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Stolfi F, Abreu H, Sinella R, Nembrini S, Centonze S, Landra V, Brasso C, Cappellano G, Rocca P, Chiocchetti A. Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine. Front Psychiatry 2024; 15:1422939. [PMID: 38938457 PMCID: PMC11210496 DOI: 10.3389/fpsyt.2024.1422939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 05/28/2024] [Indexed: 06/29/2024] Open
Abstract
Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.
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Affiliation(s)
- Fabiola Stolfi
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Hugo Abreu
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Riccardo Sinella
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Sara Nembrini
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Sara Centonze
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Virginia Landra
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, Turin, Italy
| | - Claudio Brasso
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, Turin, Italy
| | - Giuseppe Cappellano
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
| | - Paola Rocca
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, Turin, Italy
| | - Annalisa Chiocchetti
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), Università del Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara, Italy
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Luo X, Wang R, Zhou Y, Xie W. The relationship between emotional disorders and heart rate variability: A Mendelian randomization study. PLoS One 2024; 19:e0298998. [PMID: 38451975 PMCID: PMC10919610 DOI: 10.1371/journal.pone.0298998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/04/2024] [Indexed: 03/09/2024] Open
Abstract
OBJECTIVE Previous studies have shown that emotional disorders are negatively associated with heart rate variability (HRV), but the potential causal relationship between genetic susceptibility to emotional disorders and HRV remains unclear. We aimed to perform a Mendelian randomization (MR) study to investigate the potential association between emotional disorders and HRV. METHODS The data used for this study were obtained from publicly available genome-wide association study datasets. Five models, including the inverse variance weighted model (IVW), the weighted median estimation model (WME), the weighted model-based method (WM), the simple model (SM) and the MR-Egger regression model (MER), were utilized for MR. The leave-one-out sensitivity test, MR pleiotropy residual sum and outlier test (MR-PRESSO) and Cochran's Q test were used to confirm heterogeneity and pleiotropy. RESULTS MR analysis revealed that genetic susceptibility to broad depression was negatively correlated with HRV (pvRSA/HF) (OR = 0.380, 95% CI 0.146-0.992; p = 0.048). However, genetic susceptibility to irritability was positively correlated with HRV (pvRSA/HF, SDNN) (OR = 2.017, 95% CI 1.152-3.534, p = 0.008) (OR = 1.154, 95% CI 1.000-1.331, p = 0.044). Genetic susceptibility to anxiety was positively correlated with HRV (RMSSD) (OR = 2.106, 95% CI 1.032-4.299; p = 0.041). No significant directional pleiotropy or heterogeneity was detected. The accuracy and robustness of these findings were confirmed through a sensitivity analysis. CONCLUSIONS Our MR study provides genetic support for the causal effects of broad depression, irritable mood, and anxiety on HRV.
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Affiliation(s)
- Xu Luo
- College of Clinical Medicine, University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Rui Wang
- College of Clinical Medicine, University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - YunXiang Zhou
- College of Clinical Medicine, University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Wen Xie
- College of Clinical Medicine, University of Traditional Chinese Medicine, Chengdu, Sichuan, China
- Department of Cardiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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Kunugi H. Depression and lifestyle: Focusing on nutrition, exercise, and their possible relevance to molecular mechanisms. Psychiatry Clin Neurosci 2023; 77:420-433. [PMID: 36992617 PMCID: PMC11488618 DOI: 10.1111/pcn.13551] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/03/2023] [Accepted: 03/25/2023] [Indexed: 03/31/2023]
Abstract
Accumulating evidence has suggested the important role of lifestyle factors in depressive disorder. This paper aimed to introduce and outline recent research on epidemiological and intervention studies on lifestyle-related factors in depressive disorder with a special focus on diet. Evidence on exercise, sleep. and related behaviors is also described. Here, findings from meta-analytic studies are emphasized and related studies by the author's research group are introduced. Dietary factors that increase the risk of the illness include energy overload, skipping breakfast, unhealthy diet styles such as Western diet, inflammation-prone diet, and high consumption of ultraprocessed food (UPF). Nutritional imbalances such as inadequate intake of protein, fish (Ω3 polyunsaturated fatty acids), vitamins (folate and vitamin D), and minerals (iron and zinc) increases the risk of depression. Poor oral hygiene, food allergy, addiction to alcohol, and smoking constitute risk factors. Sedentary lifestyle and increased screen time (e.g. video games and the internet) confer the risk of depression. Insomnia and disturbed sleep-wake rhythm are also involved in the pathogenesis of depression. There is accumulating evidence at the meta-analysis level for interventions to modify these lifestyle habits in the protection and treatment of depressive disorder. Main biological mechanisms of the link between lifestyle factors and depression include monoamine imbalance, inflammation, altered stress response, oxidative stress, and dysfunction of brain-derived neurotrophic factor, although other players such as insulin, leptin, and orexin also play a role. To increase resilience to modern stress and ameliorate depression through modification of lifestyle habits, a list of 30 recommendable interventions is presented.
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Affiliation(s)
- Hiroshi Kunugi
- Department of PsychiatryTeikyo University School of MedicineTokyoJapan
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