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Purpose: Accurate detection of microcalcifications ( µ Calcs ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior µ Calc detectability compared with those with a narrow angular range. This study aims to (1) provide guidance for optimizing wide-angle (WA) DBT for improving µ Calcs detectability and (2) prioritize key optimization factors. Approach: An in-silico DBT pipeline was constructed to evaluate µ Calc detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with 120 µ m µ Calc clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis. Results: Results showed that FSM degraded µ Calcs sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to 50 µ m improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a 50 µ m pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC. Conclusions: Based on the magnitude of impact, the priority for enhancing µ Calc detectability in WA DBT is as follows: (1) utilizing detectors with a small pixel pitch and low EN level, (2) allocating a higher dose to central projections, and (3) reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.
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Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestry has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping. SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and linkage disequilibrium patterns, accounts for multiple causal variants in a genomic region and can be applied to GWAS summary statistics. We comprehensively assessed the performance of SuSiEx using simulations. We further showed that SuSiEx improves the fine-mapping of a range of quantitative traits available in both the UK Biobank and Taiwan Biobank, and improves the fine-mapping of schizophrenia-associated loci by integrating GWAS across East Asian and European ancestries.
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PURPOSE: A network meta-analysis was utilized to compare the rehabilitative effectiveness of different exercise interventions on motor function in cerebral palsy(CP) patients. METHODS: Computer searches were conducted across 9 databases, including PubMed, Cochrane Library, Scopus, Web of Science, Embase, and others, to identify randomized controlled trials focusing on different exercise interventions aimed at enhancing motor function in CP patients. The search spanned from the inception of the databases to January 31, 2024. RESULTS: 20 articles, encompassing 570 patients and evaluating three types of exercise interventions, were included in the analysis. Results showed that aerobic training, resistance training, and mixed training exhibited superior outcomes compared to the control group, as evidenced by improvements in Gross Motor Function Measure scores, muscle strength, gait speed, and 10-Meter Walk Test scores (P < 0.05). Furthermore, the network meta-analysis revealed that resistance training ranked highest in enhancing gross motor function and gait speed among CP patients, while mixed training was deemed most effective in improving muscle strength and 10-Meter Walk Test scores. CONCLUSION: Exercise interventions have been shown to significantly improve motor function in CP patients. Among these, resistance training and mixed training stand out for their effectiveness in enhancing walking capabilities. Resistance training is specifically aimed at improving gross motor function, while mixed training focuses on increasing muscle strength.
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Polygenic risk scores (PRSs) are promising tools for advancing precision medicine. However, existing PRS construction methods rely on static summary statistics derived from genome-wide association studies (GWASs), which are often updated at lengthy intervals. As genetic data and health outcomes are continuously being generated at an ever-increasing pace, the current PRS training and deployment paradigm is suboptimal in maximizing the prediction accuracy of PRSs for incoming patients in healthcare settings. Here, we introduce real-time PRS-CS (rtPRS-CS), which enables online, dynamic refinement and calibration of PRS as each new sample is collected, without the need to perform intermediate GWASs. Through extensive simulation studies, we evaluate the performance of rtPRS-CS across various genetic architectures and training sample sizes. Leveraging quantitative traits from the Mass General Brigham Biobank and UK Biobank, we show that rtPRS-CS can integrate massive streaming data to enhance PRS prediction over time. We further apply rtPRS-CS to 22 schizophrenia cohorts in 7 Asian regions, demonstrating the clinical utility of rtPRS-CS in dynamically predicting and stratifying disease risk across diverse genetic ancestries.
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BACKGROUND: Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia. METHODS: A total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed. FINDINGS: Higher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33-7.19) and risk CNVs was 8.47 (95% CI: 1.92-37.43). CNV interacted with genetic risk score on APD efficacy (Beta = -1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%-82.82%). INTERPRETATION: Copy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted. FUNDING: National Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.
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Antipsicóticos , Variaciones en el Número de Copia de ADN , Estudio de Asociación del Genoma Completo , Esquizofrenia , Humanos , Esquizofrenia/tratamiento farmacológico , Esquizofrenia/genética , Antipsicóticos/uso terapéutico , Femenino , Masculino , Adulto , Resultado del Tratamiento , Pueblo Asiatico/genética , China , Persona de Mediana Edad , Pueblos del Este de AsiaRESUMEN
BACKGROUND: Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. METHODS: The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. CONCLUSION: Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.
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Electroencefalografía , Esquizofrenia , Adulto , Femenino , Humanos , Masculino , Biomarcadores , Estudios de Cohortes , Electroencefalografía/métodos , Neurofisiología/métodos , Proyectos de Investigación , Esquizofrenia/fisiopatología , Esquizofrenia/diagnóstico , Sueño/fisiología , Estudios Transversales , Persona de Mediana Edad , AncianoRESUMEN
OBJECTIVE: To compare the rehabilitative efficacy of different physiotherapy scoliosis-specific exercises (PSSE) for adolescent idiopathic scoliosis (AIS) using a network meta-analysis. DESIGN: PubMed, Cochrane Library, Web of Science, EMBASE, VIP Database for Chinese Technical Periodicals, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and Wan Fang Data were searched until October 2023. Meta-analysis and network meta-analysis were conducted using RevMan 5.4 and R4.3.1. This study follows the PRISMA statement and was registered on the PROSPERO platform (No. CRD42022379206). RESULTS: Seventeen RCTs involving 857 patients were included. The meta-analysis showed that PSSE therapy improved Cobb's angle than conventional rehabilitation therapy (standardized mean difference [SMD] = -0.7; 95% confidence interval [CI] = -0.95, -0.44; p = 0.001), angle of trunk rotation (ATR; SMD = -1.05; 95% CI = -1.52, -0.58; p < 0.001), and quality of life (QoL; SMD = 0.61; 95% CI = 0.16, 1.07; p < 0.001). Network meta-analysis showed that Schroth + Scientific Exercise Approach to Scoliosis (SEAS) was the most effective in improving Cobb angle and ATR, while Schroth alone was most effective in improving the QoL. CONCLUSION: The combination of Schroth and SEAS improved the body posture and trunk deformity in patients with AIS, while Schroth alone improved the QoL. The effectiveness of combining different PSSE techniques supports future evidence-based research on AIS treatment.
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Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India (FST 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.
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Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r 2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.
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Gastric cancer (GC) is a widespread malignancy. Banxia Xiexin decoction (BXD) has been used for GC treatment, but the specific mechanisms underlying its therapeutic effects remain controversial. This study used a comprehensive approach to network pharmacology combined with experimental validation to elucidate the mechanism of BXD's anti-GC effects. Initially, we used the UHPLC-LTQ-Orbitrap-MS/MS technology to identify the main chemical constituents of BXD, as well as potential targets associated with these constituents. Then, we employed the Genecard and Online Mendelian Inheritance in Man (OMIM) to determine the targets specifically related to GC. We employed a combination of Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes pathway, and protein-protein interaction analysis to predict the crucial targets of BXD and uncover the pathways involved in its therapeutic effects against GC. The results were subsequently verified through cell experiments. The analysis revealed 174 common targets shared by BXD and GC. GO enrichment analysis highlighted biological processes, such as autophagy, protein kinase activity, and apoptosis. Moreover, the enrichment analysis revealed several significant pathways that serve as the primary mechanisms by which BXD exerts its effects. Notably, these pathways include PI3K-Akt, HIF-1, and Pathways in cancer. Subsequent in vitro experiments demonstrated that BXD effectively hindered GC cell proliferation, stimulated autophagy, and facilitated apoptosis by PI3K-Akt-mTOR signaling pathway regulation. These findings reveal the effectiveness of BXD against GC through diverse components, targets, and pathways, indicating that BXD holds potential therapeutic value in GC treatment. This study uncovers the intricate biological mechanisms that underlie BXD's efficacy in treating GC through the integration of network pharmacology analysis and rigorous in vitro experiments.
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Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.
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Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Humanos , Secuenciación del Exoma , Bancos de Muestras Biológicas , Depresión/genética , Biobanco del Reino UnidoRESUMEN
Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet, the majority of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n=158), Europeans (EUR, n=408), and East Asians (EAS, n=217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs (representing â¼17% of all eQTLs pairs) linked to 1,276 genes (about 10% of all eGenes) and 198,769 SNPs (approximately 16% of all eSNPs) were identified only in the non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare (MAF < 0.05) in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified seven new risk genes ( SFXN2 , RP11-282018.3 , CYP17A1 , VPS37B , DENR , FTCDNL1 , and NT5DC2 ), and three potential novel regulatory variants in known risk genes ( CNNM2 , C12orf65 , and MPHOSPH9 ) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of novel risk genes in SCZ.
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Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.
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Éxito Académico , Pueblos del Este de Asia , Humanos , Escolaridad , Estudio de Asociación del Genoma Completo , Herencia Multifactorial/genética , Población BlancaRESUMEN
This study aims to assess the effects of exercise on cognitive impairment behavioral performance and neuroprotective mechanisms in diabetes mellitus (DM) animal models. PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database (VIP), and China Biomedical Literature Database (CBM) were systematically searched for studies investigating the impact of exercise on cognitive impairment in animal models of diabetes mellitus (DM) from the inception of these databases through July 2023. Rigorous quality assessments were conducted on the included literature. Primary outcome measures comprised fasting blood glucose (FBG) levels and performance in the Morris water maze test, while secondary outcomes focused on mechanisms related to neuroprotection. Statistical analysis of outcome data was conducted using RevMan 5.3 and R software. A total of 17 studies were included, encompassing 399 animals. The results of the meta-analysis of primary outcome measures revealed that, compared to the control group, exercise effectively reduced fasting blood glucose (FBG) levels in diabetic animal models. In the Morris water maze experiment, exercise also significantly decreased the escape latency of diabetic animal models, increased the number of platform crossings, improved the percentage of time spent in the target quadrant, extended the time spent in the target quadrant, and enhanced swimming speed. Meta-analysis of secondary outcome measures indicated that exercise effectively reduced Aß deposition, attenuated oxidative stress, enhanced synaptic function, suppressed cellular apoptosis and neuroinflammation, and promoted neurogenesis. Exercise represents a promising non-pharmacological therapy with a positive impact on diabetes-related cognitive function and neuroprotection. Moreover, this study provides a theoretical foundation for further preclinical and clinical trials.
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Disfunción Cognitiva , Diabetes Mellitus Tipo 2 , Animales , Glucemia , Neuroprotección , Disfunción Cognitiva/terapia , Modelos AnimalesRESUMEN
OBJECTIVE: To perform an evidence-based evaluation of the clinical efficacy of Taijiquan, Baduanjin, Yijinjing and Wuqinxi in interventions for type 2 diabetes. DESIGN: A systematic review and network meta-analysis. METHODS: The comprehensive search included Chinese and other language databases such as the MEDLINE (PubMed), Web of Science, Excerpta Medica Database (Embase), The Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Scientific Journal Database, VIP and China Biomedical Literature Database (CBM). Clinical randomized controlled trials of four traditional Chinese exercise therapies in the treatment of type 2 diabetes, including Taijiquan, Baduanjin, Yijinjing and Wuqinxi, were retrieved. The search time was conducted from the establishment of the database to 30 October 2022. Two researchers screened the documents that met the inclusion criteria, extracted data according to the preset table and evaluated the methodological quality of the included studies according to the quality evaluation tools recommended by the Cochrane System Reviewer Manual V.5.1. The R language, Stata and ADDIS statistical software programs were used to conduct statistics and analysis of intervention measures. RESULTS: A total of 33 randomized controlled trials with 2609 patients were identified. All patients were from China. The results of the network meta-analysis showed that Taijiquan ranked the best for improving HbA1c, 2-h postprandial blood glucose (2hPG), low-density lipoprotein cholesterol (LDL-C) and insulin sensitivity index indicator levels; Yijinjing reduced fasting plasma glucose (FPG) and total cholesterol (TC) indicator levels for the best probability ranking; Baduanjin improved the triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) probability ranking the most. When the training period was less than 12 weeks, Baduanjin had better effects in improving 2hPG, TC, TG, HDL-C and LDL-C indicator levels. Taijiquan had better effects in reducing FPG levels. When the training period was 12 weeks, the effect of Yijinjing in improving FPG, HbAlc, TC and HDL-C levels was better than that in other traditional Chinese exercise, and Taijiquan had better effects in improving 2hPG, TG and LDL-C indicator levels. When the training period was longer than 12 weeks, Taijiquan had better effects in improving FPG, HbAlc, 2hPG and LDL-C indicator levels, and Baduanjin had better effects in improving TC, TG and HDL-C indicator levels. CONCLUSION: The four traditional Chinese exercise therapies can improve blood glucose levels, blood lipid levels and insulin-related indicators of type 2 diabetes to varying degrees. Studies have shown that Taijiquan has a better targeted treatment effect on type 2 diabetes. SYSTEMATIC REVIEW REGISTRATION: CRD42020214786. PROTOCOL PUBLISHED: We published the protocol article "Network meta-analysis of four kinds of traditional Chinese exercise therapy in the treatment of type 2 diabetes: Protocol for a systematic review" in the BMJ Open magazine 2021, Issue 11, Volume 7.
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Diabetes Mellitus Tipo 2 , Humanos , Glucemia , LDL-Colesterol/uso terapéutico , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Terapia por Ejercicio/métodos , Metaanálisis en Red , Ensayos Clínicos Controlados Aleatorios como Asunto , Revisiones Sistemáticas como Asunto , TriglicéridosRESUMEN
Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.
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Background: Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer's disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms. Objective: To study the potential mechanism of metformin action in AD and T2D. Methods: The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein. Results: A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns. Conclusion: Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD.
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Crohn's disease (CD) and ulcerative colitis (UC) are two etiologically related yet distinctive subtypes of the inflammatory bowel diseases (IBD). Differentiating CD from UC can be challenging using conventional clinical approaches in a subset of patients. We designed and evaluated a novel molecular-based prediction model aggregating genetics, serum biomarkers, and tobacco smoking information to assist the diagnosis of CD and UC in over 30,000 samples. A joint model combining genetics, serum biomarkers and smoking explains 46% (42-50%, 95% CI) of phenotypic variation. Despite modest overlaps with serum biomarkers, genetics makes unique contributions to distinguishing IBD subtypes. Smoking status only explains 1% (0-6%, 95% CI) of the phenotypic variance suggesting it may not be an effective biomarker. This study reveals that molecular-based models combining genetics, serum biomarkers, and smoking information could complement current diagnostic strategies and help classify patients based on biologic state rather than imperfect clinical parameters.
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Polygenic risk scores (PRSs) developed from multi-ancestry genome-wide association studies (GWASs), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared with PRSs constructed from single-ancestry GWASs (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Furthermore, integrating PRSs based on local ancestry-informed GWASs and large-scale, European-based PRSs improved predictive performance in understudied African populations, especially for less polygenic traits with large-effect ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRSs from multiple studies.