Identification and Functional Analysis of Genes Involved in Gliomagenesis

The median survival of glioma patient is still very poor and new therapeutic targets have to be discovered. The aim of this thesis is to identify genetic alterations in glioma and functionally characterize the most promising candidates. We describe several novel methods used to identify these mutations

Food Security Crop Price Transmission and Formation in Nigeria

The three studies in this dissertation explore the current conditions and operations of markets for seven key food security crops (cassava, cowpeas, maize, millet, rice, sorghum, and yams) in Nigeria. Chapter 2 is an empirical analysis of the current agricultural statistics system in Nigeria. A number of sources gather and report agricultural statistics for the country. Since there has not been an agricultural census implemented there for multiple decades, however, there is no objective source for data verification. Therefore, this study uses two additional types of “on the ground information” to assess if agricultural production estimates reflect growing conditions: prices and remote sensing data in the form of the normalized difference vegetation index (NDVI). The results show that existing production estimates are poorly correlated with both prices and the NDVI. Prices and the NDVI data are highly correlated, however. These findings imply that existing production estimates do not reflect growing conditions, and, therefore, are of poor quality. Chapter 3 is a comprehensive analysis of crop price transmission from global and neighbor country prices to Nigerian commercial hub and urban markets, and from commercial hubs to other urban and rural markets within the country. The results show that tradability matters for price transmission, but that tradability varies across crops and scopes of markets. Nigerian urban rice prices are highly correlated with prices on global markets and those in neighboring countries. Coarse grain prices appear disconnected from global markets, however, but move closely with those in neighboring countries. Large margins were estimated for prices of rice imported from global markets (in all regions), and for coarse grains to Southern Nigerian markets only. The existence of large margins implies that there are transactions costs and/or quality premiums that vary systematically with the world price, and/or mark-ups by traders with market power in these markets. While domestic market prices are almost always cointegrated, perfect price transmission is generally found only between commercial hubs and other urban markets. Moreover, long lags were found for price transmission across all scopes of markets, but especially between urban and rural prices in some regions. These results imply that local conditions (e.g., weather) are relatively more important than external market prices for explaining price variation in rural markets, especially in the short-run. Chapter 4 incorporates NDVI data into price formation models to estimate whether observable growing conditions explain price variation in Nigerian food security crop markets. Four issues related to use of NDVI data that exist within the literature are investigated: whether NDVI is a valid proxy for expected production, how NDVI is a proxy for seasonality, the relationship between market size and the area scope used to average NDVI values across space, and if anomalous harvest expectations can change long-run price variation and price relationships between markets. The results show that information on growing conditions is more informative for isolated than interconnected markets. Even for those local prices, however, other non-weather and non-external market price factors are relatively more important for explanation of price variation. An implication of these results is that Nigeria cannot plausibly rely solely on direct imports from global markets to meet short-run demand during future weather shock periods. Thus, storage is required to ensure stability of food security, either for imports or domestically produced surpluses acquired in non-crisis periods. Given the isolation of rural markets, local and on-farm stocks are at least as important as large facilities in commercial hubs. Improvement of village level and on-farm storage systems and elimination of other market distortions that inhibit trade between urban and rural markets would make public storage less needed. The findings on poor quality of agricultural statistics indicate a clear priority to improve agricultural data, to facilitate better planning of any food security strategies. A combination of surveys with remote sensed and crowd sourced data may improve feasibility in the funding constrained environment

Pleiotropic contribution of MECOM and AVPR1A to aggression and subcortical brain volumes

Reactive and proactive subtypes of aggression have been recognized to help parse etiological heterogeneity of this complex phenotype. With a heritability of about 50%, genetic factors play a role in the development of aggressive behavior. Imaging studies implicate brain structures related to social behavior in aggression etiology, most notably the amygdala and striatum. This study aimed to gain more insight into the pathways from genetic risk factors for aggression to aggression phenotypes. To this end, we conducted genome-wide gene-based cross-trait meta-analyses of aggression with the volumes of amygdala, nucleus accumbens and caudate nucleus to identify genes influencing both aggression and aggression-related brain volumes. We used data of large-scale genome-wide association studies (GWAS) of: (a) aggressive behavior in children and adolescents (EAGLE, N = 18,988); and (b) Magnetic Resonance Imaging (MRI)-based volume measures of aggression-relevant subcortical brain regions (ENIGMA2, N = 13,171). Second, the identified genes were further investigated in a sample of healthy adults (mean age (SD) = 25.28 (4.62) years; 43% male) who had genome-wide genotyping data and questionnaire data on aggression subtypes available (Brain Imaging Genetics, BIG, N = 501) to study their effect on reactive and proactive subtypes of aggression. Our meta-analysis identified two genes, MECOM and AVPR1A, significantly associated with both aggression risk and nucleus accumbens (MECOM) and amygdala (AVPR1A) brain volume. Subsequent in-depth analysis of these genes in healthy adults (BIG), including sex as an interaction term in the model, revealed no significant subtype-specific gene-wide associations. Using cross-trait meta-analysis of brain measures and psychiatric phenotypes, this study generated new hypotheses about specific links between genes, the brain and behavior. Results indicate that MECOM and AVPR1A may exert an effect on aggression through mechanisms involving nucleus accumbens and amygdala volumes, respectively

Relations between the milnor and quillen K-theory of fields

De novo mutations in specific mTOR pathway genes cause brain overgrowth in the context of intellectual disability (ID). By analyzing 101 mMTOR-related genes in a large ID patient cohort and two independent population cohorts, we show that these genes modulate brain growth in health and disease. We report the mTOR activator gene RHEB as an ID gene that is associated with megalencephaly when mutated. Functional testing of mutant RHEB in vertebrate animal models indicates pathway hyperactivation with a concomitant increase in cell and head size, aberrant neuronal migration, and induction of seizures, concordant with the human phenotype. This study reveals that tight control of brain volume is exerted through a large community of mTOR-related genes. Human brain volume can be altered, by either rare disruptive events causing hyperactivation of the pathway, or through the collective effects of common alleles

Exon expression arrays as a tool to identify new cancer genes

Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

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

Genetic Alterations in Glioma

Gliomas are the most common type of primary brain tumor and have a dismal prognosis. Understanding the genetic alterations that drive glioma formation and progression may help improve patient prognosis by identification of novel treatment targets. Recently, two major studies have performed in-depth mutation analysis of glioblastomas (the most common and aggressive subtype of glioma). This systematic approach revealed three major pathways that are affected in glioblastomas: The receptor tyrosine kinase signaling pathway, the TP53 pathway and the pRB pathway. Apart from frequent mutations in the IDH1/2 gene, much less is known about the causal genetic changes of grade II and III (anaplastic) gliomas. Exceptions include TP53 mutations and fusion genes involving the BRAF gene in astrocytic and pilocytic glioma subtypes, respectively. In this review, we provide an update on all common events involved in the initiation and/or progression across the different subtypes of glioma and provide future directions for research into the genetic changes

Isocitrate dehydrogenase-1 mutations: a fundamentally new understanding of diffuse glioma?

The discovery of somatic mutations in the gene encoding isocitrate dehydrogenase-1 (IDH1) in glioblastomas was remarkable because the enzyme was not previously identified with any known oncogenic pathway. IDH1 is mutated in up to 75% of grade II and grade III diffuse gliomas. Apart from acute myeloid leukaemia, other tumour types do not carry IDH1 mutations. Mutations in a homologous gene, IDH2, have also been identified, although they are much rarer. Although TP53 mutations and 1p/19q codeletions are mutually exclusive in gliomas, in both of these genotypes IDH1 mutations are common. IDH1 and IDH2 mutations are early events in the development of gliomas. Moreover, IDH1 and IDH2 mutations are a major prognostic marker for overall and progression-free survival in grade II-IV gliomas. Mutated IDH1 has an altered catalytic activity that results in the accumulation of 2-hydroxyglutarate. Molecularly, IDH1 and IDH2 mutations are heterozygous, affect only a single codon, and rarely occur together. Because IDH1 does not belong to a traditional oncogenic pathway and is specifically and commonly mutated in gliomas, the altered enzymatic activity of IDH1 may provide a fundamentally new understanding of diffuse glioma