Phenomics (Cham, Switzerland)最新文献

Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [¹⁸F]fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [¹⁸F]FDG PET images in differentiation of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [¹⁸F]FDG PET in MSA and PSP groups (absolute net reclassification index, p < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00079-6.

While early-onset Parkinson's disease (EOPD) caused by mutations in the parkin gene (PRKN) tends to have a relatively benign course compared to genetically undetermined (GU)-EOPD, the exact underlying mechanisms remain elusive. We aimed to search for the differences between PRKN-EOPD and GU-EOPD by dopamine transporter (DAT) and glucose metabolism positron-emission-tomography (PET) imaging. Twelve patients with PRKN-EOPD and 16 with GU-EOPD who accepted both ¹¹C-2b-carbomethoxy-3b-(4-trimethylstannylphenyl) tropane (¹¹C-CFT) and ¹⁸F-fluorodeoxyglucose PET were enrolled. The ¹¹C-CFT uptake was analyzed on both regional and voxel levels, whereas glucose metabolism was assessed in a voxel-wise fashion. Correlations between DAT and glucose metabolism imaging, DAT imaging and clinical severity, as well as glucose metabolism imaging and clinical severity were explored. Both clinical symptoms and DAT-binding patterns in the posterior putamen were highly symmetrical in patients with PRKN-EOPD, and dopaminergic dysfunction in the ipsilateral putamen was severer in patients with PRKN-EOPD than GU-EOPD. Meanwhile, the DAT binding was associated with the severity of motor dysfunction in  patients with GU-EOPD only. Patients with PRKN-EOPD showed increased glucose metabolism in the contralateral medial frontal gyrus (supplementary motor area (SMA)), contralateral substantia nigra, contralateral thalamus, and contralateral cerebellum. Notably, glucose metabolic activity in the contralateral medial frontal gyrus was inversely associated with regional DAT binding in the bilateral putamen. Patients with PRKN-EOPD showed enhanced metabolic connectivity within the bilateral putamen, ipsilateral paracentral and precentral lobules, and the ipsilateral SMA. Collectively, compared to GU-EOPD, PRKN-EOPD is characterized by symmetrical, more severe dopaminergic dysfunction and relative increased glucose metabolism. Meanwhile, SMA with elevated glucose metabolism and enhanced connectivity may act as compensatory mechanisms in PRKN-EOPD.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00077-8.

The systematicness of phenomics and Traditional Chinese Medicine (TCM) enable these two disciplines to interlink with each other. This article discussed the similarity in theory and application between TCM and phenomics and illustrates their respective advantages in diagnosis and treatment of diseases, forming a new discipline eventually. Chinese medicine phenomics (Chinmedphenomics) is built on classic TCM, combined with phenomics technology, and the development of which needs the mega cohort with TCM syndrome and the characteristics of precision medicine as well as multi-disciplinary cooperation, which is personalized, precise and promising, providing unique scientific insights into understanding human health.

Owing to the susceptibility of conventional observational studies to confounding factors and reverse causation, the causal association between cardiac function and frailty is unclear. We aimed to investigate whether cardiac function has causal effects on frailty. In this study, a two-sample Mendelian randomization (MR) study was conducted using genetic variants associated with cardiac function assessed by magnetic resonance imaging phenotypes as instrumental variables. Genetic variants associated with cardiac function by magnetic resonance imaging (including seven cardiac function phenotypes) and the frailty index (FI) were obtained from two large genome-wide association studies. MR estimates from each genetic instrument were combined using inverse variance weighted (IVW), weighted median, and MR‒Egger regression methods. We found that the increase in genetically determined stroke volume (beta - 0.13, 95% CI - 0.16 to - 0.10, p = 1.39E-6), rather than other cardiac phenotypes, was associated with lower FI in MR analysis of IVW after Bonferroni correction. Sensitivity analyses examining potential bias caused by pleiotropy or reverse causality revealed similar findings (e.g., intercept [SE], - 0.008 [0.011], p = 0.47 by MR‒Egger intercept test). The leave-one-out analysis indicated that the association was not driven by single nucleotide polymorphisms. No evidence of heterogeneity was found among the genetic variants (e.g., MR‒Egger: Q statistic = 14.4, p = 0.156). In conclusion, we provided evidence that improved cardiac function could contribute to reducing FI. These findings support the hypothesis that enhancing cardiac function could be an effective prevention strategy for frailty.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00072-z.

As prostate cancer (PCa) is one of the most commonly diagnosed cancer worldwide, identifying potential prognostic biomarkers is crucial. In this study, the survival information, gene expression, and protein expression data of 344 PCa cases were collected from the Cancer Proteome Atlas (TCPA) and the Cancer Genome Atlas (TCGA) to investigate the potential prognostic biomarkers. The integrated prognosis-related proteins (IPRPs) model was constructed based on the risk score of each patients using machine-learning algorithm. IPRPs model suggested that Elevated RAD50 expression (p = 0.016) and down-regulated SMAD4 expression (p = 0.017) were significantly correlated with unfavorable outcomes for PCa patients. Immunohistochemical (IHC) staining and western blot (WB) analysis revealed significant differential expression of SMAD4 and RAD50 protein between tumor and normal tissues in validation cohort. According to the overall IHC score, patients with low SMAD4 (p < 0.0001) expression and high RAD50 expression (p = 0.0001) were significantly correlated with poor outcomes. Besides, expression of SMAD4 showed significantly negative correlation with most immune checkpoint molecules, and the low SMAD4 expression group exhibited significantly high levels of LAG3 (p < 0.05), TGFβ (p < 0.001), and PD-L1 (p < 0.05) compared with the high SMAD4 expression group in the validation cohort. Patients with low SMAD4 expression had significantly higher infiltration of memory B cells (p = 0.002), CD8 + T cells (p < 0.001), regulatory T cells (p = 0.006), M2-type macrophages (p < 0.001), and significantly lower infiltration of naïve B cells (p = 0.002), plasma cells (p < 0.001), resting memory CD4 + T cells (p < 0.001) and eosinophils (p = 0.045). Candidate proteins were mainly involved in antigen processing and presentation, stem cell differentiation, and type I interferon pathways.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00070-1.

Advances in genomic medicine have greatly improved our understanding of human diseases. However, phenome is not well understood. High-resolution and multidimensional phenotypes have shed light on the mechanisms underlying neonatal diseases in greater details and have the potential to optimize clinical strategies. In this review, we first highlight the value of analyzing traditional phenotypes using a data science approach in the neonatal population. We then discuss recent research on high-resolution, multidimensional, and structured phenotypes in neonatal critical diseases. Finally, we briefly introduce current technologies available for the analysis of multidimensional data and the value that can be provided by integrating these data into clinical practice. In summary, a time series of multidimensional phenome can improve our understanding of disease mechanisms and diagnostic decision-making, stratify patients, and provide clinicians with optimized strategies for therapeutic intervention; however, the available technologies for collecting multidimensional data and the best platform for connecting multiple modalities should be considered.

Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.

Poor adherence to standard protocols of blood pressure (BP) measurement in routine clinical practice leads to higher readings than "research-quality" measurements. Whether this phenomenon exists in periodic health examinations was unknown. We aimed to explore the concordance between BP measurements in periodic health examinations and those measured following a standard measurement protocol. We used data from the Kailuan Study, an ongoing longitudinal cohort study in China, of which participants received biennial health examinations in health management centers. In addition, BPs were measured following standard protocols in a workplace-based hypertension management program nested in the Kailuan Study. We compared BP readings of the same person between the two settings using generalized linear mixed-effects models. A total of 3988 men (the mean age was 44.9 years) had at least two BP measurements both in health examinations and management program with a time interval between the two settings that less than 90 days. The mean systolic blood pressures (SBP) and diastolic blood pressures (DBP) in health examinations were 4.2 (95% CI 3.9-4.5) mm Hg and 3.3 (95% CI 3.1-3.5) mm Hg higher than those in the management program, respectively. Bland-Altman analyses showed the wide agreement intervals ranging from - 27.7- to 36.5-mm Hg for SBP and - 18.3- to 24.7-mm Hg for DBP. In conclusion, BP measurements in periodic health examinations were generally higher than BPs measured following a standard protocol. Our findings highlight the importance of standard BP measurement to avoid overestimation of hypertension prevalence and treatment initiation.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00067-w.

Glutamate (Glu) has been reported to be closely related to the pathophysiology of Tic Disorders (TD). By using proton magnetic resonance spectroscopy (¹H-MRS), we aimed to investigate the relationship between in vivo Glu levels and the severity of TD. We performed a cross-sectional study in medication-free patients with TD and healthy controls aged between 5 and 13 years using ¹H-MRS at 3 T. First, we measured the Glu levels in both patients and controls and observed the difference in subgroups, including mild TD patients and moderate TD patients. We then examined the correlations between the Glu levels and clinical features of the patients. Finally, we assessed the diagnostic value of ¹H-MRS and the influencing factors. Our results show that the Glu levels in the striatum of all patients with TD were not significantly different from those of the healthy controls. Subgroup analysis revealed that the Glu levels in the moderate TD group were higher than those in the mild TD group and healthy controls. The correlation analysis showed that Glu levels are strongly positive correlated with TD severity. The optimal cutoff value of Glu levels to differentiate mild tics from moderate tics was 1.244, with a sensitivity of 88.2% and a specificity of 94.7%. Multiple linear regression models revealed that the severity of TD is one of the important factors that affect Glu levels. We conclude that Glu levels are mainly associated with the severity of tics, thus it could serve as a key biomarker for TD classification.

Palmprints are of long practical and cultural interest. Palmprint principal lines, also called primary palmar lines, are one of the most dominant palmprint features and do not change over the lifespan. The existing methods utilize filters and edge detection operators to get the principal lines from the palm region of interest (ROI), but can not distinguish the principal lines from fine wrinkles. This paper proposes a novel deep-learning architecture to extract palmprint principal lines, which could greatly reduce the influence of fine wrinkles, and classify palmprint phenotypes further from 2D palmprint images. This architecture includes three modules, ROI extraction module (REM) using pre-trained hand key point location model, principal line extraction module (PLEM) using deep edge detection model, and phenotype classifier (PC) based on ResNet34 network. Compared with the current ROI extraction method, our extraction is competitive with a success rate of 95.2%. For principal line extraction, the similarity score between our extracted lines and ground truth palmprint lines achieves 0.813. And the proposed architecture achieves a phenotype classification accuracy of 95.7% based on our self-built palmprint dataset CAS_Palm.