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https://griffinshare.fontbonne.edu/fas-205-projects/1006/thumbnail.jp

Clustered Coding Variants in the Glutamate Receptor Complexes of Individuals with Schizophrenia and Bipolar Disorder

Current models of schizophrenia and bipolar disorder implicate multiple genes, however their biological relationships remain elusive. To test the genetic role of glutamate receptors and their interacting scaffold proteins, the exons of ten glutamatergic ‘hub’ genes in 1304 individuals were re-sequenced in case and control samples. No significant difference in the overall number of non-synonymous single nucleotide polymorphisms (nsSNPs) was observed between cases and controls. However, cluster analysis of nsSNPs identified two exons encoding the cysteine-rich domain and first transmembrane helix of GRM1 as a risk locus with five mutations highly enriched within these domains. A new splice variant lacking the transmembrane GPCR domain of GRM1 was discovered in the human brain and the GRM1 mutation cluster could perturb the regulation of this variant. The predicted effect on individuals harbouring multiple mutations distributed in their ten hub genes was also examined. Diseased individuals possessed an increased load of deleteriousness from multiple concurrent rare and common coding variants. Together, these data suggest a disease model in which the interplay of compound genetic coding variants, distributed among glutamate receptors and their interacting proteins, contribute to the pathogenesis of schizophrenia and bipolar disorders

Place-Based Learning Communities on a Rural Campus: Turning Challenges into Assets

At Humboldt State University (HSU), location is everything. Students are as drawn to our spectacular natural setting as they are to the unique majors in the natural resource sciences that the university has to offer. However, the isolation that nurtures the pristine natural beauty of the area presents a difficult reality for students who are accustomed to more densely populated environments. With the large majority of our incoming students coming from distant cities, we set out to cultivate a “home away from home” by connecting first-year students majoring in science, technology, engineering and math (STEM) to the communities and local environment of Humboldt County. To achieve this, we designed first-year place-based learning communities (PBLCs) that integrate unique aspects and interdisciplinary themes of our location throughout multiple high impact practices, including a summer experience, blocked-enrolled courses, and a first-year experience course entitled Science 100: Becoming a STEM Professional in the 21st Century. Native American culture, traditional ways of knowing, and contemporary issues faced by tribal communities are central features of our place-based curriculum because HSU is located on the ancestral land of the Wiyot people and the university services nine federally recognized American Indian tribes. Our intention is that by providing a cross-cultural, validating environment, students will: feel and be better supported in their academic pursuits; cultivate values of personal, professional and social responsibility; and increase the likelihood that they will complete their HSU degree. As we complete the fourth year of implementation, we aim to harness our experience and reflection to improve our programming and enable promising early results to be sustained

Hyperpolarized 13C MRI: Path to Clinical Translation in Oncology.

This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging's (MRI's) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind

Hyperpolarized ¹³C MRI: Path to Clinical Translation in Oncology

This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging’s (MRI’s) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind

Variability in Working Memory Performance Explained by Epistasis vs Polygenic Scores in the ZNF804A Pathway

Importance: We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. Objectives To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. Design, Setting, and Participants: Patients with psychosis (n = 424) were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition. We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). Main Outcomes and Measures: Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. Results: Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1% to 3% of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2% using the polygenic score only to 4.8% (P = .11 and .001, respectively) but did not explain additional variation in control participants. Conclusions and Relevance: These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building