Category: Research

The association between psychological status and the development of early gastric cancer from atrophic gastritis

A recent hospital-based, cross-sectional observational study, was conducted in the Chinese population to explore the potential relationship between psychological state and the progression of atrophic gastritis (AG; caused by H. pylori or not) to early stage gastric cancer (EGC).

The study included 258 individuals receiving care in the Department of Gastroenterology at The Affiliated Hospital of Xuzhou Medical University between March 2020 and November 2024, and included 173 patients diagnosed with AG and 85 with EGC. Clinical profiles, demographic characteristics, and laboratory indices were initially recorded, and then comparative analyses were conducted between groups.

Results showed that, compared to the AG group, patients with EGC exhibited significantly higher psychological distress and depressive tendencies. These findings, while not conclusive, imply a possible association between psychological state and the presence of early gastric cancer (EGC) in patients with atrophic gastritis, thus suggesting that they could function as independent indicators and contribute to the malignant progression of EGC in patients.

Incorporating mental health screening tools could, therefore, offer supplementary value in the broader context of evaluating patients who might carry an increased likelihood of disease progression.

Learn more about this study here: http://dx.doi.org/10.1097/MD.0000000000045653

Reference

Liang, Mengmeng BD; Wang, Juan MD; Li, Rui MD; Yang, Jun MD; Liu, Yuping BD; Zhao, Lian BD. The association between psychological status and the development of early gastric cancer from atrophic gastritis. Medicine 104(45):p e45653, November 07, 2025
The association between H. pylori infection and cognitive deterioration: a systematic review and meta-analysis

The association between cognitive decline and H. pylori infection remains controversial, with some evidence suggesting that H. pylori eradication may slow the progression of the disease.

A new meta-analysis reviewed 16 studies to explore whether H. pylori affects cognitive function and whether cognitive decline is linked to higher rates of infection.

The analysis found that people with H. pylori infection had a higher risk of cognitive decline, especially when cognitive dysfunction and dementia were combined. However, the infection was not clearly linked to Alzheimer’s disease. Conversely, people with Alzheimer’s disease were more likely to have H. pylori infection than those without, though the association was weaker for other forms of dementia.

These findings suggest a bidirectional relationship in which H. pylori may contribute to cognitive decline, and certain cognitive conditions may increase susceptibility to infection. The study also highlights the need for more well-designed research to fully understand this complex interaction.

Learn more about this study here: https://doi.org/10.1186/s40001-025-03160-8

Reference

Elhady, M.M., Zidan, A., Rabea, E.M. et al. The association between H. pylori infection and cognitive deterioration: a systematic review and meta-analysis. Eur J Med Res 30, 846 (2025)
Assessing Algorithmic Bias in Language-Based Depression Detection: A Comparison of DNN and LLM Approaches

A study found that large language models (LLMs) outperform traditional deep neural network (DNN) embeddings in automated depression detection and show reduced gender bias, through racial disparities remain. Among DNN fairness-mitigation techniques, the worst-group loss provided the best balance between overall accuracy and demographic fairness, while fairness-regularized loss underperformed.

The identified biases affect the fairness and diagnostic reliability of AI systems for mental health assessment, particularly by disadvantaging underrepresented racial and gender groups, mainly Hispanic participants in the case of this research. Such disparities risk perpetuating inequities in automated mental health screening and could undermine trust and validity in clinical or public health applications.

Learn more about the study here: https://doi.org/10.48550/arXiv.2509.25795

Reference

Junias, O., Kini, P., & Chaspari, T. (2025). Assessing Algorithmic Bias in Language-Based Depression Detection: A Comparison of DNN and LLM Approaches. 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), 1-7.
Developing personalized algorithms for sensing mental health symptoms in daily life

This study investigates algorithmic bias in AI tools that predict depression risk using smartphone-sensed behavioral data.

It finds that these tools underperform in larger, more diverse populations because the behavioral patterns used to predict depression are inconsistent across demographic and socioeconomic subgroups.

Specifically, the AI models often misclassify individuals from certain groups—such as older adults or those from different racial or gender backgrounds—as being at lower risk than they actually are. The authors emphasize the need for tailored, subgroup-aware approaches to improve reliability and fairness in mental health prediction tools. This work highlights the importance of addressing demographic bias to ensure equitable AI deployment in mental healthcare.

Learn more about this study here: https://doi.org/10.1038/s44184-025-00147-5

Reference

Timmons, A.C., Tutul, A.A., Avramidis, K. et al. Developing personalized algorithms for sensing mental health symptoms in daily life. npj Mental Health Res 4, 34 (2025).
Regulatory Effects of Probiotics on Anxiety and Depression‑Like Behaviors in H. pylori‑Infected Rats

In a recent experimental study, researchers used rats to explore whether the use of probiotics such as Lactobacillus can mitigate anxiety- and depression-like behaviors, counteracting the psychological and biological effects of H. pylori infection. Infected rats were treated with each probiotic alone or with the combination, and were then evaluated using standard behavioral tests for anxiety and depression.

Both probiotics, especially when co-administered, reversed the depressive and anxiogenic effects induced by H. pylori. Probiotic supplementation also corrected several brain changes linked to H. pylori, including oxidative stress, inflammation, reduced BDNF/serotonin, and elevated corticosterone.

The findings suggest that multi-strain probiotics may help manage psychiatric symptoms associated with H. pylori infection, and that they merit further clinical evaluation in patients with psychiatric comorbidities.

Learn more about this study here: https://doi.org/10.1007/s12602-025-10674-4

Reference

Ahmadi-Soleimani, S.M., Masoudi, M., Tabrizi, A.M.A. et al. Regulatory Effects of Probiotics on Anxiety and Depression-Like Behaviors in H. pylori-Infected Rats. Probiotics & Antimicro. Prot. (2025)
Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models

The article investigates racial bias in psychiatric diagnosis and treatment recommendations across four large language models (LLMs): Claude, ChatGPT, Gemini, and NewMes-15. The study evaluates the models’ responses to ten psychiatric cases representing five diagnoses (depression, anxiety, schizophrenia, eating disorders, and ADHD) under three conditions: race-neutral, race-implied, and race-explicitly stated (African American).

Key findings include:

1) Bias in Treatment Recommendations: LLMs often proposed inferior or divergent treatments when racial characteristics were explicitly or implicitly indicated, particularly for schizophrenia and anxiety cases. Diagnostic decisions showed minimal bias overall.

2) Model Performance: NewMes-15 exhibited the highest degree of racial bias, while Gemini demonstrated the least bias across conditions.

3) Statistical Analysis: A Kruskal–Wallis H-test revealed significant differences in bias among the LLMs, with Gemini being significantly less biased than ChatGPT and NewMes-15.

4) Challenges in AI Development: The study highlights that LLMs trained on biased datasets may perpetuate racial disparities in psychiatric care, even when specialized medical training data is used. Local LLMs, despite their cost and privacy advantages, showed higher susceptibility to bias compared to larger, online models.

Learn more about this study here: https://doi.org/10.1038/s41746-025-01746-4

Reference

Bouguettaya, A., Stuart, E.M. & Aboujaoude, E. Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models. npj Digit. Med. 8, 332 (2025).
Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection

A domain adversarial training (DAT) was developed in a study as a method to reduce gender bias in AI models for depression and PTSD detection using speech data (E-DAIC dataset).

DAT improved F1-scores up to +13% and reduced gender gaps in detection accuracy, improving generalization across male and female participants, specially addressing the effects of the latter’s underrepresentation.

Learn more about this study here: https://doi.org/10.48550/arXiv.2505.03359

Reference

Kim, J., Yoon, H., Oh, W., Jung, D., Yoon, S., Kim, D., Lee, D., Lee, S., & Yang, C. (2025). Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection. 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1-7.
Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders

Although depression is often linked to digestive disorders, the biological connection behind this phenomenon has remained unclear.

A recent genome-wide association study analyzed genetic data from hundreds of thousands of people to explore potential links between major depressive disorder (MDD) and gastrointestinal conditions such as peptic ulcers (mainly caused by H. pylori infection), acid reflux, irritable bowel disease, and inflammatory bowel disease.

The researchers found that depression shares genetic risk factors with most digestive disorders, meaning that some of the same genes and genetic regions influence both mental and gut health. The study also suggested that genetic susceptibility to certain gut conditions may increase the risk of depression, once again highlighting the strong gut-brain connection.

These findings could help scientists better understand the gut-brain connection and may point to new ways to treat gastrointestinal symptoms in patients with depression.

Learn more about this study here: https://doi.org/10.1016/j.jad.2025.01.048

Reference

Zhou, S., Zi, J., Hu, Y., Wang, X., Cheng, G., & Xiong, J. (2025). Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders. Journal of affective disorders, 374, 84–90.
Minding the Gaps: Neuroethics, AI, and Depression

In this article, the author highlights the benefits and potential issues regarding the use of AI in depression diagnosis/treatment, focusing on the prevalent gender, racial and ethnicity biases.

It is mentioned that, given the historical, inherent biases in society generally and healthcare specifically, AI-driven advancements are not going to serve minority groups as a matter of course. Unless they are tailored to represent and serve all communities equally, they will exacerbate existing biases and disparities.

Learn more about this article here: https://nonprofitquarterly.org/minding-the-gaps-neuroethics-ai-and-depression/

Reference

Boothroyd, Gemma (2024), “Minding the Gaps: Neuroethics, AI, and Depression”, in Nonprofit Quarterly Magazine, winter 2024, “Health Justice in the Digital Age: Can We Harness AI for Good?”
Bias and Fairness in AI-Based Mental Health Models

The paper examines bias and fairness issues in AI-based mental health applications, including diagnostic tools, chatbots, and suicide risk prediction models. It reports how unrepresentative datasets lead to misdiagnosis and unequal outcomes across different socioeconomic, gender and racial groups – namely concerning women, local ethnic minorities or non-Western societies -, and presents mitigation strategies such as diverse datasets, fairness metrics, and human-in-the-loop approaches.

Learn more about this paper here: https://www.researchgate.net/publication/389214235_Bias_and_Fairness_in_AI-Based_Mental_Health_Models

Reference

Barnty, Barnabas & Joseph, Oloyede & Ok, Emmanuel. (2025). Bias and Fairness in AI-Based Mental Health Models.
AI and Mental Healthcare – ethical and regulatory considerations

This governmental report discusses the ethical and regulatory considerations of using artificial intelligence in mental healthcare in the UK.

Bias in AI tools (algorithmic bias) can stem from various places, including tools being trained on biased datasets and outputting discriminatory outcomes or developers making biased decisions in the design or training of such tools. For example, mental health Electronic health record (EHR) data is susceptible to cohort and label bias. This can occur because culture-bound presentations of mental disorders, combined with a lack of transcultural literacy among clinicians, often lead to both over- and under-diagnosis. People can also exhibit bias when using AI tools, such as over-relying on, or mistrusting AI outputs. All these biases can be conscious or unconscious.

Learn more about the report here: https://doi.org/10.58248/PN738

Reference

Gardiner, Hannah and Natasha Mutebi (2025), AI and Mental Healthcare – ethical and regulatory considerations, UK Parliament – POST, POSTnote 738, 31 January 2025
A Data-Centric Approach to Detecting and Mitigating Demographic Bias in Pediatric Mental Health Text: A Case Study in Anxiety Detection

This study examines classification parity across sex and finds that female adolescents have systematically under-diagnosed mental health disorders: their model’s accuracy was ~4 % lower and false negative rate ~9 % higher compared to male patients. The source of the bias resides in the textual data, namely notes corresponding to male patients tended to be on average 500 words longer and had distinct word usage. To mitigate this, the authors introduce a de-biasing method, based on neutralizing biased terms (gendered words and pronouns) and reducing sentences to essential clinical information. After correcting, diagnostic bias is reduced by up to 27%.

This emphasizes how linguistically transmitted bias—ensuing from word choice and gendered language—consistently leads to the under-diagnosis of mental health disorders among female adolescents, which critically undermines the impartiality of medical diagnosis and treatment.

Learn more about this study here: https://doi.org/10.48550/arXiv.2501.00129

Reference

Ive, J., Bondaronek, P., Yadav, V., Santel, D., Glauser, T., Cheng, T., Strawn, J.R., Agasthya, G., Tschida, J., Choo, S., Chandrashekar, M., Kapadia, A.J., & Pestian, J.P. (2024). A Data-Centric Approach to Detecting and Mitigating Demographic Bias in Pediatric Mental Health Text: A Case Study in Anxiety Detection.
The Role of Gender: Gender Fairness in the Detection of Depression Symptoms on Social Media

The study found that the BDI-Sen dataset used for depression symptom detection on social media exhibits gender bias, with machine learning models such as mentalBERT showing predictive disparities that generally favour male users. Although bias mitigation techniques like data augmentation reduced the bias, they did not eliminate it completely.

The existence of this bias affects the fairness and reliability of AI systems in detecting depression symptoms, leading to unequal predictive performance across genders. This can result in under- or over-identification of depression symptoms in certain groups, thereby compromising the validity of such systems for clinical or mental health monitoring.

Learn more about this study here: https://studenttheses.uu.nl/handle/20.500.12932/47734

Reference

Gierschmann, Lara (2024), The Role of Gender: Gender Fairness in the Detection of Depression Symptoms on Social Media, Utrecht University, unpublished Master Thesis
Association of Helicobacter pylori Infection with Depression and Anxiety: A Systematic Review and Meta-Analysis

The association between Helicobacter pylori infection and depression and anxiety has been reported in the literature.

A meta-analysis was developed in 2024 with the aim of investigating the association between H. pylori infection with these mental health conditions. The systematic search was conducted not only in international sources such as PubMed, Web of Science, and Embase, but also in Chinese databases, and looked for observational studies that reported the incidence or prevalence of depression and anxiety in patients with H. pylori infection.

Surprisingly, while the findings of this analysis showed a significant positive association between the bacteria and anxiety disorders, the association with depression appeared to be insignificant. Nevertheless, this finding seems to imply that clinicians treating H. pylori patients should also address their psychological well-being.

Learn more about this review here: https://doi.org/10.1155/2024/9247586

Reference

Li, Lu, Ren, Yadi, Wang, Zeyu, Niu, Yanqing, Zhao, Ying, Aihaiti, Xiaherezhati, Ji, Yinglan, Li, Man, Association of Helicobacter pylori Infection with Depression and Anxiety: A Systematic Review and Meta-Analysis, International Journal of Clinical Practice, 2024, 9247586, 9 pages, 2024.
Impact of Helicobacter pylori eradication on age‑specific risk of incident dementia in patients with peptic ulcer disease: a nationwide population‑based cohort study

A large South Korean cohort study from 2024 examined whether peptic ulcer disease (PUD) and Helicobacter pylori eradication therapy influence dementia risk in adults aged 55–79.

Using national health insurance data from 2002–2015 and propensity score matching, researchers assessed overall dementia and Alzheimer’s disease (AD) over 5–10 years. While the researchers did not directly verify the presence of the bacteria, their findings were based on treatment history.

The results showed that PUD was associated with a higher risk of developing dementia, with a stronger link for overall dementia than for AD. Eradication therapy itself did not markedly change overall risk, but later treatment was associated with greater dementia risk, highlighting the importance of timely management. Age-stratified analyses also indicated elevated AD risk, particularly in individuals in their 60s and 70s.

Overall, the findings suggest that PUD is a risk factor for dementia in older adults, and that early treatment of H. pylori infection may play a role in prevention strategies for neurodegenerative diseases.

Learn more about this study here: https://doi.org/10.1007/s11357-024-01284-z

Reference

Kang, D.W., Lee, JW., Park, M.Y. et al. Impact of Helicobacter pylori eradication on age-specific risk of incident dementia in patients with peptic ulcer disease: a nationwide population-based cohort study. GeroScience 47, 1161–1174 (2025).
Gender Bias in AI’s Perception of Cardiovascular Risk

The study investigated gender bias in GPT-4’s assessment of coronary artery disease risk and showed that there was a substantial shift in the perception of risk between men and women when a psychiatric comorbidity was added to the vignette, even when they presented identical complaints.

This resulted in women being assessed as having as lower risk of CAD when concurrently having a psychiatric condition.

Learn more about this study here: https://www.jmir.org/2024/1/e54242

Reference

Achtari M, Salihu A, Muller O, Abbé E, Clair C, Schwarz J, Fournier S
Gender Bias in AI’s Perception of Cardiovascular Risk
J Med Internet Res 2024;26:e54242
DOI: 10.2196/54242
Fairness in AI-Based Mental Health: Clinician Perspectives and Bias Mitigation

Considering how there is limited research on fairness in automated decision making systems in the clinical domain, particularly in the mental health domain, this study explores clinicians’ perceptions of AI fairness through two distinct scenarios: violence risk assessment and depression phenotype recognition using textual clinical notes.

Clinicians were engaged with through semi-structured interviews to understand their fairness perceptions and to identify appropriate quantitative fairness objectives for these scenarios. Then, a set of bias mitigation strategies were compared, developed to improve at least one of the four selected fairness objectives. The findings underscore the importance of carefully selecting fairness measures, as prioritizing less relevant measures can have a detrimental rather than a beneficial effect on model behavior in real-world clinical use.

Learn more about the article here: https://doi.org/10.1609/aies.v7i1.31732

Reference

Sogancioglu, G., Mosteiro, P., Salah, A. A., Scheepers, F., & Kaya, H. (2024). Fairness in AI-Based Mental Health: Clinician Perspectives and Bias Mitigation. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 7(1), 1390-1400.
Multimodal Fusion of EEG and Audio Spectrogram for Major Depressive Disorder Recognition Using Modified DenseNet121

Depression and anxiety are common, often co-occurring mental health disorders that complicate diagnosis due to overlapping symptoms and reliance on subjective assessments.

Standard diagnostic tools are widely used but can introduce bias, as they depend on self-reported symptoms and clinician interpretation, which vary across individuals. These methods also fail to account for neurobiological factors such as neurotransmitter imbalances and altered brain connectivity.

Similarly, clinical AI/ML models used in healthcare often lack demographic diversity in their training data, with most studies failing to report race and gender, leading to biased outputs and reduced fairness. EEG offers a promising, objective approach to monitoring brain activity, potentially improving diagnostic accuracy and helping address biases in mental health assessment, as this study found.

Learn more about it here: https://doi.org/10.3390/brainsci14101018

Reference

Yousufi, M., Damaševičius, R., & Maskeliūnas, R. (2024). Multimodal Fusion of EEG and Audio Spectrogram for Major Depressive Disorder Recognition Using Modified DenseNet121. Brain sciences, 14(10), 1018.
Deconstructing demographic bias in speech-based machine learning models for digital health

This study investigates algorithmic bias in AI tools that predict depression risk using smartphone-sensed behavioral data.

It finds that the model underperforms across several demographic subgroups, including gender, race, age, and socioeconomic status, often misclassifying individuals with depression as low-risk. For example, older adults and Black or low-income individuals were frequently ranked lower in risk than healthier younger or White individuals.

These biases stem from inconsistent relationships between sensed behaviors and depression across groups. The authors emphasized the need for subgroup-specific modeling to improve fairness and reliability in mental health AI tools.

Learn more about this study here: https://doi.org/10.3389/fdgth.2024.1351637

Reference

Yang M, El-Attar AA and Chaspari T (2024) Deconstructing demographic bias in speech-based machine learning models for digital health. Front. Digit. Health 6: 1351637.
Investigating the synergistic effects of amitriptyline and H. pylori eradication on depressive-like behaviors and inflammatory cytokines in mice

Recent research has highlighted the potential role of Helicobacter pylori in the pathogenesis of psychiatric disorders. In this experimental study, researchers used mice to explore whether combining amitriptyline with H. pylori eradication therapy produced greater benefits than either treatment alone.

Male mice were firstly allocated into four groups: healthy controls, H. pylori-infected mice, mice receiving antidepressant treatment only, and mice receiving both antidepressant and eradication therapy.

The initial findings confirmed that H. pylori infection induced depression-like behaviors in mice. In addition, while the use of antidepressants alone slightly improved these depression-like behaviors, it was the combination of antidepressants and bacterial eradication therapy that induced a more significant improvement in these symptoms. The combined treatment also appears to have led to an improvement in the psychomotor function of the animals.

Inflammatory cytokines (e.g., interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α)) are usually released in response to Helicobacter colonization and tissue damage, leading to a chronic state of inflammation, but are also associated with depression-like behaviors in humans and animal models, behaviors that have been shown to be attenuated by the use of antidepressants. In this study, researchers found that not only was H. pylori infection associated with changes in inflammatory cytokine levels, but that these alterations were partially reversed when both therapies were used together.

Overall, the findings suggest that targeting both infection and mood symptoms simultaneously may offer enhanced behavioral and anti-inflammatory benefits compared to isolated treatment approaches.

Learn more about this study here: https://doi.org/10.1016/j.physbeh.2024.114552

Reference

Miao Xu and Hua Fan, “Investigating the synergistic effects of amitriptyline and H. pylori eradication on depressive-like behaviors and inflammatory cytokines in mice”, Physiology & Behavior, Volume 281, 1 July 2024, 114552
Fairness and bias correction in machine learning for depression prediction across four study populations

A study found that standard machine learning approaches often exhibit biased behaviours in predicting depression across different populations. It also demonstrated that both standard and novel post-hoc-bias mitigation techniques can effectively reduce unfair bias, though no single model achieves equality of outcomes.

The biases that were identified risk reinforcing structural inequalities in mental healthcare, particularly affecting underserved populations. This underscores the importance of analyzing fairness during model selection and transparently reporting the impact of debiasing interventions to ensure equitable healthcare applications.

Learn more about this study here: https://doi.org/10.1038/s41598-024-58427-7

Reference

Dang, V.N., Cascarano, A., Mulder, R.H. et al. Fairness and bias correction in machine learning for depression prediction across four study populations. Sci Rep 14, 7848 (2024).
Key language markers of depression on social media depend on race

A recent U.S. study published in PNAS found that artificial intelligence models analyzing social media posts can detect signs of depression in white Americans but are far less accurate for Black Americans, underscoring the dangers of using AI trained on non-diverse data in healthcare.

According to co-author Sharath Chandra Guntuku from Penn Medicine, these differences suggest that prior AI models and language-based assessments have largely overlooked racial diversity. While the researchers noted that social media analysis should not be used for diagnosis, it may still help assess risk or monitor mental health trends in communities

Learn more about the study here: https://www.pnas.org/doi/10.1073/pnas.2319837121

Reference

S. Rai et al (2024), Key language markers of depression on social media depend on race, Proc. Natl. Acad. Sci. U.S.A. 121 (14)
Value of serum brain-derived neurotrophic factor and glial fibrillary acidic protein for detecting depression in patients with Helicobacter pylori infection

Depression is often associated with Helicobacter pylori and the success of its treatment.

In this recent research paper, it was shown that people infected with these bacteria have lower levels of BDNF (a brain health marker considered a promising biomarker of depression) and higher levels of GFAP (a protein known as a marker of astroglia pathology in depression) in their blood, a change that is strongly related to depression symptoms. The researchers also found that a combined marker including BDNF, GFAP, gut hormone levels, and gastrointestinal symptoms scores was able to accurately predict depression in infected patients.

These findings suggest that these markers could be used to detect depression in people with H. pylori infection.

Learn more about this study here: https://doi.org/10.1016/j.neulet.2024.137687

Reference

Zhao, E., Yu, Q., Wang, M., Wang, Z., Jiang, B., Ma, X., Zhou, B., Dai, Q., Li, J., Wang, S., Chen, F., & Yang, X. (2024). Value of serum brain-derived neurotrophic factor and glial fibrillary acidic protein for detecting depression in patients with Helicobacter pylori infection. Neuroscience letters, 825, 137687.
New-Onset Illness Anxiety Disorder After Helicobacter Pylori Infection: A Case Report

In this interesting case study from 2024, a 21-year-old woman developed illness anxiety disorder (IAD), formerly known as hypochondria, following a Helicobacter pylori infection.

In the case, even after the H. pylori infection was successfully treated, the patient’s anxiety persisted, affecting her daily life and leading to frequent medical visits and avoidance behaviors.

While the study also explored potential psychosocial risk factors that may contribute to developing IAD and discussed both pharmacological and psychological treatment options, this case underscores how physical health events, like infections, can sometimes trigger or exacerbate mental health conditions, emphasizing the importance of integrated care for both gut and mental health.

Learn more about this study here: https://doi.org/10.7759/cureus.52613

Reference

Labban S A, Murshid L, Yousef Alhazmi A, et al. (January 20, 2024) New-Onset Illness Anxiety Disorder After Helicobacter Pylori Infection: A Case Report. Cureus 16(1): e52613.
Neuromodulating agents in functional dyspepsia: a comprehensive review

Functional dyspepsia is a frequent chronic condition characterized by upper abdominal discomfort without an identifiable organic cause. Usual first-line treatments include proton pump inhibitors or Helicobacter pylori eradication, but many patients continue to have persistent symptoms. Because of this, neuromodulating agents are frequently used in clinical practice, although current European, American and Canadian guidelines primarily mention tricyclic antidepressants (TCAs).

This review analyzed randomized controlled trials in adults meeting Rome criteria or with normal endoscopy findings. Out of 386 studies screened, 14 met inclusion criteria.

The findings indicate that TCAs, such as amitriptyline and imipramine, show the strongest evidence of benefit for symptom relief in functional dyspepsia. Other agents, including tetracyclic antidepressants, levosulpiride, and anxiolytics, may be helpful, but current data are insufficient to draw firm conclusions. By contrast, SSRIs and SNRIs do not appear effective for this condition.

Learn more about this review here: https://doi.org/10.51821/86.1.10998

Reference

Bosman, L., Wauters, L., & Vanuytsel, T. (2023). Neuromodulating agents in functional dyspepsia: a comprehensive review. Acta gastro-enterologica Belgica, 86(1), 49–57
Helicobacter Pylori and Psychiatric Disorders: Comorbidity and Therapeutic Perspectives

This 2023 observational study, conducted over three consecutive years in a psychiatric clinic, followed adults receiving outpatient psychiatric care for different psychiatric disorders.

Of those patients, 291 had depression that did not respond to treatment, persistent iron deficiency, or digestive complaints, and were tested for the presence of Helicobacter pylori. After confirming the infection and treating it, most patients also received iron and vitamins B9 and B12 when needed.

The results were striking: 74% of H. pylori–positive patients who continued psychiatric follow-up reported improvement after treatment. They experienced reductions in symptoms such as apathy, loss of pleasure, anxiety, sadness, cognitive problems, derealization, and sleep disturbances.

Although these benefits may be linked to several biological mechanisms, including reduced brain inflammation and changes in how tryptophan is metabolized, as well as the removal of toxins produced by the bacteria the researchers suggest that screening and treating H. pylori infection may meaningfully support psychiatric care in selected patients.

Learn more about this study here: https://www.scientificliterature.org/Anxiety/Anxiety-23-136.pdf

Reference

Kassir Adel and Kassir Sarah. Helicobacter Pylori and Psychiatric Disorders: Comorbidity and Therapeutic Perspectives. Anxiety And Depression Journal. 2023; 4(1):136
Association of mental health conditions and functional gastrointestinal disorders among Vietnamese new-entry medical students

Functional gastrointestinal disorders (FGIDs), sometimes called disorders of gut–brain interaction, do not affect only older people, they are also common in young adults. A study among 400 first-year medical students in Vietnam investigated how these gut disorders relate to mental health.

About 10% of students had an FGID such as functional dyspepsia or irritable bowel syndrome, and 3% had overlapping conditions including acid reflux. Depression and anxiety were also frequent, with around 10% showing signs of major depressive disorder and 7% showing generalized anxiety disorder. Helicobacter pylori infection was detected in 45% of participants.

The key finding was that depression was strongly associated with gut disorders. Students with major depressive disorder were much more likely to have FGIDs and overlapping gastrointestinal problems than students without depression.

Interestingly, in this study, this risk was also greater in women.

These results support the strong link between mental health and digestive symptoms in young adults, highlighting the importance of screening and early support for both areas in student populations.

Learn more about this study here: https://doi.org/10.1371/journal.pone.0289123

Reference

Tran, T. T. T., Luu, M. N., Tran, L. L., Nguyen, D., Quach, D. T., & Hiyama, T. (2023). Association of mental health conditions and functional gastrointestinal disorders among Vietnamese new-entry medical students. PloS one, 18(7), e0289123.
Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression

The systematic review and meta-analysis found that wearable AI systems demonstrate promising performance in detecting and predicting depression. However, substantial variability exists among algorithms and devices, thereby indicating that performance can vary significantly.

What this means is that disparities across different algorithms and devices were identified, suggesting that certain demographic groups may be underrepresented or inadequately served by current wearable AI systems. This variability underscores the need for further research to enhance the generalizability and fairness of these technologies in clinical practice.

Learn more about this review here: https://doi.org/10.1038/s41746 -023-00828-5

Reference

Abd-Alrazaq, A., AlSaad, R., Shuweihdi, F. et al. Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression. npj Digit. Med. 6, 84 (2023).
Helicobacter Pylori Associated Depression among Patients Presenting with Epigastric Pain

Helicobacter pylori infection is an extremely prevalent infection that has been connected not only to a number of illnesses such as stomach cancer and peptic ulcer disease. H. pylori has also been linked to depression but the mechanisms behind this connection are still poorly understood.

A research study by Mohamed and colleagues aimed to better explore this relation by assessing the presence and severity of depression in 150 patients with or without H. pylori infection.

When comparing both groups, the authors found that H. pylori infection was significantly associated with depression and, more interestingly, with its severity. These findings point to the importance of assessing the presence of gastrointestinal symptoms or dyspepsia in patients with depression.

Learn more about this study here: https://healthcitizens.org/wp-content/uploads/2026/01/Mohamed-and-Elrassas_Helicobacter-Pylori-.pdf

Reference

Dina M. Mohamed and Hanan Elrassas, “Helicobacter Pylori Associated Depression among Patients Presenting with Epigastric Pain”, The Egyptian Journal of Hospital Medicine (January 2023) Vol. 90 (2), Page 2315-2320
Helicobacter pylori Infection Is Associated with Long-Term Cognitive Decline in Older Adults: A Two-Year Follow-Up Study

Helicobacter pylori infection is usually known for causing stomach problems, but it may also affect brain health. This research study published in 2023 followed 268 older adults with memory complaints for two years to see whether H. pylori infection was linked to cognitive decline.

While at the beginning of the study, people with and without H. pylori performed similarly on memory tests, over the two-year follow-up, those with a history of infection showed greater declines in their Mini-Mental State Examination (MMSE) scores. After taking into account age, sex, education, genetic risk factors and common medical conditions, H. pylori infection was still associated with a significantly higher risk of cognitive decline, with infected participants more likely to lose three or more MMSE points and showing a faster rate of decline over time.

These findings suggest that H. pylori infection may contribute to progressive cognitive deterioration in older adults with memory complaints and may be relevant in understanding pathways linking infection and dementia.

Learn more about this study here: https://doi.org/10.3233/JAD-221112

Reference

Wang J, Yu N-W, Wang D-Z, et al. Helicobacter pylori Infection Is Associated with Long-Term Cognitive Decline in Older Adults: A Two-Year Follow-Up Study. Journal of Alzheimer’s Disease. 2023;91(4):1351-1358.
Depression among people with dyspepsia and H. pylori infection: A community based cross-sectional study in Ethiopia

A 2022 community-based study in southwest Ethiopia explored potential links between Helicobacter pylori infection, dyspepsia, and depression in residents aged 13 years and older.

Among the 871 participants – most of whom were married, had no formal education, and lived in rural areas – around 11% showed signs of probable depression. The prevalence was slightly higher (13%) among those experiencing at least one symptom of dyspepsia. Interestingly, in this study, H. pylori infection alone was not linked to higher depression rates, nor were age or gender.

The findings suggest digestive symptoms may increase the risk of depression, highlighting the importance of addressing both mental and gut health when managing gastrointestinal symptoms.

Learn more about this study here: https://doi.org/10.1371/journal.pone.0275424

Reference

Soboka, M., Gudina, E. K., Gashaw, M., Amare, H., Berhane, M., Desalegn, H., Tewolde, D., Jebena, M. G., Ali, S., Wieser, A., Froeschl, G., & Tesfaye, M. (2022). Depression among people with dyspepsia and H. pylori infection: A community based cross-sectional study in Ethiopia. PloS one, 17(10), e0275424.
Rapamycin Attenuates Anxiety and Depressive Behavior Induced by Helicobacter pylori in Association with Reduced Circulating Levels of Ghrelin

In this experimental study, researchers investigated how H. pylori infection influences depression-like behavior and certain biological markers in mice, focusing especially on the hormone ghrelin.

Mice infected with the bacteria showed more anxiety- and depression-like behaviors in standard laboratory tests compared with healthy mice. They moved less, showed more signs of stress, and had lower preference for sweet solutions, a common indicator of loss of pleasure.
Biologically, H. pylori infection led to reduced circulating ghrelin levels and activation of the mTOR signaling pathway in the stomach. It was also associated with increased markers of brain inflammation and cell injury in the hippocampus, a brain region important for mood regulation. When mice were treated with rapamycin, an mTOR inhibitor, ghrelin levels increased and brain-inflammation markers were reduced.

Overall, the study suggests that H. pylori infection may contribute to anxiety- and depression-like behaviors by lowering ghrelin levels and increasing neuroinflammation, highlighting a potential biological link between gut infection and mental health.

Learn more about this study here: https://doi.org/10.1155/2022/2847672

Reference

Tian, Jiageng, Wang, Zeyu, Ren, Yadi, Jiang, Yong, Zhao, Ying, Li, Man, Zhang, Zhiguang, Rapamycin Attenuates Anxiety and Depressive Behavior Induced by Helicobacter pylori in Association with Reduced Circulating Levels of Ghrelin, Neural Plasticity, 2022, 2847672, 8 pages, 2022.
Bias Discovery in Machine Learning Models for Mental Health

This article examined how AI can unintentionally reproduce social and demographic biases when applied to mental health prediction. Using benzodiazepine prescriptions as a proxy for conditions such as depression and anxiety, a study analyzed machine learning models trained on patient data to identify systematic disparities.

It found that women are more frequently predicted to receive such treatments, reflecting gender bias, while the models perform less accurately for minority ethnic groups, indicating representation and evaluation bias. The AI models here are not used to prescribe drugs but rather to predict treatment likelihoods, revealing how bias in healthcare data can lead to inequitable AI performance in the context of depression-related care.

Learn more about the article here: https://doi.org/10.3390/info13050237

Reference

Mosteiro, P.J., Kuiper, J., Masthoff, J., Scheepers, F., & Spruit, M. (2022). Bias Discovery in Machine Learning Models for Mental Health. Inf., 13, 237.
Digital health tools for the passive monitoring of depression: a systematic review of methods

This systematic review examines studies linking passive data from smartphones and wearables to depression, identifying key methodological flaws and threats to reproducibility. It highlights biases such as representation, measurement, and evaluation bias, stemming from small, homogenous samples and inconsistent feature construction.

Although gender and race are not explicitly discussed, the lack of diversity in study populations suggests potential demographic bias. The review calls for improved reporting standards and broader sample inclusion to enhance generalizability and clinical relevance. These improvements are essential for ensuring that digital mental health tools are equitable and reliable across diverse populations.

Learn more about this review here: https://doi.org/10.1038/s41746-021-00548-8

Reference

De Angel, V., Lewis, S., White, K., Oetzmann, C., Leightley, D., Oprea, E., Lavelle, G., Matcham, F., Pace, A., Mohr, D. C., Dobson, R., & Hotopf, M. (2022). Digital health tools for the passive monitoring of depression: a systematic review of methods. NPJ digital medicine, 5(1), 3.
Increased risk of short-term depressive disorder after Helicobacter pylori eradication: A population-based nested cohort study

A study using Taiwan’s National Health Insurance data found that antibiotic therapy for H. pylori in patients with peptic ulcer disease was linked to a short-term increase in psychiatrist-diagnosed depression within 30 days. Women and patients treated with clarithromycin were particularly at higher risk.

The researchers reported that the increased risk of depression after H. pylori eradication therapy may involve alterations in the brain-gut-microbiome axis induced by antibiotic treatment, as is it well known that antibiotics can change the gut microbial composition, metabolism, and function, thereby affecting human health and possibly contributing to the pathophysiology of depression.

Based on these findings, the authors recommend that clinicians should monitor mental health shortly after H. pylori eradication, as short-term depressive symptoms may occur and be easily overlooked.

Learn more about this study here: https://doi.org/10.1111/hel.12824

Reference

Tsai C-F, Chen M-H, Wang Y-P, et al. Increased risk of short-term depressive disorder after Helicobacter pylori eradication: A population-based nested cohort study. Helicobacter. 2021; 26:e12824.
GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression

A study of over 450,000 people in the UK Biobank identified 8 independent genes that affect stomach acid, gut movement, and the body’s response to infection, including susceptibility to Helicobacter pylori infection.

The study also explored connections between these gut conditions and depression, which often occurs alongside digestive problems, providing new insights into the complex interplay between gut health and mental well-being.

Learn more about this study here: https://doi.org/10.1038/s41467-021-21280-7

Reference

Wu, Y., Murray, G.K., Byrne, E.M. et al. GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression. Nat Commun 12, 1146 (2021)
Artificial Intelligence in mental health and the biases of language based models

In this literature review of the uses of Natural Language Processing (NLP) models in psychiatry, an approach that “systematically evaluates each stage of model development to explore how biases arise from a clinical, data science and linguistic perspective” was employed to find existing patterns.

The result was that significant biases were found, with respect to religion, race, gender, nationality, sexuality and age.

Learn more about this review here: https://doi.org/10.1371/journal.pone.0240376

Reference

Straw, I., & Callison-Burch, C. (2020). Artificial Intelligence in mental health and the biases of language based models. PloS one, 15(12), e0240376.
The Psychotic Impact of Helicobacter pylori Gastritis and Functional Dyspepsia on Depression: A Systematic Review

The clinical practice of adding antidepressant drugs to the therapy for the eradication of Helicobacter pylori, in addition to the standard drug regimen, has been widely considered in recent years but its specific role in this treatment is still unclear.

In this systematic review researchers tried to establish if there is an association between H. pylori gastritis and depression and to further analyze the therapeutic effect of antidepressants on symptomatic relief in gastritis. For that, they analyzed randomized clinical trials, cross-sectional and prospective studies, and review articles that examined H. pylori infection, depression, functional dyspepsia, and antidepressant treatment. They focused especially on patients whose digestive symptoms did not improve even after successful H. pylori eradication.

Across the studies, a clear pattern emerged: patients with ongoing functional dyspepsia after H. pylori treatment often improved when they were given antidepressants, even when standard eradication therapy alone had not worked. However, the authors highlight that more research is needed before this approach becomes routine medical practice.

Learn more about this review here: https://doi.org/10.7759/cureus.5956

Reference

Al Quraan A M, Beriwal N, Sangay P, et al. (October 21, 2019) The Psychotic Impact of Helicobacter pylori Gastritis and Functional Dyspepsia on Depression: A Systematic Review. Cureus 11(10)
Psychological effects of Helicobacter pylori-associated atrophic gastritis in patients under 50 years: A cross-sectional study

A cross-sectional, observational study involving 975 Japanese individuals who underwent a health checkup, has found that people with atrophic gastritis had a significantly higher risk of experiencing psychological distress or depressed mood.

Interestingly, the risk was higher in females under 50 years old, regardless of H. pylori infection status.

Although the mechanism remains to be elucidated, the researchers suggest there is a possibility that nutritional status, neuroendocrinologic factors, and/or socioeconomic factors are involved. However, further studies are necessary to reveal the precise underlying mechanisms.

Learn more about this study here: https://doi.org/10.1111/hel.12445

Reference

Takeoka A, Tayama J, Kobayashi M, et al. Psychological effects of Helicobacter pylori-associated atrophic gastritis in patients under 50 years: A cross-sectional study. Helicobacter. 2017; 22:e12445
Correlation between social factors and anxiety-depression in function dyspepsia: do relationships exist?

A research study conducted on the Chinese population in 2014 aimed at evaluating the prevalence and the social factors linked to anxiety and depression in patients with functional dyspepsia (FD). This study included 907 patients with FD who attended a gastroenterology service.

Despite being a hospital-based study, results showed that patients with functional dyspepsia had higher anxiety and depression scores when compared to data from the general population. They also found that a higher prevalence of A/D was observed in women, older individuals, those with lower socioeconomic status (lower wages, lower education levels), and those with more stressful jobs, making these aspects risk factors for the development of A/D. Interestingly, they found no differences in relation to family history.

Learn more about this study here: https://doi.org/10.5114/pg.2014.47897

Reference

Huang, Z., Yang, X., Lan, L., Liu, T., Liu, C., & Li, J. et al. (2014). Correlation between social factors and anxiety-depression in function dyspepsia: do relationships exist?. Gastroenterology Review/Przegląd Gastroenterologiczny, 9(6), 348-353.