Browsing by Author "Liu, Y."

Now showing 1 - 6 of 6
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    Gene Expression Patterns in Bone Following Mechanical Loading
    (Office of the Vice Chancellor for Research, 2010-04-09) Mantila Roosa, S.M.; Liu, Y.; Turner, C.H.
    Mechanical loading is a potent anabolic stimulus that substantially strengthens bones, and the time course of bone formation after initiating mechanical loading is well characterized. However, the time sequence for gene expression in a bone subjected to mechanical loading, over an extended period of time, has not been established. The advent of high-throughput measurements of gene expression and bioinformatics analysis methods offers new ways to study gene expression patterns. The primary goal of this study was to determine the time sequence for gene expression in a bone subjected to mechanical loading, during key periods of the bone formation process, including expression of matrix-related genes, the appearance of active osteoblasts, and bone desensitization. We evaluated loading-induced gene expression over a time course of 4 hours to 32 days. We then used bioinformatics tools to cluster genes into similar expression patterns and created groups of genes with common functions or signaling pathways.
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    Genetic variants in the folate metabolic pathway genes predict melanoma-specific survival
    (Oxford University Press, 2020-10) Dai, W.; Liu, H.; Liu, Y.; Xu, X.; Qian, D.; Luo, S.; Cho, E.; Zhu, D.; Amos, C.I.; Fang, S.; Lee, J.E.; Li, X.; Nan, H.; Li, C.; Wei, Q.; Epidemiology, School of Public Health
    Background: Folate metabolism plays an important role in DNA methylation and nucleic acid synthesis and thus may function as a regulatory factor in cancer development. Genome-wide association studies (GWASs) have identified some single-nucleotide polymorphisms (SNPs) associated with cutaneous melanoma-specific survival (CMSS), but no SNPs were found in genes involved in the folate metabolic pathway. Objectives: To examine associations between SNPs in folate metabolic pathway genes and CMSS. Methods: We comprehensively evaluated 2645 (422 genotyped and 2223 imputed) common SNPs in folate metabolic pathway genes from a published GWAS of 858 patients from The University of Texas MD Anderson Cancer Center and performed the validation in another GWAS of 409 patients from the Nurses' Health Study and Health Professionals Follow-up Study, in which 95/858 (11·1%) and 48/409 (11·7%) patients died of cutaneous melanoma, respectively. Results: We identified two independent SNPs (MTHFD1 rs1950902 G>A and ALPL rs10917006 C>T) to be associated with CMSS in both datasets, and their meta-analysis yielded an allelic hazards ratio of 1·75 (95% confidence interval 1·32-2·32, P = 9·96 × 10-5 ) and 2·05 (1·39-3·01, P = 2·84 × 10-4 ), respectively. The genotype-phenotype correlation analyses provided additional support for the biological plausibility of these two variants' roles in tumour progression, suggesting that variation in SNP-related mRNA expression levels is likely to be the mechanism underlying the observed associations with CMSS. Conclusions: Two possibly functional genetic variants, MTHFD1 rs1950902 and ALPL rs10917006, were likely to be independently or jointly associated with CMSS, which may add to personalized treatment in the future, once further validated. What is already known about this topic? Existing data show that survival rates vary among patients with melanoma with similar clinical characteristics; therefore, it is necessary to identify additional complementary biomarkers for melanoma-specific prognosis. A hypothesis-driven approach, by pooling the effects of single-nucleotide polymorphisms (SNPs) in a specific biological pathway as genetic risk scores, may provide a prognostic utility, and genetic variants of genes in folate metabolism have been reported to be associated with cancer risk. What does this study add? Two genetic variants in the folate metabolic pathway genes, MTHFD1 rs1950902 and ALPL rs10917006, are significantly associated with cutaneous melanoma-specific survival (CMSS). What is the translational message? The identification of genetic variants will make a risk-prediction model possible for CMSS. The SNPs in the folate metabolic pathway genes, once validated in larger studies, may be useful in the personalized management and treatment of patients with cutaneous melanoma.
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    Identification of functional variants from whole-exome sequencing, combined with neuroimaging genetics
    (Springer Nature, 2013) Nho, K.; Corneveaux, J. J.; Kim, S.; Lin, H.; Risacher, S. L.; Shen, L.; Swaminathan, S.; Ramanan, V. K.; Liu, Y.; Foroud, T.; Inlow, M. H.; Siniard, A. L.; Reiman, R. A.; Aisen, P. S.; Petersen, R. C.; Green, R. C.; Jack, C. R.; Weiner, M. W.; Baldwin, C. T.; Lunetta, K.; Farrer, L. A.; Multi-Institutional Research on Alzheimer Genetic Epidemiology (MIRAGE) Study; Furney, S. J.; Lovestone, S.; Simmons, A.; Mecocci, P.; Vellas, B.; Tsolaki, M.; Kloszewska, I.; Soininen, H.; AddNeuroMed Consortium; McDonald, B. C.; Farlow, M. R.; Ghetti, B.; Indiana Memory and Aging Study; Huentelman, M. J.; Saykin, A. J.; Alzheimer's Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
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    Interspecies Comparison of Alveolar Bone Biology, Part I: Morphology and Physiology of Pristine Bone
    (Sage, 2021) Pilawski, I.; Tulu, U. S.; Ticha, P.; Schüpbach, P.; Traxler, H.; Xu, Q.; Pan, J.; Coyac, B. R.; Yuan, X.; Tian, Y.; Liu, Y.; Chen, J.; Erdogan, Y.; Arioka, M.; Armaro, M.; Wu, M.; Brunski, J. B.; Helms, J. A.; Otolaryngology -- Head and Neck Surgery, School of Medicine
    Introduction: Few interspecies comparisons of alveolar bone have been documented, and this knowledge gap raises questions about which animal models most accurately represent human dental conditions or responses to surgical interventions. Objectives: The objective of this study was to employ state-of-the-art quantitative metrics to directly assess and compare the structural and functional characteristics of alveolar bone among humans, mini pigs, rats, and mice. Methods: The same anatomic location (i.e., the posterior maxillae) was analyzed in all species via micro-computed tomographic imaging, followed by quantitative analyses, coupled with histology and immunohistochemistry. Bone remodeling was evaluated with alkaline phosphatase activity and tartrate-resistant acid phosphatase staining to identify osteoblast and osteoclast activities. In vivo fluorochrome labeling was used as a means to assess mineral apposition rates. Results: Collectively, these analyses demonstrated that bone volume differed among the species, while bone mineral density was equal. All species showed a similar density of alveolar osteocytes, with a highly conserved pattern of collagen organization. Collagen maturation was equal among mouse, rat, and mini pig. Bone remodeling was a shared feature among the species, with morphologically indistinguishable hemiosteonal appearances, osteocytic perilacunar remodeling, and similar mineral apposition rates in alveolar bone. Conclusions: Our analyses demonstrated equivalencies among the 4 species in a plurality of the biological features of alveolar bone. Despite contradictory results from older studies, we found no evidence for the superiority of pig models over rodent models in representing human bone biology. Knowledge transfer statement: Animal models are extensively used to evaluate bone tissue engineering strategies, yet there are few state-of-the-art studies that rigorously compare and quantify the factors influencing selection of a given animal model. Consequently, there is an urgent need to assess preclinical animal models for their predictive value to dental research. Our article addresses this knowledge gap and, in doing so, provides a foundation for more effective standardization among animal models commonly used in dentistry.
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    Predicting Hazardous Driving Events Using Multi-Modal Deep Learning Based on Video Motion Profile and Kinematics Data
    (IEEE, 2018-11) Gao, Z.; Liu, Y.; Zheng, J. Y.; Yu, R.; Wang, X.; Sun, P.; Computer and Information Science, School of Science
    As the raising of traffic accidents caused by commercial vehicle drivers, more regulations have been issued for improving their safety status. Driving record instruments are required to be installed on such vehicles in China. The obtained naturalistic driving data offer insight into the causal factors of hazardous events with the requirements to identify where hazardous events happen within large volumes of data. In this study, we develop a model based on a low-definition driving record instrument and the vehicle kinematic data for post-accident analysis by multi-modal deep learning method. With a higher camera position on commercial vehicles than cars that can observe further distance, motion profiles are extracted from driving video to capture the trajectory features of front vehicles at different depths. Then random forest is used to select significant kinematic variables which can reflect the potential crash. Finally, a multi-modal deep convolutional neural network (DCNN) combined both video and kinematic data is developed to identify potential collision risk in each 12-second vehicle trip. The analysis results indicate that the proposed multi-modal deep learning model can identify hazardous events within a large volumes of data at an AUC of 0.81, which outperforms the state-of-the-art random forest model and kinematic threshold method.
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    Whole-exome sequencing and imaging genetics identify functional variants for rate of change in hippocampal volume in mild cognitive impairment
    (Springer Nature, 2013) Nho, K.; Corneveaux, J. J.; Kim, S.; Lin, H.; Risacher, S. L.; Shen, L.; Swaminathan, S.; Ramanan, V. K.; Liu, Y.; Foroud, T.; Inlow, M. H.; Siniard, A. L.; Reiman, R. A.; Aisen, P. S.; Petersen, R. C.; Green, R. C.; Jack, C. R.; Weiner, M. W.; Baldwin, C. T.; Lunetta, K.; Farrer, L. A.; Multi-Institutional Research on Alzheimer Genetic Epidemiology (MIRAGE) Study; Furney, S. J.; Lovestone, S.; Simmons, A.; Mecocci, P.; Vellas, B.; Tsolaki, M.; Kloszewska, I.; Soininen, H.; AddNeuroMed Consortium; McDonald, B. C.; Farlow, M. R.; Ghetti, B.; Indiana Memory and Aging Study; Huentelman, M. J.; Saykin, A. J.; Alzheimer's Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Whole-exome sequencing of individuals with mild cognitive impairment, combined with genotype imputation, was used to identify coding variants other than the apolipoprotein E (APOE) ε4 allele associated with rate of hippocampal volume loss using an extreme trait design. Matched unrelated APOE ε3 homozygous male Caucasian participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were selected at the extremes of the 2-year longitudinal change distribution of hippocampal volume (eight subjects with rapid rates of atrophy and eight with slow/stable rates of atrophy). We identified 57 non-synonymous single nucleotide variants (SNVs) which were found exclusively in at least 4 of 8 subjects in the rapid atrophy group, but not in any of the 8 subjects in the slow atrophy group. Among these SNVs, the variants that accounted for the greatest group difference and were predicted in silico as 'probably damaging' missense variants were rs9610775 (CARD10) and rs1136410 (PARP1). To further investigate and extend the exome findings in a larger sample, we conducted quantitative trait analysis including whole-brain search in the remaining ADNI APOE ε3/ε3 group (N=315). Genetic variation within PARP1 and CARD10 was associated with rate of hippocampal neurodegeneration in APOE ε3/ε3. Meta-analysis across five independent cross sectional cohorts indicated that rs1136410 is also significantly associated with hippocampal volume in APOE ε3/ε3 individuals (N=923). Larger sequencing studies and longitudinal follow-up are needed for confirmation. The combination of next-generation sequencing and quantitative imaging phenotypes holds significant promise for discovery of variants involved in neurodegeneration.