Phenomics (Cham, Switzerland)最新文献

Retinal imaging is pivotal in the evaluation of ocular and systemic health, presenting significant promise for extensive population studies. However, the lack of standardized and automated techniques for extracting Imaging-Derived Phenotypes (IDPs) from retinal images is a major impediment. To counteract this challenge, the Chinese Human Phenome Project (CHPP) has developed a comprehensive protocol that includes Quality Control (QC), preprocessing, and automated or semi-automated extraction of IDPs from fundus photography and Optical Coherence Tomography (OCT) images. This protocol incorporates Artificial Intelligence (AI)-based methods to achieve accurate and efficient IDP extraction, facilitating standardized analysis of large-scale populations. We hope that this Standard Operating Procedure (SOP) guideline will impart valuable insights for ophthalmology-related disciplines and provides support for future research endeavors utilizing retinal imaging data.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00155-5.

In gut microbial research, DNA extraction remarkably influences study outcomes and biological interpretations. Rapid advancements in the research scale and technological upgrades necessitate evaluating new methods to ensure reliability and precision in microbial community profiling. We systematically evaluated the performance of eight recent and commonly used extraction methods using a microbial mock community (MMC) and fecal samples from two healthy volunteers, incorporating bacterial, archaeal, and fungal constituents. Performance metrics included nucleic acid assessment, microbial profile assessment, and scalability for large-scale studies, leveraging shotgun metagenomics for in-depth analysis. Despite variations in DNA quantity and quality, all methods yielded sufficient DNA for shotgun metagenomic sequencing. In the MMC microbial profile assessment, the QIAamp PowerFecal pro Kit (PF) and DNeasy PowerSoil HTP kit (PS) methods exhibited higher similarity with the theoretical composition and lower variability across technical replicates compared to other methods. For fecal samples, the extraction method accounted for 21.4% of the overall microbiome variation and significantly affected the abundances of 32% of detected microbial species. Methods using mechanical lysis with small beads, such as PF and PS, demonstrated better efficiency, indicated by increased microbial diversity in extracting DNA from Gram-positive bacteria. Furthermore, the PF and PS methods are notably simple to execute and automation-friendly, though relatively costly. Our study underscores the importance of maintaining consistency in DNA extraction methods for reliable comparative metagenomic analyses. We recommend PF and PS methods as optimal for expansive gut metagenomic research, emphasizing the critical role of mechanical lysis in DNA extraction.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-025-00232-x.

Lipoprotein metabolism is markedly altered in chronic kidney disease (CKD). Studies on the association between nuclear magnetic resonance (NMR) derived lipoprotein subfraction signature and mortality in CKD patients undergoing hemodialysis are limited. NMR based metabolomics was performed on the baseline plasma samples from 368 maintenance hemodialysis patients. Survival analyses were used to investigate the effect of lipoproteins on all-cause mortality and cardiovascular disease (CVD) mortality. Prediction models were further developed using stepwise regression combined cox proportional-hazards model. During the average follow-up of 45.1 months, we observed 144 all-cause deaths and 67 CVD deaths. After adjustment for 14 important covariates, we identified 18 and 35 lipoprotein parameters associated with all-cause mortality and CVD mortality, separately. Cholesterol in total low-density lipoprotein (LDL-C) and total high-density lipoprotein (HDL-C) were correlated with neither all-cause death nor CVD death. For lipoprotein subfractions, triglyceride levels in large very-low density lipoprotein (VLDL) were positively correlated only with all-cause mortality. Lipids (triglyceride, cholesterol and phospholipid) in medium VLDL, cholesterol/total lipids in intermediate-density lipoprotein (IDL) and free cholesterol/total lipids in small high-density lipoprotein (HDL) were positively associated with both all-cause and CVD mortality. The addition of lipoprotein parameters to traditional risk factors significantly improved the mortality risk prediction: the area under the receiver operating characteristic curve (AUC) was improved from 0.811 to 0.842 (p-value = 0.020) for all-cause mortality and 0.806 to 0.854 (p-value = 0.005) for CVD mortality. Our results highlight the lipoprotein subfractions related to all-cause and CVD mortality of maintenance hemodialysis patients, and the lipoproteins-driven prediction models significantly outperform traditional risk factors.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00179-5.

High-altitude polycythemia (HAPC) is a prevalent chronic condition affecting individuals at high altitudes, including both highland and plains populations. This study, involving 2248 participants, explored genetic susceptibility to HAPC among ethnic groups, with 898 HAPC patients (450 Han, 448 Tibetan). The Genome-wide Association Study, encompassing 198 cases (100 Han, 98 Tibetan), identified eight Tibetan HAPC-susceptibility single-nucleotide polymorphisms and four in Han individuals. The common polymorphism locus rs7618658 (SNX4, p _combine < 5 × 10^-8) was validated in both populations. The investigation of Tibetan EPAS1 revealed the rs1374749 locus, along with linked loci, as a potential prevalence factor for HAPC. The GGTAC haplotype containing this locus emerged as a Protect haplotype for HAPC (p = 2.461 × 10^-12, OR = 0.344). Enrichment analysis revealed that Tibetans exhibited susceptibility in oxygen-sensing pathways, such as EPAS1, associated with phenotypes like hemoglobin and platelets. In contrast, Han Chinese showed significant sensitivity in cell differentiation and angiogenesis, closely linked to hemoglobin, hematocrit, and platelets.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00180-y.

Gut microbiome, the group of commensals residing within the intestinal tract, is closely associated with dietary patterns by interacting with food components. The gut microbiome is modifiable by the diet, and in turn, it utilizes the undigested food components as substrates and generates a group of small molecule-metabolites that addressed as "meta-metabolome" in this review. Profiling and mapping of meta-metabolome could yield insightful information at higher resolution and serve as functional readouts for precision nutrition and formation of personalized dietary strategies. For assessing the meta-metabolome, sample preparation is important, and it should aim for retrieval of gut microbial metabolites as intact as possible. The meta-metabolome can be investigated via untargeted and targeted meta-metabolomics with analytical platforms such as nuclear magnetic resonance spectroscopy and mass spectrometry. Employing flux analysis with meta-metabolomics using available database could further elucidate metabolic pathways that lead to biomarker discovery. In conclusion, integration of gut microbiome and meta-metabolomics is a promising supplementary approach to tailor precision dietary intervention. In this review, relationships among diet, gut microbiome, and meta-metabolome are elucidated, with an emphasis on recent advances in alternative analysis techniques proposed for nutritional research. We hope that this review will provide information for establishing pipelines complementary to traditional approaches for achieving precision dietary intervention.

Ovarian cancer (OC), a predominant gynecological malignancy, has consistently showcased grim prognostic outcomes. This investigation delves into the emerging field of pyroptosis and the intricacies of long non-coding RNAs (lncRNAs), specifically the lesser-studied pyroptosis-related lncRNAs (PRlncRNAs), and their roles in OC prognosis. By harnessing transcriptome, and clinic data from the genotype-tissue expression (GTEx) and the cancer genome Atlas (TCGA), we formulated a unique PRlncRNAs risk model consisting of five prognostic lncRNAs by Cox regression and least absolute shrinkage and selection operator (LASSO) regression. Next, the Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, nomogram, and calibration were implemented to verify and evaluate the model. The model also showed general applicability in pan-cancer analysis. Remarkably, our model, upon rigorous validation, outperformed 16 pre-existing counterparts, offering a promising avenue for prognosis prediction. The risk score was used to classify patients into high and low-risk subgroups. The low-risk group showed improved overall survival (OS) and progression-free survival (PFS). The risk score was proved to be an independent prognosis factor. The low-risk group patients also exhibited a higher immune infiltration score and homologous recombination deficiency (HRD) score. Moreover, consensus clustering analysis was utilized to categorize OC patients into three distinct groups, predicated on the expression of the five prognostic lncRNAs. Patients within the third cluster exhibited noteworthy traits, encompassing elevated survival, heightened immune checkpoint expression, and the HRD score. Finally, the expressions of five PRlncRNAs were validated by quantitative real-time PCR (qRT-PCR) in OC cell lines and tissues. In conclusion, the risk model based on the five PRlncRNAs might function as prognostic biomarkers to predict the immune and target drug treatment in OC.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00173-x.

Aldehydes, heterocyclic aromatic amines (HAAs) and terpenes were sparsely studied for their sex-hormone disrupting effect in children and adolescents, although people are widely exposed. This study aimed to investigate the individual and mixture effect of aldehydes, HAAs and terpenes on sex hormones among children and adolescents and explore the effect modification of Vitamin D (VD). Six aldehydes, three HAAs and three terpenes were collected from the National Health and Nutrition Examination Survey 2013-2014, which sampled representative U.S. population. Five sex hormone indicators [testosterone (TT), estradiol (E₂), sex hormone binding globulin (SHBG), free androgen index (FAI) and ratio of TT to E₂ (TT/E₂)] were measured. Multiple linear regression and Bayesian kernel machine regression were used to explore the individual- and joint- exposure to these chemicals with each sex hormone, respectively. We primarily found some chemicals were positively associated with SHBG and negatively associated with TT, E₂, and FAI among male adolescents. In addition, when stratified by pubertal status, we mainly found certain chemicals were negatively associated with TT, E₂, FAI and TT/E₂ in pubertal male and prepubertal female. Joint exposure to HAAs were associated with significant decrease in TT and FAI in male adolescent. These associations present age-, sex- and development-dependent patterns. VD modified these associations with significant results more pronounced in VD ≥ 75 nmol/L group. Our study provided novel findings for the hormonal effect of aldehydes, HAAs and terpenes in children and adolescents, and is also significant for potential avenues for public health action and intervention.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00190-w.

Mobile health technologies provided innovative solutions for lifestyle interventions and offered reliable methods to evaluate behavioral phenotypes during such interventions. To systematically quantify the impacts of behavioral compliance on weight-loss and metabolic profiles during lifestyle intervention, a total of 395 Chinese adults with overweight/obesity (BMI ≥ 24 kg/m²) or central obesity (waistline ≥ 90 cm for men or ≥ 80 cm for women) were randomly assigned to a smartphone app-based arm (SAA, n = 197) or smartphone app plus dietitian arm (SADA, n = 198) for 6 months. Compliance scores (0-5) were determined based on fulfilling five behavioral tasks: completing online courses, wearing a smart band, and recording weight, food intake, and blood pressure. SADA had greater weight-loss (- 4.94% vs. - 2.28%, p < 0.001) and lower triglyceride, but higher HDL-C levels (both p < 0.05) than SAA after six months. Between-group weight-loss differences were attenuated at compliance scores ≥ 3 (SADA: - 6.30% vs. SAA: - 4.79%, p = 0.07). Mediation analysis suggested that compliance scores explained approximately 30% of the additional weight loss in the SADA (p < 0.001), and self-weighing was the primary mediator (p < 0.05). Higher educational levels, greater initial weight loss, self-perceived simplicity, and satisfaction with the program were potential determinants of intervention compliance. Overall, the superior weight loss and metabolic improvements in the SADA group could be mediated by behavioral compliance, which was possibly influenced by some demographic and intervention response features. Our findings highlighted the roles of behavioral phenotypes and adherence in app-based lifestyle interventions, and added evidence for the future development of more precise strategies in long-term weight management.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00162-0.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and immune checkpoint inhibitor (ICI)-based therapies are now an integral part of systemic treatment. In this study, we identify potential biomarker for HCC and further investigate its functional significance using both bioinformatic and experimental methods. Differential analysis and weighted gene co-expression network analysis (WGCNA) were conducted, identifying lumican (LUM) as the target gene. Our results showed a significant downregulation of LUM in HCC. LUM expression was also associated with the progression-free interval and the infiltration of B cells, neutrophils, and myeloid dendritic cells. Enrichment analysis highlighted the involvement of LUM in focal adhesion and the extracellular matrix. In addition, overexpression of LUM suppressed proliferation, migration and invasion in hepatoma cell lines while promoting cell apoptosis. Our results demonstrate the importance of LUM in HCC development and may help to elucidate the underlying mechanisms and biological processes influenced by LUM.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00182-w.