Browsing by Author "Li, Cai"
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Item Open Access Avianbase: a community resource for bird genomics.(Genome Biol, 2015-01-29) Eöry, Lél; Gilbert, M Thomas P; Li, Cai; Li, Bo; Archibald, Alan; Aken, Bronwen L; Zhang, Guojie; Jarvis, Erich; Flicek, Paul; Burt, David WGiving access to sequence and annotation data for genome assemblies is important because, while facilitating research, it places both assembly and annotation quality under scrutiny, resulting in improvements to both. Therefore we announce Avianbase, a resource for bird genomics, which provides access to data released by the Avian Phylogenomics Consortium.Item Open Access Comparative genomic data of the Avian Phylogenomics Project.(2014) Zhang, Guojie; Li, Bo; Li, Cai; Gilbert, M Thomas P; Jarvis, Erich D; Wang, Jun; Wang, Jun; Avian Genome ConsortiumBACKGROUND: The evolutionary relationships of modern birds are among the most challenging to understand in systematic biology and have been debated for centuries. To address this challenge, we assembled or collected the genomes of 48 avian species spanning most orders of birds, including all Neognathae and two of the five Palaeognathae orders, and used the genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomics analyses (Jarvis et al. in press; Zhang et al. in press). Here we release assemblies and datasets associated with the comparative genome analyses, which include 38 newly sequenced avian genomes plus previously released or simultaneously released genomes of Chicken, Zebra finch, Turkey, Pigeon, Peregrine falcon, Duck, Budgerigar, Adelie penguin, Emperor penguin and the Medium Ground Finch. We hope that this resource will serve future efforts in phylogenomics and comparative genomics. FINDINGS: The 38 bird genomes were sequenced using the Illumina HiSeq 2000 platform and assembled using a whole genome shotgun strategy. The 48 genomes were categorized into two groups according to the N50 scaffold size of the assemblies: a high depth group comprising 23 species sequenced at high coverage (>50X) with multiple insert size libraries resulting in N50 scaffold sizes greater than 1 Mb (except the White-throated Tinamou and Bald Eagle); and a low depth group comprising 25 species sequenced at a low coverage (~30X) with two insert size libraries resulting in an average N50 scaffold size of about 50 kb. Repetitive elements comprised 4%-22% of the bird genomes. The assembled scaffolds allowed the homology-based annotation of 13,000 ~ 17000 protein coding genes in each avian genome relative to chicken, zebra finch and human, as well as comparative and sequence conservation analyses. CONCLUSIONS: Here we release full genome assemblies of 38 newly sequenced avian species, link genome assembly downloads for the 7 of the remaining 10 species, and provide a guideline of genomic data that has been generated and used in our Avian Phylogenomics Project. To the best of our knowledge, the Avian Phylogenomics Project is the biggest vertebrate comparative genomics project to date. The genomic data presented here is expected to accelerate further analyses in many fields, including phylogenetics, comparative genomics, evolution, neurobiology, development biology, and other related areas.Item Open Access Comparative genomics reveals insights into avian genome evolution and adaptation.(Science, 2014-12-12) Zhang, Guojie; Li, Cai; Li, Qiye; Li, Bo; Larkin, Denis M; Lee, Chul; Storz, Jay F; Antunes, Agostinho; Greenwold, Matthew J; Meredith, Robert W; Ödeen, Anders; Cui, Jie; Zhou, Qi; Xu, Luohao; Pan, Hailin; Wang, Zongji; Jin, Lijun; Zhang, Pei; Hu, Haofu; Yang, Wei; Hu, Jiang; Xiao, Jin; Yang, Zhikai; Liu, Yang; Xie, Qiaolin; Yu, Hao; Lian, Jinmin; Wen, Ping; Zhang, Fang; Li, Hui; Zeng, Yongli; Xiong, Zijun; Liu, Shiping; Zhou, Long; Huang, Zhiyong; An, Na; Wang, Jie; Zheng, Qiumei; Xiong, Yingqi; Wang, Guangbiao; Wang, Bo; Wang, Jingjing; Fan, Yu; da Fonseca, Rute R; Alfaro-Núñez, Alonzo; Schubert, Mikkel; Orlando, Ludovic; Mourier, Tobias; Howard, Jason T; Ganapathy, Ganeshkumar; Pfenning, Andreas; Whitney, Osceola; Rivas, Miriam V; Hara, Erina; Smith, Julia; Farré, Marta; Narayan, Jitendra; Slavov, Gancho; Romanov, Michael N; Borges, Rui; Borges, Rui; Machado, João Paulo; Khan, Imran; Springer, Mark S; Gatesy, John; Hoffmann, Federico G; Opazo, Juan C; Håstad, Olle; Sawyer, Roger H; Kim, Heebal; Kim, Kyu-Won; Kim, Hyeon Jeong; Cho, Seoae; Li, Ning; Huang, Yinhua; Bruford, Michael W; Zhan, Xiangjiang; Dixon, Andrew; Bertelsen, Mads F; Derryberry, Elizabeth; Warren, Wesley; Wilson, Richard K; Li, Shengbin; Ray, David A; Green, Richard E; O'Brien, Stephen J; Griffin, Darren; Johnson, Warren E; Haussler, David; Ryder, Oliver A; Willerslev, Eske; Graves, Gary R; Alström, Per; Fjeldså, Jon; Mindell, David P; Edwards, Scott V; Braun, Edward L; Rahbek, Carsten; Burt, David W; Houde, Peter; Zhang, Yong; Yang, Huanming; Wang, Jian; Avian Genome Consortium; Jarvis, Erich D; Gilbert, M Thomas P; Wang, JunBirds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.Item Open Access CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study.(Radiology, 2021-09-07) Rigiroli, Francesca; Hoye, Jocelyn; Lerebours, Reginald; Lafata, Kyle J; Li, Cai; Meyer, Mathias; Lyu, Peijie; Ding, Yuqin; Schwartz, Fides R; Mettu, Niharika B; Zani, Sabino; Luo, Sheng; Morgan, Desiree E; Samei, Ehsan; Marin, DanieleBackground Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Do and Kambadakone in this issue.Item Open Access Derivation of a Risk Assessment Tool for Prediction of Long-Term Pain Intensity Reduction After Physical Therapy.(Journal of pain research, 2021-01) Horn, Maggie E; George, Steven Z; Li, Cai; Luo, Sheng; Lentz, Trevor ARationale
Risk assessment tools can improve clinical decision-making for individuals with musculoskeletal pain, but do not currently exist for predicting reduction of pain intensity as an outcome from physical therapy.Aims and objective
The objective of this study was to develop a tool that predicts failure to achieve a 50% pain intensity reduction by 1) determining the appropriate statistical model to inform the tool and 2) select the model that considers the tradeoff between clinical feasibility and statistical accuracy.Methods
This was a retrospective, secondary data analysis of the Optimal Screening for Prediction of Referral and Outcome (OSPRO) cohort. Two hundred and seventy-nine individuals seeking physical therapy for neck, shoulder, back, or knee pain who completed 12-month follow-up were included. Two modeling approaches were taken: a longitudinal model included demographics, presence of previous episodes of pain, and regions of pain in addition to baseline and change in OSPRO Yellow Flag scores to 12 months; two comparison models included the same predictors but assessed only baseline and early change (4 weeks) scores. The primary outcome was failure to achieve a 50% reduction in pain intensity score at 12 months. We compared the area under the curve (AUC) to assess the performance of each candidate model and to determine which to inform the Personalized Pain Prediction (P3) risk assessment tool.Results
The baseline only and early change models demonstrated lower accuracy (AUC=0.68 and 0.71, respectively) than the longitudinal model (0.79) but were within an acceptable predictive range. Therefore, both baseline and early change models were used to inform the P3 risk assessment tool.Conclusion
The P3 tool provides physical therapists with a data-driven approach to identify patients who may be at risk for not achieving improvements in pain intensity following physical therapy.Item Open Access Developing and Validating Risk Assessment Models of Clinical Outcomes in Modern Oncology.(JCO precision oncology, 2019-01) Halabi, Susan; Li, Cai; Luo, ShengThe identification of prognostic factors and building of risk assessment prognostic models will continue to play a major role in 21st century medicine in patient management and decision making. Investigators are often interested in examining the relationship between host, tumor-related, and environmental variables in predicting clinical outcomes. We make a distinction between static and dynamic prediction models. In static prediction modelling, typically variables collected at baseline are utilized in building models. On the other hand, dynamic predictive models leverage the longitudinal data of covariates collected during treatment or follow-up, and hence provide accurate predictions of patients prognoses. To date, most risk assessment models in oncology have been based on static models. In this article, we cover topics that are related to the analysis of prognostic factors, centering on factors that are both relevant at the time of diagnosis or initial treatment and during treatment. We describe the types of risk prediction and then provide a brief description of the penalized regression methods. We then review the state-of-the art methods for dynamic prediction and compare the strengths and the limitations of these methods. While static models will continue to play an important role in oncology, developing and validating dynamic models of clinical outcomes need to take a higher priority. It is apparent that a framework for developing and validating dynamic tools in oncology is still needed. One of the limitations in oncology that modelers may be constrained by the lack of access to the longitudinal biomarker data. It is highly recommended that the next generation of risk assessments consider the longitudinal biomarker data and outcomes so that prediction can be continually updated.Item Open Access Dynamic evolution of the alpha (α) and beta (β) keratins has accompanied integument diversification and the adaptation of birds into novel lifestyles.(BMC Evol Biol, 2014-12-12) Greenwold, Matthew J; Bao, Weier; Jarvis, Erich D; Hu, Haofu; Li, Cai; Gilbert, M Thomas P; Zhang, Guojie; Sawyer, Roger HBACKGROUND: Vertebrate skin appendages are constructed of keratins produced by multigene families. Alpha (α) keratins are found in all vertebrates, while beta (β) keratins are found exclusively in reptiles and birds. We have studied the molecular evolution of these gene families in the genomes of 48 phylogenetically diverse birds and their expression in the scales and feathers of the chicken. RESULTS: We found that the total number of α-keratins is lower in birds than mammals and non-avian reptiles, yet two α-keratin genes (KRT42 and KRT75) have expanded in birds. The β-keratins, however, demonstrate a dynamic evolution associated with avian lifestyle. The avian specific feather β-keratins comprise a large majority of the total number of β-keratins, but independently derived lineages of aquatic and predatory birds have smaller proportions of feather β-keratin genes and larger proportions of keratinocyte β-keratin genes. Additionally, birds of prey have a larger proportion of claw β-keratins. Analysis of α- and β-keratin expression during development of chicken scales and feathers demonstrates that while α-keratins are expressed in these tissues, the number and magnitude of expressed β-keratin genes far exceeds that of α-keratins. CONCLUSIONS: These results support the view that the number of α- and β-keratin genes expressed, the proportion of the β-keratin subfamily genes expressed and the diversification of the β-keratin genes have been important for the evolution of the feather and the adaptation of birds into multiple ecological niches.Item Open Access Fast covariance estimation for multivariate sparse functional data(Stat, 2020-01) Li, Cai; Xiao, Luo; Luo, ShengItem Open Access Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease.(Biometrics, 2021-01-26) Li, Cai; Xiao, Luo; Luo, ShengStudies of Alzheimer's disease (AD) often collect multiple longitudinal clinical outcomes, which are correlated and predictive of AD progression. It is of great scientific interest to investigate the association between the outcomes and time to AD onset. We model the multiple longitudinal outcomes as multivariate sparse functional data and propose a functional joint model linking multivariate functional data to event time data. In particular, we propose a multivariate functional mixed model (MFMM) to identify the shared progression pattern and outcome-specific progression patterns of the outcomes, which enables more interpretable modeling of associations between outcomes and AD onset. The proposed method is applied to the Alzheimer's Disease Neuroimaging Initiative study (ADNI) and the functional joint model sheds new light on inference of five longitudinal outcomes and their associations with AD onset. Simulation studies also confirm the validity of the proposed model. Data used in preparation of this article were obtained from the ADNI database. This article is protected by copyright. All rights reserved.Item Open Access Longitudinal associations between BMI change and the risks of colorectal cancer incidence, cancer-relate and all-cause mortality among 81,388 older adults : BMI change and the risks of colorectal cancer incidence and mortality.(BMC cancer, 2019-11-11) Li, Ji-Bin; Luo, Sheng; Wong, Martin CS; Li, Cai; Feng, Li-Fen; Peng, Jian-Hong; Li, Jing-Hua; Zhang, XiBACKGROUND:It remains controversial whether weight change could influence the risks of colorectal cancer (CRC) and mortality. This study aimed to quantify the associations between full-spectrum changes in body mass index (BMI) and the risks of colorectal cancer (CRC) incidence, cancer-related and all-cause mortality among midlife to elder population. METHODS:A total of 81,388 participants who were free of cancer and aged 55 to 74 years from the Prostate, Lung, Colorectal, and Ovarian (PLCO) screening program were involved. The percentage change of BMI was calculated as (BMI in 2006 - BMI at baseline)/BMI at baseline, and was categorized into nine groups: decrease (≥ 15.0%, 10.0-14.9%, 5.0-9.9%, 2.5-4.9%), stable (decrease/increase < 2.5%), increase (2.5-4.9%, 5.0-9.9%, 10.0-14.9%, ≥ 15.0%). The associations between percentage change in BMI from study enrolment to follow-up (median: 9.1 years) and the risks of CRC and mortality were evaluated using Cox proportional hazard regression models. RESULTS:After 2006, there were 241 new CRC cases, 648 cancer-related deaths, and 2361 all-cause deaths identified. Overall, the associations between BMI change and CRC incidence and cancer-related mortality, respectively, were not statistically significant. Compared with participants whose BMI were stable, individuals who had a decrease in BMI were at increased risk of all-cause mortality, and the HRs were 1.21 (95% CI: 1.03-1.42), 1.65 (95% CI: 1.44-1.89), 1.84 (95% CI: 1.56-2.17), and 2.84 (95% CI: 2.42-3.35) for 2.5-4.9%, 5.0-9.9%, 10.0-14.9%, and ≥ 15.0% decrease in BMI, respectively. An L-shaped association between BMI change and all-cause mortality was observed. Every 5% decrease in BMI was associated with a 27% increase in the risk of all-cause mortality (HR = 1.27, 95% CI: 1.22-1.31, p < 0.001). The results from subgroups showed similar trends. CONCLUSIONS:A decrease in BMI more than 5% shows a significantly increased risk of all-cause mortality among older individuals; but no significant association between increase in BMI and all-cause mortality. These findings emphasize the importance of body weight management in older population, and more studies are warranted to evaluate the cause-and-effect relationship between changes in BMI and cancer incidence/mortality.Item Open Access Longitudinal Monitoring of Pain Associated Distress with the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) Tool: Predicting Reduction Pain Intensity and Disability.(Archives of physical medicine and rehabilitation, 2020-06-26) George, Steven Z; Li, Cai; Luo, Sheng; Horn, Maggie E; Lentz, Trevor AOBJECTIVE:To investigate the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) tool for longitudinal monitoring of pain associated distress with the goal of improving prediction of 50% reduction in pain intensity and disability outcomes. DESIGN:Cohort study with 12-month follow-up after initial care episode SETTING: Ambulatory care, participants seeking care from out-patient physical therapy clinics PARTICIPANTS: Participants were seeking care for primary complaint of neck, low back, knee or shoulder pain. This secondary analysis included 440 subjects (62.5% female; mean age 45.1± 17) at baseline with n=279 (63.4%) providing follow-up data at 12 months. INTERVENTIONS:Not applicable MAIN OUTCOME MEASURES: 50% reduction (baseline to 12-month follow-up) in pain intensity and self-reported disability RESULTS: Trends for prediction accuracy were similar for all versions of the OSPRO-YF. For predicting 50% reduction in pain intensity, model fit met the statistical criterion for improvement (i.e., p < 0.05) with each additional time point added from baseline. Model discrimination improved statistically when the 6-month to 12-month change was added to the model (Area Under the Curve = 0.849, p = 0.003). For predicting 50% reduction in disability, there was no evidence of improvement in model fit or discrimination from baseline with the addition of 4-week, 6-month, or 12-month changes (p's > 0.05). CONCLUSIONS:These results suggested that longitudinal monitoring improved prediction accuracy for reduction in pain intensity, but not for disability reduction. Differences in OSPRO-YF item sets (10 vs. 17 items) or scoring methods (simple summary score vs. yellow flag count) did not impact predictive accuracy for pain intensity, providing flexibility for implementing this tool in practice settings.Item Open Access Olfactory Receptor Subgenomes Linked with Broad Ecological Adaptations in Sauropsida.(Mol Biol Evol, 2015-11) Khan, Imran; Yang, Zhikai; Maldonado, Emanuel; Li, Cai; Zhang, Guojie; Gilbert, M Thomas P; Jarvis, Erich D; O'Brien, Stephen J; Johnson, Warren E; Antunes, AgostinhoOlfactory receptors (ORs) govern a prime sensory function. Extant birds have distinct olfactory abilities, but the molecular mechanisms underlining diversification and specialization remain mostly unknown. We explored OR diversity in 48 phylogenetic and ecologically diverse birds and 2 reptiles (alligator and green sea turtle). OR subgenomes showed species- and lineage-specific variation related with ecological requirements. Overall 1,953 OR genes were identified in reptiles and 16,503 in birds. The two reptiles had larger OR gene repertoires (989 and 964 genes, respectively) than birds (182-688 genes). Overall, birds had more pseudogenes (7,855) than intact genes (1,944). The alligator had significantly more functional genes than sea turtle, likely because of distinct foraging habits. We found rapid species-specific expansion and positive selection in OR14 (detects hydrophobic compounds) in birds and in OR51 and OR52 (detect hydrophilic compounds) in sea turtle, suggestive of terrestrial and aquatic adaptations, respectively. Ecological partitioning among birds of prey, water birds, land birds, and vocal learners showed that diverse ecological factors determined olfactory ability and influenced corresponding olfactory-receptor subgenome. OR5/8/9 was expanded in predatory birds and alligator, suggesting adaptive specialization for carnivory. OR families 2/13, 51, and 52 were correlated with aquatic adaptations (water birds), OR families 6 and 10 were more pronounced in vocal-learning birds, whereas most specialized land birds had an expanded OR family 14. Olfactory bulb ratio (OBR) and OR gene repertoire were correlated. Birds that forage for prey (carnivores/piscivores) had relatively complex OBR and OR gene repertoires compared with modern birds, including passerines, perhaps due to highly developed cognitive capacities facilitating foraging innovations.Item Open Access Phylogenomic analyses data of the avian phylogenomics project.(Gigascience, 2015) Jarvis, Erich D; Mirarab, Siavash; Aberer, Andre J; Li, Bo; Houde, Peter; Li, Cai; Ho, Simon YW; Faircloth, Brant C; Nabholz, Benoit; Howard, Jason T; Suh, Alexander; Weber, Claudia C; da Fonseca, Rute R; Alfaro-Núñez, Alonzo; Narula, Nitish; Liu, Liang; Burt, Dave; Ellegren, Hans; Edwards, Scott V; Stamatakis, Alexandros; Mindell, David P; Cracraft, Joel; Braun, Edward L; Warnow, Tandy; Jun, Wang; Gilbert, M Thomas Pius; Zhang, Guojie; Avian Phylogenomics ConsortiumBACKGROUND: Determining the evolutionary relationships among the major lineages of extant birds has been one of the biggest challenges in systematic biology. To address this challenge, we assembled or collected the genomes of 48 avian species spanning most orders of birds, including all Neognathae and two of the five Palaeognathae orders. We used these genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomic analyses. FINDINGS: Here we present the datasets associated with the phylogenomic analyses, which include sequence alignment files consisting of nucleotides, amino acids, indels, and transposable elements, as well as tree files containing gene trees and species trees. Inferring an accurate phylogeny required generating: 1) A well annotated data set across species based on genome synteny; 2) Alignments with unaligned or incorrectly overaligned sequences filtered out; and 3) Diverse data sets, including genes and their inferred trees, indels, and transposable elements. Our total evidence nucleotide tree (TENT) data set (consisting of exons, introns, and UCEs) gave what we consider our most reliable species tree when using the concatenation-based ExaML algorithm or when using statistical binning with the coalescence-based MP-EST algorithm (which we refer to as MP-EST*). Other data sets, such as the coding sequence of some exons, revealed other properties of genome evolution, namely convergence. CONCLUSIONS: The Avian Phylogenomics Project is the largest vertebrate phylogenomics project to date that we are aware of. The sequence, alignment, and tree data are expected to accelerate analyses in phylogenomics and other related areas.Item Open Access Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach.(BMC medical research methodology, 2024-03) Yang, Qing; Jiang, Meilin; Li, Cai; Luo, Sheng; Crowley, Matthew J; Shaw, Ryan JBackground
Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research.Objective
To introduce functional principal component analysis (fPCA) and demonstrate its potential applicability in estimating trends in ILD collected by mobile heath devices, assessing longitudinal association between ILD and health outcomes, and predicting health outcomes.Methods
fPCA and scalar-to-function regression models were reviewed. A case study was used to illustrate the process of abstracting trends in intensively self-measured blood glucose using functional principal component analysis and then predicting future HbA1c values in patients with type 2 diabetes using a scalar-to-function regression model.Results
Based on the scalar-to-function regression model results, there was a slightly increasing trend between daily blood glucose measures and HbA1c. 61% of variation in HbA1c could be predicted by the three preceding months' blood glucose values measured before breakfast (P < 0.0001, [Formula: see text]).Conclusions
Functional data analysis, specifically fPCA, offers a unique tool to capture patterns in ILD collected by mobile health devices. It is particularly useful in assessing longitudinal dynamic association between repeated measures and outcomes, and can be easily integrated in prediction models to improve prediction precision.Item Open Access Predicting the Risk of Huntington's Disease with Multiple Longitudinal Biomarkers.(Journal of Huntington's disease, 2019-06-22) Li, Fan; Li, Kan; Li, Cai; Luo, Sheng; PREDICT-HD and ENROLL-HD Investigators of the Huntington Study GroupBACKGROUND:Huntington's disease (HD) has gradually become a public health threat, and there is a growing interest in developing prognostic models to predict the time for HD diagnosis. OBJECTIVE:This study aims to develop a novel prognostic model that leverages multiple longitudinal biomarkers to inform the risk of HD. METHODS:The multivariate functional principal component analysis was used to summarize the essential information from multiple longitudinal markers and to obtain a set of prognostic scores. The prognostic scores were used as predictors in a Cox model to predict the right-censored time to diagnosis. We used cross-validation to determine the best model in PREDICT-HD (n = 1,039) and ENROLL-HD (n = 1,776); external validation was carried out in ENROLL-HD. RESULTS:We considered six commonly measured longitudinal biomarkers in PREDICT-HD and ENROLL-HD (Total Motor Score, Symbol Digit Modalities Test, Stroop Word Test, Stroop Color Test, Stroop Interference Test, and Total Functional Capacity). The prognostic model utilizing these longitudinal biomarkers significantly improved the predictive performance over the model with baseline biomarker information. A new prognostic index was computed using the proposed model, and can be dynamically updated over time as new biomarker measurements become available. CONCLUSION:Longitudinal measurements of commonly measured clinical biomarkers substantially improve the risk prediction of Huntington's disease diagnosis. Calculation of the prognostic index informs the patient's risk category and facilitates patient selection in future clinical trials.Item Open Access The LI-RADS Version 2018 MRI Treatment Response Algorithm: Evaluation of Ablated Hepatocellular Carcinoma.(Radiology, 2019-12-17) Chaudhry, Mohammad; McGinty, Katrina A; Mervak, Benjamin; Lerebours, Reginald; Li, Cai; Shropshire, Erin; Ronald, James; Commander, Leah; Hertel, Johann; Luo, Sheng; Bashir, Mustafa R; Burke, Lauren MBBackground The Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is used to assess presumed hepatocellular carcinoma (HCC) after local-regional therapy, but its performance has not been extensively assessed. Purpose To assess the performance of LI-RADS version 2018 TRA in the evaluation of HCC after ablation. Materials and Methods In this retrospective study, patients who underwent ablation therapy for presumed HCC followed by liver transplantation between January 2011 and December 2015 at a single tertiary care center were identified. Lesions were categorized as completely (100%) or incompletely (≤99%) necrotic based on transplant histology. Three radiologists assessed pre- and posttreatment MRI findings using LI-RADS version 2018 and the TRA, respectively. Interreader agreement was assessed by using the Fleiss κ test. Performance characteristics for predicting necrosis category based on LI-RADS treatment response (LR-TR) category (viable or nonviable) were calculated by using generalized mixed-effects models to account for clustering by subject. Results A total of 36 patients (mean age, 58 years ± 5 [standard deviation]; 32 men) with 53 lesions was included. Interreader agreement for pretreatment LI-RADS category was 0.40 (95% confidence interval [CI]: 0.15, 0.67; P < .01) and was lower than the interreader agreement for TRA category (κ = 0.71; 95% CI: 0.59, 0.84; P < .01). After accounting for clustering by subject, sensitivity of tumor necrosis across readers ranged from 40% to 77%, and specificity ranged from 85% to 97% when LR-TR equivocal assessments were treated as nonviable. When LR-TR equivocal assessments were treated as viable, sensitivity of tumor necrosis across readers ranged from 81% to 87%, and specificity ranged from 81% to 85% across readers. Six (11%) of 53 treated lesions were LR-TR equivocal by consensus, with most (five of six) incompletely necrotic at histopathology. Conclusion The Liver Imaging Reporting and Data System treatment response algorithm can be used to predict viable or nonviable hepatocellular carcinoma after ablation. Most ablated lesions rated as treatment response equivocal were incompletely necrotic at histopathology. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Do and Mendiratta-Lala in this issue.Item Open Access Two Antarctic penguin genomes reveal insights into their evolutionary history and molecular changes related to the Antarctic environment.(Gigascience, 2014) Li, Cai; Zhang, Yong; Li, Jianwen; Kong, Lesheng; Hu, Haofu; Pan, Hailin; Xu, Luohao; Deng, Yuan; Li, Qiye; Jin, Lijun; Yu, Hao; Chen, Yan; Liu, Binghang; Yang, Linfeng; Liu, Shiping; Zhang, Yan; Lang, Yongshan; Xia, Jinquan; He, Weiming; Shi, Qiong; Subramanian, Sankar; Millar, Craig D; Meader, Stephen; Rands, Chris M; Fujita, Matthew K; Greenwold, Matthew J; Castoe, Todd A; Pollock, David D; Gu, Wanjun; Nam, Kiwoong; Ellegren, Hans; Ho, Simon Yw; Burt, David W; Ponting, Chris P; Jarvis, Erich D; Gilbert, M Thomas P; Yang, Huanming; Wang, Jian; Lambert, David M; Wang, Jun; Zhang, GuojieBACKGROUND: Penguins are flightless aquatic birds widely distributed in the Southern Hemisphere. The distinctive morphological and physiological features of penguins allow them to live an aquatic life, and some of them have successfully adapted to the hostile environments in Antarctica. To study the phylogenetic and population history of penguins and the molecular basis of their adaptations to Antarctica, we sequenced the genomes of the two Antarctic dwelling penguin species, the Adélie penguin [Pygoscelis adeliae] and emperor penguin [Aptenodytes forsteri]. RESULTS: Phylogenetic dating suggests that early penguins arose ~60 million years ago, coinciding with a period of global warming. Analysis of effective population sizes reveals that the two penguin species experienced population expansions from ~1 million years ago to ~100 thousand years ago, but responded differently to the climatic cooling of the last glacial period. Comparative genomic analyses with other available avian genomes identified molecular changes in genes related to epidermal structure, phototransduction, lipid metabolism, and forelimb morphology. CONCLUSIONS: Our sequencing and initial analyses of the first two penguin genomes provide insights into the timing of penguin origin, fluctuations in effective population sizes of the two penguin species over the past 10 million years, and the potential associations between these biological patterns and global climate change. The molecular changes compared with other avian genomes reflect both shared and diverse adaptations of the two penguin species to the Antarctic environment.Item Open Access Whole-genome analyses resolve early branches in the tree of life of modern birds.(Science, 2014-12-12) Jarvis, Erich D; Mirarab, Siavash; Aberer, Andre J; Li, Bo; Houde, Peter; Li, Cai; Ho, Simon YW; Faircloth, Brant C; Nabholz, Benoit; Howard, Jason T; Suh, Alexander; Weber, Claudia C; da Fonseca, Rute R; Li, Jianwen; Zhang, Fang; Li, Hui; Zhou, Long; Narula, Nitish; Liu, Liang; Ganapathy, Ganesh; Boussau, Bastien; Bayzid, Md Shamsuzzoha; Zavidovych, Volodymyr; Subramanian, Sankar; Gabaldón, Toni; Capella-Gutiérrez, Salvador; Huerta-Cepas, Jaime; Rekepalli, Bhanu; Munch, Kasper; Schierup, Mikkel; Lindow, Bent; Warren, Wesley C; Ray, David; Green, Richard E; Bruford, Michael W; Zhan, Xiangjiang; Dixon, Andrew; Li, Shengbin; Li, Ning; Huang, Yinhua; Derryberry, Elizabeth P; Bertelsen, Mads Frost; Sheldon, Frederick H; Brumfield, Robb T; Mello, Claudio V; Lovell, Peter V; Wirthlin, Morgan; Schneider, Maria Paula Cruz; Prosdocimi, Francisco; Samaniego, José Alfredo; Vargas Velazquez, Amhed Missael; Alfaro-Núñez, Alonzo; Campos, Paula F; Petersen, Bent; Sicheritz-Ponten, Thomas; Pas, An; Bailey, Tom; Scofield, Paul; Bunce, Michael; Lambert, David M; Zhou, Qi; Perelman, Polina; Driskell, Amy C; Shapiro, Beth; Xiong, Zijun; Zeng, Yongli; Liu, Shiping; Li, Zhenyu; Liu, Binghang; Wu, Kui; Xiao, Jin; Yinqi, Xiong; Zheng, Qiuemei; Zhang, Yong; Yang, Huanming; Wang, Jian; Wang, Jian; Smeds, Linnea; Rheindt, Frank E; Braun, Michael; Fjeldsa, Jon; Orlando, Ludovic; Barker, F Keith; Jønsson, Knud Andreas; Johnson, Warren; Koepfli, Klaus-Peter; O'Brien, Stephen; Haussler, David; Ryder, Oliver A; Rahbek, Carsten; Willerslev, Eske; Graves, Gary R; Glenn, Travis C; McCormack, John; Burt, Dave; Ellegren, Hans; Alström, Per; Edwards, Scott V; Stamatakis, Alexandros; Mindell, David P; Cracraft, Joel; Braun, Edward L; Warnow, Tandy; Jun, Wang; Gilbert, M Thomas P; Zhang, GuojieTo better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.