Computers and mathematics are forging a new revolution in biology and medicine. These fields are providing insights that would be near-impossible to deduce from traditional scientific approaches. The future is indeed very bright for curing some of the most devastating human diseases.
NeuroTexas Institute has established the first computational neuroscience research center in Central Texas. The core focus of the Center for Computational Neuroscience is to develop a wide range of computational tools with which to further our understanding of neurological diseases and disorders, and improve the quality of care provided to patients.
NeuroTexas Institute scientists are also working to create new statistical methods to increase the power of genome-wide association studies (GWAS). The first disease on which our models are being developed is autism, a neurological disorder that affects about 6 in every 1,000 children. This collaboration promises to greatly expand our understanding about autism genetics, and the methods developed are expected to be applicable to other diseases.
Evidence-Based Medicine
Researchers in the Center for Computational Neuroscience are working with researchers in the Center for Evidence-Based Medicine to develop an innovative database system to prospectively capture detailed clinical information about neurosciences patients. This database will allow us to collect data that is custom tailored to specific research questions on the brain and spine that are not amenable to classical research approaches. Using this database will allow scientists to unearth new research information about how medical treatments impact patient’s health and recovery.
Genome-wide association studies (GWAS)
Genome-wide association (GWA) studies are becoming a powerful and cost-effective approach to identifying the genes and molecules underlying human traits, including disease. GWA studies have many advantages over classical genetic approaches, but most notable is that such studies can survey an entire human genome in a matter of two hours for about $500. Consider that roughly ten years ago the first human genome was sequenced after 2-5 years of effort and tens of millions of dollars.
The GWA approach provides scientists with an unprecedented window through which to peer into our genetic content. To date, many common human traits such as hair color and many major disease have been studied through a GWA analysis (see this compilation for the genetic locations of numerous traits). The GWA framework has many potential applications in healthcare, and more will become possible as the technology continues to mature. Indeed, the technology is poised to become an important weapon in the arsenal of clinicians to diagnose and treat a wide array of diseases. For example, GWAS technologies are being used to identify genetic markers that increase an individual’s risk of developing an aggressive form of brain cancer; once validated, such markers could be easily screened to inform individuals about their risks.
At NeuroTexas Institute, novel GWAS studies are currently in the works. We are currently planning to conduct a genetic screen for markers associated with long-term phantom pain in amputees. The markers identified through this screen should provide deeper insight into the biology of this disease and pave the way for better therapies for amputees afflicted with this neuropathic disease. We are also considering GWA studies related to glioblastoma multiformae, a deadly form of brain cancer.
The future is bright for unraveling the genetic circuits underlying human disease, and ultimately paving the road to a new era of medicine. To learn more about GWA studies, consider reading this recent article from the NeuroTexas Institute Center for Computational Neuroscience.
Publications:
The Association Between Weather and Spontaneous Subarachnoid Hemorrhage: An Analysis of 155 United States Hospitals. Cowperthwaite MC, Burnett, MG. Neurosurgery (in press).
Abstract:
Objective: A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (SAH) has been suggested, but a consensus within the literature has yet to emerge. The present study examines the impact of weather patterns on the incidence of SAH utilizing a geographically broad analysis of hospital admissions and represents the largest study of the topic to date.
Genome-wide association studies: a powerful tool for neurogenomics. Cowperthwaite MC, Mohanty D, Burnett MG. Neurosurg Focus (2010). 28(1):E2.
Abstract:
As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetics tests for clinicians.
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The ascent of the abundant: how mutational networks constrain evolution. Cowperthwaite MC, Economo EP, Harcombe WR, Miller EL, Meyers LA. PLoS Comput Biol (2008). 4(7): e1000110.
Abstract:
Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance--the number of genotypes producing a particular phenotype--varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an "ascent of the abundant" hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit. PMID: 18636097
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Bioinformatic analysis of the contribution of primer sequences to aptamer structures. Cowperthwaite MC, Ellington AD. J Mol Evol (2008). 67(1):95-102.
Abstract:
Aptamers are nucleic acid molecules selected in vitro to bind a particular ligand. While numerous experimental studies have examined the sequences, structures, and functions of individual aptamers, considerably fewer studies have applied bioinformatics approaches to try to infer more general principles from these individual studies. We have used a large Aptamer Database to parse the contributions of both random and constant regions to the secondary structures of more than 2000 aptamers. We find that the constant, primer-binding regions do not, in general, contribute significantly to aptamer structures. These results suggest that (a) binding function is not contributed to nor constrained by constant regions; (b) in consequence, the landscape of functional binding sequences is sparse but robust, favoring scenarios for short, functional nucleic acid sequences near origins; and (c) many pool designs for the selection of aptamers are likely to prove robust
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