News Article | April 25, 2017
The search for the genetic determinants of extreme longevity has been challenging, with the prevalence of centenarians (people older than 100) just one per 5,000 population in developed nations. But a recently published study by Boston University School of Public Health and School of Medicine researchers, which combines four studies of extreme longevity, has identified new rare variants in chromosomes 4 and 7 associated with extreme survival and with reduced risks for cardiovascular and Alzheimer's disease. The results, published in the Journals of Gerontology: Biological Sciences, highlight the importance of studying "truly rare survival, to discover combinations of common and rare variants associated with extreme longevity and longer health span," the authors said. The research group, led by Paola Sebastiani, professor of biostatistics the BU School of Public Health (BUSPH), created a consortium of four studies -- the New England Centenarian Study, the Long Life Family Study, the Southern Italian Centenarian Study, and the Longevity Gene Project - to build a large sample of 2,070 people who survived to the oldest one percentile of survival for the 1900 birth year cohort. The researchers conducted various analyses to discover longevity-associated variants (LAVs), and to characterize those LAVs that differentiated survival to extreme age. Their analysis identified new "extreme longevity-promoting variants" on chromosomes 4 and 7, while also confirming variants (SNPs, or single nucleotide polymorphisms) previously associated with longevity. In addition, in two of the datasets where researchers had age-of-onset data for age-related diseases, they found that certain longevity alleles also were significantly associated with reduced risks for cardiovascular disease and hypertension. "The data and survival analysis provide support for the hypothesis that the genetic makeup of extreme longevity is based on a combination of common and rare variants, with common variants that create the background to survive to relatively common old ages (e.g. into the 80s and 90s), and specific combinations of uncommon and rare variants that add an additional survival advantage to even older ages," the authors wrote. They said, however, that while the "yield of discovery" in the study was more substantial than in prior genome-wide association studies (GWAS) of extreme longevity, it remained disappointing, in that the two most significant genotypes discovered "are carried by a very small proportion of the cases included in the analysis," meaning that much of the genetic variability around extreme lifespan remains unexplained. "We expect that many more uncommon genetic variants remain to be discovered through sequencing of centenarian samples," they wrote. "Larger sample sizes are needed to detect association of rare variants. . . and therefore promising associations that miss the threshold for genome-wide significance are important to discuss." BU co-authors on the study include: Stacy Andersen, assistant professor of medicine at BUSM and study manager of the New England Centenarian Study; Thomas Perls, professor of medicine and geriatrics at BUSM and principal investigator of the New England Centenarian Study; and Anastasia Gurinovich, of the BU Bioinformatics Program. The study was supported by funding from the National Institute on Aging, the National Heart Lung Blood Institute, and the William Wood Foundation.
Briers D.,Bioinformatics Program |
Haghighi I.,Boston University |
White D.,Georgia Institute of Technology |
Kemp M.L.,Georgia Institute of Technology |
Belta C.,Boston University
2016 IEEE 55th Conference on Decision and Control, CDC 2016 | Year: 2016
Embryonic stem cells (ESC) are generally regarded as the smallest functional units necessary to reproduce multicellular systems such as tissues and organs. Recent work showed that agent-based models of the stochastic dynamics of locally interacting stem cell agents accurately capture the time-dependent distributions of a variety of spatial patterns. Starting from a 3-dimensional, local interaction model of ESC proliferation and differentiation, in this paper, we developed a pattern classification and parameter optimization approach to maximize the occurrence of desired morphogenic patterns. Our approach uses Particle Swarm Optimization (PSO) and a pattern classification method that exploits a quantitative characterization of pattern formation. Since patterning likely imprints subsequent choices that stem cell aggregates make in lineage specification (e.g. precursors of neurons, lung cells, or muscle cells), our parameter optimization approach can be used to synthesize global differentiation patterns through local cues. © 2016 IEEE.
Friese R.S.,University of California at San Diego |
Ye C.,Bioinformatics Program |
Schork A.J.,University of California at San Diego |
Mahapatra N.R.,Indian Institute of Technology Madras |
And 8 more authors.
Circulation: Cardiovascular Genetics | Year: 2012
Background: Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability. Methods and Results: We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We frst undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose. Conclusions: The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome. © 2012 American Heart Association, Inc.
News Article | November 10, 2016
PORTLAND, Ore, and LA JOLLA, Calif. - Families struggling with infertility or a genetic predisposition for debilitating mitochondrial diseases may someday benefit from a new breakthrough led by scientists at OHSU and the Salk Institute for Biological Studies. In a study to be published Thursday, Nov. 10 in the journal Cell Stem Cell, researchers discovered it's possible to regenerate human eggs or oocytes - the cellular beginning of an embryo - by making use of genetic material that normally goes to waste. This DNA comes from small cells called polar bodies that form off of eggs and contain the same genetic material as in a woman's egg nucleus. Until now, polar bodies had never been shown to be potentially useful for generating functional human eggs for fertility treatments. In the study, scientists successfully transplanted a polar body from a woman's developing oocyte into the cytoplasm of a donor oocyte stripped of its nucleus. Though the technique could be years away from progressing to clinical trials, the advancement eventually could be significant for women of advanced maternal age. One recent survey showed that the average age of first-time mothers increased in the United States from 21.4 years in 1970 to 25.0 years in 2006. "We know that fertility declines as women get older," said Shoukhrat Mitalipov, Ph.D., co- senior author and director of the OHSU Center for Embryonic Cell and Gene Therapy. "This is potentially a way to double the number of eggs we're able to get from one session of in vitro fertilization." "Although it was only possible to examine a limited number of lines, from the point of view of epigenomic profiles, the quality of polar body-derived embryonic cells looks quite promising," says co-senior author Joseph Ecker, Ph.D., Salk professor and director of the Genomic Analysis Laboratory. By rescuing polar bodies that would otherwise simply bud off the developing oocyte, researchers were able to form additional oocytes genetically related to the mother through nuclear transfer. When fertilized with sperm, the new oocytes developed into viable embryos. None of the embryos were implanted to carry out an actual pregnancy. "Normally, polar bodies disintegrate and disappear during egg development," said co-first author Hong Ma, M.D., Ph.D., with OHSU's Center for Embryonic Cell and Gene Therapy. "We were able to recycle them. We hope that by doing this, we can double the number of patient eggs available for in vitro fertilization." "This is the first investigation into the surprising viability of human polar bodies and it reveals a new source of previously discarded genetic material to study," says Ryan O'Neil, co-first author and Salk researcher. In addition to potentially benefitting women of advanced maternal age, the technique may present another opportunity to help women known to have mutations in their mitochondria, the tiny powerhouses inside nearly every cell of the body. Mutations in mitochondria can result in debilitating forms of disease in children. "This new technique maximizes the chances of families having a child through in vitro fertilization free of genetic mutations," Mitalipov said. Mitalipov previously developed a mitochondrial replacement therapy involving the implantation of patient's egg nucleus - or spindle - into a healthy donated egg stripped of its original nucleus. Mitalipov also has successfully demonstrated the spindle-transfer technique in the healthy offspring of rhesus macaque monkeys. In addition to Mitalipov, Ecker, Ma and O'Neil, authors of the study include Ryan C. O'Neil and Yupeng He, of the Genomic Analysis Laboratory at the Salk Institute and the Bioinformatics Program at the University of California and San Diego; Joseph R. Ecker, Ph.D., of the Salk Institute and Howard Hughes Medical Institute; Nuria Marti Gutierrez, Eunju Kang, Yeonmi Lee, Tomonari Hayama, M.D., Ph.D., Amy Koski, Rebecca Tippner-Hedges, Riffat Ahmed, Crystal Van Dyken, Ying Li, and Don P. Wolf, Ph.D., of the OHSU Center for Embryonic Cell and Gene Therapy; Manoj Hariharan, Ph.D., Zhuzhu Z. Zhang, Ph.D., Joseph Nery and Rosa Castanon, of the Salk Institute; Susan Olson, Ph.D., of the OHSU Department of Molecular and Medical Genetics; David Battaglia, Ph.D., H.C.L.D., David M. Lee, M.D., Diana H. Wu, M.D., and Paula Amato, M.D., of the OHSU Department of Obstetrics and Gynecology; and Cengiz Cinnioglu, Ph.D., and Refik Kayali, Ph.D., of IviGen Los Angeles.
Eurich C.,Elizabethtown Area High School |
Fields P.A.,Franklin And Marshall College |
Rice E.,Bioinformatics Program
American Biology Teacher | Year: 2012
Proteomics is an emerging area of systems biology that allows simultaneous study of thousands of proteins expressed in cells, tissues or whole organisms. We have developed this activity to enable high school or college students to explore proteomic databases using mass spectrometry data files generated from yeast proteins in a college laboratory course. Students upload files of "unknown" proteins from our public website, enter them into a proteomics search engine (Mascot), identify the proteins, and use additional proteomics websites to learn about their functions and three-dimensional structures. This activity is suitable for use in units exploring protein structure and function, metabolism, or bioinformatics. © 2012 by National Association of Biology Teachers. All rights reserved.
Chan W.H.,Bioinformatics Program |
Ebner J.,Golisano Institute for Sustainability |
Ramchandra R.,Golisano Institute for Sustainability |
Ramchandra R.,New York State Pollution Prevention Institute |
Trabold T.,Golisano Institute for Sustainability
ASME 2013 7th Int. Conf. on Energy Sustainability Collocated with the ASME 2013 Heat Transfer Summer Conf. and the ASME 2013 11th Int. Conf. on Fuel Cell Science, Engineering and Technology, ES 2013 | Year: 2013
Prior research conducted by our Institute has revealed the large quantities of food waste available in New York State, particularly in the Upstate corridor extending from Buffalo to Syracuse. The Finger Lakes region is heavily populated with agricultural operations, dairy farms and food processing plants, including those producing milk, yogurt, wine, and canned fruits and vegetables. The diverse supply of organic waste generated by these facilities offers the opportunity for sustainable energy production through one of three primary pathways: •Anaerobic digestion to produce methane •Fermentation to produce alcohols •Transesterification to produce biodiesel. Generally speaking, food wastes are better suited for biochemical conversion instead of thermo-chemical conversion (combustion, gasification, pyrolysis) due to their relatively high moisture content. The current paper provides an initial assessment of food wastes within the 9-County Finger Lakes region around Rochester, New York. Available databases were utilized to first identify all the relevant companies operating in one of four broad industry sectors: agriculture, food processing, food distribution and food services (including restaurants). Our analysis has demonstrated that anaerobic digestion can be a viable method for sustainable energy production from food waste in the Finger Lakes region, due to the dual economic benefits of effective disposal cost reduction and production of methane-rich biogas. Copyright © 2013 by ASME.
Reznik E.,Bioinformatics Program |
Reznik E.,Boston University |
Segre D.,Bioinformatics Program |
Segre D.,Boston University
Journal of Theoretical Biology | Year: 2010
We investigate the stability properties of two different classes of metabolic cycles using a combination of analytical and computational methods. Using principles from structural kinetic modeling (SKM), we show that the stability of metabolic networks with certain structural regularities can be studied using a combination of analytical and computational techniques. We then apply these techniques to a class of single input, single output metabolic cycles, and find that the cycles are stable under all conditions tested. Next, we extend our analysis to a small autocatalytic cycle, and determine parameter regimes within which the cycle is very likely to be stable. We demonstrate that analytical methods can be used to understand the relationship between kinetic parameters and stability, and that results from these analytical methods can be confirmed with computational experiments. In addition, our results suggest that elevated metabolite concentrations and certain crucial saturation parameters can strongly affect the stability of the entire metabolic cycle. We discuss our results in light of the possibility that evolutionary forces may select for metabolic network topologies with a high intrinsic probability of being stable. Furthermore, our conclusions support the hypothesis that certain types of metabolic cycles may have played a role in the development of primitive metabolism despite the absence of regulatory mechanisms. © 2010 Elsevier Ltd.
Xu L.,Bioinformatics Program
BMC genomics | Year: 2012
Gene expression data are noisy due to technical and biological variability. Consequently, analysis of gene expression data is complex. Different statistical methods produce distinct sets of genes. In addition, selection of expression p-value (EPv) threshold is somewhat arbitrary. In this study, we aimed to develop novel literature based approaches to integrate functional information in analysis of gene expression data. Functional relationships between genes were derived by Latent Semantic Indexing (LSI) of Medline abstracts and used to calculate the function cohesion of gene sets. In this study, literature cohesion was applied in two ways. First, Literature-Based Functional Significance (LBFS) method was developed to calculate a p-value for the cohesion of differentially expressed genes (DEGs) in order to objectively evaluate the overall biological significance of the gene expression experiments. Second, Literature Aided Statistical Significance Threshold (LASST) was developed to determine the appropriate expression p-value threshold for a given experiment. We tested our methods on three different publicly available datasets. LBFS analysis demonstrated that only two experiments were significantly cohesive. For each experiment, we also compared the LBFS values of DEGs generated by four different statistical methods. We found that some statistical tests produced more functionally cohesive gene sets than others. However, no statistical test was consistently better for all experiments. This reemphasizes that a statistical test must be carefully selected for each expression study. Moreover, LASST analysis demonstrated that the expression p-value thresholds for some experiments were considerably lower (p < 0.02 and 0.01), suggesting that the arbitrary p-values and false discovery rate thresholds that are commonly used in expression studies may not be biologically sound. We have developed robust and objective literature-based methods to evaluate the biological support for gene expression experiments and to determine the appropriate statistical significance threshold. These methods will assist investigators to more efficiently extract biologically meaningful insights from high throughput gene expression experiments.
Wu H.,Bioinformatics Program |
Palani A.,Bioinformatics Program
Proceedings - Frontiers in Education Conference, FIE | Year: 2015
The rapid advancement in biological data acquisition technologies has led to massive biological datasets, which requires the development and application of computational methods to analyze and interpret the information. Bioinformatics is the confluence of biology, computer science, and information technology. The Bioinformatics programs are offered by more than 100 universities in the United States, and much more worldwide. Different degree (including BS, MS, and PhD), and certificate programs in Bioinformatics have been performed. The current bioinformatics programs in the US have been studied, regarding their curriculum, program competencies, sizes of the faculty, and student enrollments. The job market is also explored for bioinformatics professional training and career planning. The bioinformatics skill requirements are analyzed. Systematical analysis is carried out by integrating the core competences and curriculum improvements in bioinformatics. The potential employers for bioinformatics professionals are analyzed according to the properties of the companies, such as the sizes, the focus areas, the locations, the skill requirements, and other information. The results provide guidance for bioinformatics curriculum development, such as the minimized courses to cover the basic required skill sets for a bioinformatics student to be a successful bioinformatician. In addition, the analytical results are applied to the redesign of the curriculum in our bioinformatics program which offers MS, PhD, and PhD Minor. In summary, the systematic study of the existing bioinformatics programs in the US and the current market needs for professionals in bioinformatics provide great insight for education in bioinformatics. It helps the curriculum development and reexamination. It also provides the students with the required knowledge for their future career. © 2015 IEEE.
PubMed | Bioinformatics Program
Type: Journal Article | Journal: Journal of theoretical biology | Year: 2010
We investigate the stability properties of two different classes of metabolic cycles using a combination of analytical and computational methods. Using principles from structural kinetic modeling (SKM), we show that the stability of metabolic networks with certain structural regularities can be studied using a combination of analytical and computational techniques. We then apply these techniques to a class of single input, single output metabolic cycles, and find that the cycles are stable under all conditions tested. Next, we extend our analysis to a small autocatalytic cycle, and determine parameter regimes within which the cycle is very likely to be stable. We demonstrate that analytical methods can be used to understand the relationship between kinetic parameters and stability, and that results from these analytical methods can be confirmed with computational experiments. In addition, our results suggest that elevated metabolite concentrations and certain crucial saturation parameters can strongly affect the stability of the entire metabolic cycle. We discuss our results in light of the possibility that evolutionary forces may select for metabolic network topologies with a high intrinsic probability of being stable. Furthermore, our conclusions support the hypothesis that certain types of metabolic cycles may have played a role in the development of primitive metabolism despite the absence of regulatory mechanisms.