Phenomics (Cham, Switzerland)最新文献

Phenome has become a consensus as the next innovation source of biomedicine. As the global network dedicated to large-scale research efforts on human phenome and promoting the Human Phenome Project, the Board of International Human Phenome Consortium (IHPC) plays an essential role to guide the strategy and implementation of international human phenome project and to ensure coordination across the IHPC members. The 4th International Human Phenome Consortium Board Meeting was held virtually on December 13, 2022. During the meeting, the keynote speeches highlighted the latest advancements in phenomics. The construction and discoveries of the first human phenome Atlas had shown promising potential in limb development, disease prevention, and early diagnosis. Combining genome-phenome sequencing, analysis, and wellness coaching enhanced individual wellness. Phenomics trajectories from healthy to diseased states and recovery provided insight into the metabolic risk spaces associated with COVID-19. Board members from Ghana, Malaysia, India, and Russia presented their own plans and research progress. The IHPC Board deliberated on the "Framework Guidelines for Human Phenome-related Measurements" and "Proposal of the PhenoBank Initiative". The meeting also featured a presentation of the annual report of the IHPC Journal Phenomics. Laboratory coordination, interoperable databases, and standardized platforms were productively discussed, which would enable concerted research efforts of the Human Phenome Project.

It is widely recognized that tumor immune microenvironment (TIME) plays a crucial role in tumor progression, metastasis, and therapeutic response. Despite several noninvasive strategies have emerged for cancer diagnosis and prognosis, there are still lack of effective radiomic-based model to evaluate TIME status, let alone predict clinical outcome and immune checkpoint inhibitor (ICIs) response for hepatocellular carcinoma (HCC). In this study, we developed a radiomic model to evaluate TIME status within the tumor and predict prognosis and immunotherapy response. A total of 301 patients who underwent magnetic resonance imaging (MRI) examinations were enrolled in our study. The intra-tumoral expression of 17 immune-related molecules were evaluated using co-detection by indexing (CODEX) technology, and we construct Immunoscore (IS) with the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression method to evaluate TIME. Of 6115 features extracted from MRI, five core features were filtered out, and the Radiomic Immunoscore (RIS) showed high accuracy in predicting TIME status in testing cohort (area under the curve = 0.753). More importantly, RIS model showed the capability of predicting therapeutic response to anti-programmed cell death 1 (PD-1) immunotherapy in an independent cohort with advanced HCC patients (area under the curve = 0.731). In comparison with previously radiomic-based models, our integrated RIS model exhibits not only higher accuracy in predicting prognosis but also the potential guiding significance to HCC immunotherapy.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00136-8.

Nuclear medicine and molecular imaging plays a significant role in the detection and management of cardiovascular disease (CVD). With recent advancements in computer power and the availability of digital archives, artificial intelligence (AI) is rapidly gaining traction in the field of medical imaging, including nuclear medicine and molecular imaging. However, the complex and time-consuming workflow and interpretation involved in nuclear medicine and molecular imaging, limit their extensive utilization in clinical practice. To address this challenge, AI has emerged as a fundamental tool for enhancing the role of nuclear medicine and molecular imaging. It has shown promising applications in various crucial aspects of nuclear cardiology, such as optimizing imaging protocols, facilitating data processing, aiding in CVD diagnosis, risk classification and prognosis. In this review paper, we will introduce the key concepts of AI and provide an overview of its current progress in the field of nuclear cardiology. In addition, we will discuss future perspectives for AI in this domain.

The polymorphic microbiome has been defined as one of the "Hallmarks of Cancer". Extensive studies have now uncovered the role of oral microbiota in cancer development and progression. Bacteria, fungi, archaea, and viruses in the oral cavity interact dynamically with the oral microenvironment to maintain the oral micro-ecological homeostasis. This complex interaction is influenced by many factors, such as maternal transmission, personal factors and environmental factors. Dysbiosis of oral microbiota can disturbed this host-microbiota interaction, leading to systemic diseases. Numerous studies have shown the potential associations between oral microbiota and a variety of cancers. However, the underlying mechanisms and therapeutic insights are still poorly understood. In this review, we mainly focus on the following aspects: (1) the factors affect oral microbiota composition and function; (2) the interaction between microenvironment and oral microbiota; (3) the role of multi-kingdom oral microbiota in human health; (4) the potential underlying mechanisms and therapeutic benefits of oral microbiota against cancer. Finally, we aim to describe the impact of oral microbiota on cancer progression and provide novel therapeutic insights into cancer prevention and treatment by targeting oral microbiota.

Evidence for the influence of chronic inflammation induced by microbial dysbiosis on aberrant DNA methylation supports a plausible connexion between disordered microbiota and precancerous lesions of gastric cancer (PLGC). Here, a comprehensive study including multi-omics data was performed to estimate the relationships amongst the gastric microbiome, inflammatory proteins and DNA methylation alterations and their roles in PLGC development. The results demonstrated that gastric dysbacteriosis increased the risk of PLGC and DNA methylation alterations in related tumour suppressor genes. Seven inflammatory biomarkers were identified for antrum and corpus tissues, respectively, amongst which the expression levels of several biomarkers were significantly correlated with the microbial dysbiosis index (MDI) and methylation status of specific tumour suppressor genes. Notably, mediation analysis revealed that microbial dysbiosis partially contributed to DNA methylation changes in the stomach via the inflammatory cytokines C-C motif chemokine 20 (CCL20) and tumour necrosis factor receptor superfamily member 9 (TNFRSF9). Overall, these results may provide new insights into the mechanisms that might link the gastric microbiome to PLGC.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00118-w.

Thyroid cancer, a common endocrine malignancy, is one of the leading death causes among endocrine tumors. The diagnosis of pathological section analysis suffers from diagnostic delay and cumbersome operating procedures. Therefore, we intend to construct the models based on spectral data that can be potentially used for rapid intraoperative papillary thyroid carcinoma (PTC) diagnosis and characterize PTC characteristics. To alleviate any concerns pathologists may have about using the model, we conducted an analysis of the used bands that can be interpreted pathologically. A spectra acquisition system was first built to acquire spectra of pathological section images from 91 patients. The obtained spectral dataset contains 217 spectra of normal thyroid tissue and 217 spectra of PTC tissue. Clinical data of the corresponding patients were collected for subsequent model interpretability analysis. The experiment has been approved by the Ethics Review Committee of the Wuhu Hospital of East China Normal University. The spectral preprocessing method was used to process the spectra, and the preprocessed signal respectively optimized by the first and secondary informative wavelengths selection was used to develop the PTC detection models. The PTC detection model using mean centering (MC) and multiple scattering correction (MSC) has optimal performance, and the reasons for the good performance were analyzed in combination with the spectral acquisition process and composition of the test slide. For model interpretable analysis, the near-ultraviolet band selected for modeling corresponds to the location of amino acid absorption peak, and this is consistent with the clinical phenomenon of significantly lower amino acid concentrations in PTC patients. Moreover, the absorption peak of hemoglobin selected for modeling is consistent with the low hemoglobin index in PTC patients. In addition, the correlation analysis was performed between the selected wavelengths and the clinical data, and the results show: the reflection intensity of selected wavelengths in normal cells has a moderate correlation with cell arrangement structure, nucleus size and free thyroxine (FT4), and has a strong correlation with triiodothyronine (T3); the reflection intensity of selected bands in PTC cells has a moderate correlation with free triiodothyronine (FT3).

Pulse diagnosis equipment used in Traditional Chinese Medicine (TCM) has long been developed for collecting pulse information and in TCM research. However, it is still difficult to implement pulse taking automatically or efficiently in clinical practice. Here, we present a digital protocol for TCM pulse information collection based on bionic pulse diagnosis equipment, which ensures high efficiency, reliability and data integrity of pulse diagnosis information. A four-degree-of-freedom pulse taking platform together with a wrist bracket can satisfy the spatial positioning and angle requirements for individually adaptive pulse acquisition. Three-dimensional reconstruction of a wrist surface and an image localization model are combined to provide coordinates of the acquisition position and detection direction automatically. Three series elastic joints can not only simulate the TCM pulse taking method that "Three fingers in a straight line, the middle finger determining the 'Guan' location and finger pulp pressing on the radial artery," but also simultaneously carry out the force-controlled multi-gradient pressing process. In terms of pulse information integrity, this proposed protocol can generate rich pulse information, including basic individual information, pulse localization distribution, multi-gradient dynamic pulse force time series, and objective pulse parameters, which can help establish the fundamental data sets that are required as the pulse phenotype for subsequent comprehensive analysis of pulse diagnosis. The implementation of this scheme is beneficial to promote the standardization of the digitalized collection of pulse information, the effectiveness of detecting abnormal health status, and the promotion of the fundamental and clinical research of TCM, such as TCM pulse phenomics.

Blood oxygen saturation (SpO₂) is a key indicator of oxygen availability in the body. It is known that a low SpO₂ at high altitude is associated with morbidity and mortality risks due to physiological hypoxemia. Previously, it was proposed that the lowlander immigrants living at high altitude should have a lower SpO₂ level compared to the highlander natives, but this proposal has not been rigorously tested due to the lack of data from the lowlander immigrants living at high altitude. In this study, we compared arterial oxygen saturation of 5929 Tibetan natives and 1034 Han Chinese immigrants living at altitudes ranging from 1120 m to 5020 m. Unexpectedly, the Han immigrants had a higher SpO₂ than the Tibetan natives at the same high altitudes. At the same time, there is a higher prevalence of chronic mountain sickness in Han than in Tibetans at the same altitude. This result suggests that the relatively higher SpO₂ level of the acclimatized Han is associated with a physiological cost, and the SpO₂ level of Tibetans tends to be sub-optimal. Consequently, SpO₂ alone is not a robust indicator of physiological performance at high altitude.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00117-x.

Genome-wide association studies (GWASs) have identified over 100 loci associated with rheumatoid arthritis (RA); however, the functionally affected genes and the underlying molecular mechanisms contributing to these associations are often unknown. In this study, we conducted an integrative genomic analysis incorporating multiple "omics" data and identified a functional regulatory DNA variant, rs56199421, and a plausible mechanism by which it regulates the expression of a putative RA risk gene, ORMDL Sphingolipid Biosynthesis Regulator 3 (ORMDL3). The T allele of rs56199421, located in the enhancer region of ORMDL3, exhibited stronger direct binding ability than the other C allele of rs56199421 did in vitro with the transcription factor JunD and demonstrated higher transcriptional activity. Moreover, the T allele of rs56199421 is associated with elevated RA risk, and ORMDL3 expression is increased in RA patients. Thus, these findings suggest that the T allele of rs56199421 enhances JunD transcription factor binding, increases enhancer activity, and elevates the expression of the RA risk gene ORMDL3.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00107-z.