RESUMO
Translational research on complex, multifactorial mental health disorders, such as bipolar disorder, major depressive disorder, schizophrenia, and substance use disorders requires databases with large-scale, harmonized, and integrated real-world and research data. The Munich Mental Health Biobank (MMHB) is a mental health-specific biobank that was established in 2019 to collect, store, connect, and supply such high-quality phenotypic data and biosamples from patients and study participants, including healthy controls, recruited at the Department of Psychiatry and Psychotherapy (DPP) and the Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital of the Ludwig-Maximilians-University (LMU), Munich, Germany. Participants are asked to complete a questionnaire that assesses sociodemographic and cross-diagnostic clinical information, provide blood samples, and grant access to their existing medical records. The generated data and biosamples are available to both academic and industry researchers. In this manuscript, we outline the workflow and infrastructure of the MMHB, describe the clinical characteristics and representativeness of the sample collected so far, and reveal future plans for expansion and application. As of 31 October 2021, the MMHB contains a continuously growing set of data from 578 patients and 104 healthy controls (46.37% women; median age, 38.31 years). The five most common mental health diagnoses in the MMHB are recurrent depressive disorder (38.78%; ICD-10: F33), alcohol-related disorders (19.88%; ICD-10: F10), schizophrenia (19.69%; ICD-10: F20), depressive episode (15.94%; ICD-10: F32), and personality disorders (13.78%; ICD-10: F60). Compared with the average patient treated at the recruiting hospitals, MMHB participants have significantly more mental health-related contacts, less severe symptoms, and a higher level of functioning. The distribution of diagnoses is also markedly different in MMHB participants compared with individuals who did not participate in the biobank. After establishing the necessary infrastructure and initiating recruitment, the major tasks for the next phase of the MMHB project are to improve the pace of participant enrollment, diversify the sociodemographic and diagnostic characteristics of the sample, and improve the utilization of real-world data generated in routine clinical practice.
RESUMO
Checkpoint blockade immunotherapy relies on the empowerment of the immune system to fight cancer. Why some patients fail to achieve durable clinical responses is not well understood, but unique individual factors such as diet, obesity, and related metabolic syndrome could play a role. The link between obesity and patient outcomes remains controversial and has been mired by conflicting reports and limited mechanistic insight. We addressed this in a C57BL/6 mouse model of diet-induced obesity using a Western diet high in both fats and sugars. Obese mice bearing B16 melanoma or MC38 carcinoma tumors had impaired immune responses to immunotherapy and a reduced capacity to control tumor progression. Unexpectedly, these compromised therapeutic outcomes were independent of body mass and, instead, were directly attributed to dietary fructose. Melanoma tumors in mice on the high-fructose diet were resistant to immunotherapy and showed increased expression of the cytoprotective enzyme heme oxygenase-1 (HO-1). This increase in HO-1 protein was recapitulated in human A375 melanoma cells exposed to fructose in culture. Induced expression of HO-1 shielded tumor cells from immune-mediated killing and was critical for resistance to checkpoint blockade immunotherapy, which could be overcome in vivo using a small-molecule inhibitor of HO-1. This study reveals dietary fructose as a driver of tumor immune evasion, identifying HO-1 expression as a mechanism of resistance and a promising molecular target for combination cancer immunotherapy.See article by Khojandi et al., p. 214.
