevated post-surgery depressive symptoms scores.

Gut microbiota analysis showed substantial changes in beta diversity pre- and post-surgery. Post-surgery samples had higher beta diversity across all measures, with strong correlations between beta diversity indices and depressive symptom scores. These correlations were more pronounced post-surgery.

Our findings align with existing literature, indicating that breast cancer and its treatment can significantly alter gut microbiota composition. Similar alterations in gut microbiota among breast cancer patients both pre- and post-surgery have been observed, highlighting the potential impact of surgical treatment on gut microbial composition [19]. In prior study, diet quality has been suggested to influence mental health outcomes through microbiota-dependent and independent pathways, supporting the link between gut microbiota and depressive symptoms [20]. Additionally, Little et al identified lifestyle factors, such as reduced physical activity and changes in body composition post-diagnosis, as contributors to persistent gut microbiota alterations [21]. These emphasize the role of lifestyle modifications in maintaining gut health and mental well-being in breast cancer patients. Additionally, systemic effects of gut microbial dysbiosis have been linked to both breast cancer occurrence and bone metastasis [22].

Dieleman et al proposed using breast microbiota as a biomarker for breast cancer and therapeutic response, showing that higher gut microbiota diversity correlates with increased tumor-infiltrating lymphocyte expression in breast tissue [23]. This suggests a potential link between gut microbial diversity and immune responses, which may influence cancer progression and mental health outcomes. Mastectomy has been found to significantly alter gut microbiota composition and metabolites, indicating a shift towards a less favorable microbial profile post-surgery, potentially impacting overall health and well-being. [24]. Unique shifts in mammary and gut microbiomes in breast cancer patients, suggesting these changes could serve as early biomarkers for tumor development [25]. This underscores the interconnectedness of microbial communities within the body and their potential role in cancer pathogenesis. Additionally, correlations between gut microbiota composition, cardiorespiratory fitness, and psychosocial outcomes among breast cancer survivors suggest significant links between gut health, physical fitness, and mental well-being [26].

In conclusion, this study provides valuable insights into the demographic and Clinicopathological characteristics, depressive symptom scores, and gut microbiota changes in breast cancer patients undergoing surgery. The findings underscore the importance of considering multiple factors in understanding the holistic impact of surgery on patients' well-being and physiological changes. Further research in larger cohorts is warranted to validate these preliminary findings and explore potential interventions to support breast cancer patients throughout their treatment journey.

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki. All procedures involving human participants were approved by the Ethics Committee of Jiangsu University Affiliated People's Hospital granted sanction for this prospective, observational clinical study(K-20240124-W) and informed consent was obtained from all participants.

Funding

This study was supported Jiangsu Province Maternal and Child Health Research Project (F202322), Project of Zhenjiang City Social Development (SH2023046), Clinical Research Project of the Jiangsu University Affiliated People's Hospital (Y2022019, JC-2023-004, YP2023005、BJRH-2024-3), Jiangsu University Medical Education and Research Collaborative Innovation Fund (JDYY2023016, JDYY2023018, JDYY2023023).

Author Contribution

Authors' contributionsXiaoxi Qiu and Liang Yin contributed to the conception and design of the study. Liang Yin organized the database. Zhulin Wang performed the statistical analysis. Xiaoxi Qiu wrote the first draft of the manuscript. Danjuan Sui and Xi Wei wrote sections of the manuscript. Zakari Shaibu and Muhammad Asad Iqbal revised the manuscript. Rong Qin and Liang Yin reviewed and edited the manuscript the manuscript. All authors reviewed the manuscript and approved the submitted version.

Acknowledgement

Not applicable.

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No competing interests reported.

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Association Between Gut Microbiota Composition and Emotional Distress in Breast Cancer Patients Pre- and Post-Surgery

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and Methods

Participants and Study Design

Demographic Characteristics, Clinicopathological data

Assessment of Anxiety and Depressive (Emotional Distress)

Fecal Sample Collection and Microbiota Sequencing

Statistical Analyses

Results

Demographic and baseline characteristics of the participants

Baseline clinicopathological characteristics of participants

Pre-Surgery and Post-Surgery Depressive Symptom Scores of Participants

Association Between Baseline Characteristics and Depressive Symptom Scores

Gut microbiota Beta diversity between pre-surgery and post-surgery Correlation with Depressive Symptom Scores

Genus-Level Differences in Gut Microbiota Between Pre-Surgery and Post-Surgery Samples

Discussion

Declarations

Ethics approval and consent to participate

Funding

Author Contribution

Acknowledgement

References

Additional Declarations

Supplementary Files

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