Development of the catecholamine innervation of the supraoptic nucleus in the Brattleboro rat

The ontogenetic development of the noradrenergic innervation of the supraoptic nucleus was studied in the Brattleboro rat at late postcoital and early postnatal ages. This genetic mutant offers a useful model for analysis of neuronal development because of the absence of a specific peptide component of identifiable target neurons and has been used presently to eliminate the possibility that such substances are essential for the establishment of normal connectivity during postnatal development. In this model, catecholamine varicosities were seen in juxtaposition to vasopressin-deficient perikarya during the initial phases of postnatal development, but these varicosities gradually decreased in number suggesting the possibility that the target neuron peptide, or some functional aspect of the neuron, may be necessary for the normal maintenance of this neuronal interaction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24975/1/0000402.pd

Comparison of Fetal Mesencephalic Grafts, AAV-delivered GDNF, and Both Combined in an MPTP-induced Nonhuman Primate Parkinson’s Model

We combined viral vector delivery of human glial-derived neurotrophic factor (GDNF) with the grafting of dopamine (DA) precursor cells from fetal ventral mesencephalon (VM) to determine whether these strategies would improve the anti-Parkinson's effects in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys, an animal model for Parkinson's disease (PD). Both strategies have been reported as individually beneficial in animal models of PD, leading to clinical studies. GDNF delivery has also been reported to augment VM tissue implants, but no combined studies have been done in monkeys. Monkeys were treated with MPTP and placed into four balanced treatment groups receiving only recombinant adeno-associated virus serotype 5 (rAAV5)/hu-GDNF, only fetal DA precursor cells, both together, or a buffered saline solution (control). The combination of fetal precursors with rAAV5/hu-GDNF showed significantly higher striatal DA concentrations compared with the other treatments, but did not lead to greater functional improvement in this study. For the first time under identical conditions in primates, we show that all three treatments lead to improvement compared with control animals

Human Neural Stem Cells Survive Long Term in the Midbrain of Dopamine-Depleted Monkeys After GDNF Overexpression and Project Neurites Toward an Appropriate Target

Transplanted multipotent human fetal neural stem cells (hfNSCs) significantly improved the function of parkinsonian monkeys in a prior study primarily by neuroprotection, with only 3%–5% of cells expressing a dopamine (DA) phenotype. In this paper, we sought to determine whether further manipulation of the neural microenvironment by overexpression of a developmentally critical molecule, glial cell-derived neurotrophic factor (GDNF), in the host striatum could enhance DA differentiation of hfNSCs injected into the substantia nigra and elicit growth of their axons to the GDNF-expressing target. hfNSCs were transplanted into the midbrain of 10 green monkeys exposed to 1-methyl-4-phenyl-1,2,3,6-tetrahydro-pyridine. GDNF was delivered concomitantly to the striatum via an adeno-associated virus serotype 5 vector, and the fate of grafted cells was assessed after 11 months. Donor cells remained predominantly within the midbrain at the injection site and sprouted numerous neurofilament-immunoreactive fibers that appeared to course rostrally toward the striatum in parallel with tyrosine hydroxylase-immunoreactive fibers from the host substantia nigra but did not mature into DA neurons. This work suggests that hfNSCs can generate neurons that project long fibers in the adult primate brain. However, in the absence of region-specific signals and despite GDNF overexpression, hfNSCs did not differentiate into mature DA neurons in large numbers. It is encouraging, however, that the adult primate brain appeared to retain axonal guidance cues. We believe that transplantation of stem cells, specifically instructed ex vivo to yield DA neurons, could lead to reconstruction of some portion of the nigrostriatal pathway and prove beneficial for the parkinsonian condition

Independent test assessment using the extreme value distribution theory

Abstract The new generation of whole genome sequencing platforms offers great possibilities and challenges for dissecting the genetic basis of complex traits. With a very high number of sequence variants, a naïve multiple hypothesis threshold correction hinders the identification of reliable associations by the overreduction of statistical power. In this report, we examine 2 alternative approaches to improve the statistical power of a whole genome association study to detect reliable genetic associations. The approaches were tested using the Genetic Analysis Workshop 19 (GAW19) whole genome sequencing data. The first tested method estimates the real number of effective independent tests actually being performed in whole genome association project by the use of an extreme value distribution and a set of phenotype simulations. Given the familiar nature of the GAW19 data and the finite number of pedigree founders in the sample, the number of correlations between genotypes is greater than in a set of unrelated samples. Using our procedure, we estimate that the effective number represents only 15 % of the total number of independent tests performed. However, even using this corrected significance threshold, no genome-wide significant association could be detected for systolic and diastolic blood pressure traits. The second approach implements a biological relevance-driven hypothesis tested by exploiting prior computational predictions on the effect of nonsynonymous genetic variants detected in a whole genome sequencing association study. This guided testing approach was able to identify 2 promising single-nucleotide polymorphisms (SNPs), 1 for each trait, targeting biologically relevant genes that could help shed light on the genesis of the human hypertension. The first gene, PFH14, associated with systolic blood pressure, interacts directly with genes involved in calcium-channel formation and the second gene, MAP4, encodes a microtubule-associated protein and had already been detected by previous genome-wide association study experiments conducted in an Asian population. Our results highlight the necessity of the development of alternative approached to improve the efficiency on the detection of reasonable candidate associations in whole genome sequencing studies.http://deepblue.lib.umich.edu/bitstream/2027.42/134747/1/12919_2016_Article_38.pd

Eight common genetic variants associated with serum dheas levels suggest a key role in ageing mechanisms

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands-yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10-36), SULT2A1 (rs2637125; p = 2.61×10-19), ARPC1A (rs740160; p = 1.56×10-16), TRIM4 (rs17277546; p = 4.50×10-11), BMF (rs7181230; p = 5.44×10-11), HHEX (rs2497306; p = 4.64×10-9), BCL2L11 (rs6738028; p = 1.72×10-8), and CYP2C9 (rs2185570; p = 2.29×10-8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS

Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies

Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation

Variants in KCNQ1 increase type II diabetes susceptibility in South Asians: A study of 3,310 subjects from India and the US

<p>Abstract</p> <p>Background</p> <p>Polymorphisms in intron 15 of potassium voltage-gated channel, KQT-like subfamily member 1 (<it>KCNQ1</it>) gene have been associated with type II diabetes (T2D) in Japanese genome-wide association studies (GWAS). More recently a meta-analysis of European GWAS has detected a new independent signal associated with T2D in intron 11 of the <it>KCNQ1 </it>gene. The purpose of this investigation is to examine the role of these variants with T2D in populations of Asian Indian descent from India and the US.</p> <p>Methods</p> <p>We examined the association between four variants in the <it>KCNQ1 </it>gene with T2D and related quantitative traits in a total of 3,310 Asian Indian participants from two different cohorts comprising 2,431 individuals of the Punjabi case-control cohort from the Sikh Diabetes Study and 879 migrant Asian Indians living in the US.</p> <p>Results</p> <p>Our data confirmed the association of a new signal at the <it>KCNQ1 </it>locus (rs231362) with T2D showing an allelic odds ratio (OR) of 1.24 95%CI [1.08-1.43], p = 0.002 in the Punjabi cohort. A moderate association with T2D was also seen for rs2237895 in the Punjabi (OR 1.14; p = 0.036) and combined cohorts (meta-analysis OR 1.14; p = 0.018). Three-site haplotype analysis of rs231362, rs2237892, rs2237895 exhibited considerably stronger evidence of association of the GCC haplotype with T2D showing OR of 1.24 95%CI [1.00-1.53], p = 0.001, permutation p = 8 × 10^-4in combined cohorts. The 'C' risk allele carriers of rs2237895 had significantly reduced measures of HOMA-B in the US cohort (p = 0.008) as well as in combined cohort in meta-analysis (p = 0.009).</p> <p>Conclusions</p> <p>Our investigation has confirmed that the variation within the <it>KCNQ1 </it>locus confers a significant risk to T2D among Asian Indians. Haplotype analysis further suggested that the T2D risk associated with <it>KCNQ1 </it>SNPs may be derived from 'G' allele of rs231362 and 'C' allele of rs2237895 and this appears to be mediated through β cell function.</p

Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations

BACKGROUND: Meta-analysis is the systematic and quantitative synthesis of effect sizes and the exploration of their diversity across different studies. Meta-analyses are increasingly applied to synthesize data from genome-wide association (GWA) studies and from other teams that try to replicate the genetic variants that emerge from such investigations. Between-study heterogeneity is important to document and may point to interesting leads. METHODOLOGY/PRINCIPAL FINDINGS: To exemplify these issues, we used data from three GWA studies on type 2 diabetes and their replication efforts where meta-analyses of all data using fixed effects methods (not incorporating between-study heterogeneity) have already been published. We considered 11 polymorphisms that at least one of the three teams has suggested as susceptibility loci for type 2 diabetes. The I2 inconsistency metric (measuring the amount of heterogeneity not due to chance) was different from 0 (no detectable heterogeneity) for 6 of the 11 genetic variants; inconsistency was moderate to very large (I2 = 32-77%) for 5 of them. For these 5 polymorphisms, random effects calculations incorporating between-study heterogeneity revealed more conservative p-values for the summary effects compared with the fixed effects calculations. These 5 associations were perused in detail to highlight potential explanations for between-study heterogeneity. These include identification of a marker for a correlated phenotype (e.g. FTO rs8050136 being associated with type 2 diabetes through its effect on obesity); differential linkage disequilibrium across studies of the identified genetic markers with the respective culprit polymorphisms (e.g., possibly the case for CDKAL1 polymorphisms or for rs9300039 and markers in linkage disequilibrium, as shown by additional studies); and potential bias. Results were largely similar, when we treated the discovery and replication data from each GWA investigation as separate studies. SIGNIFICANCE: Between-study heterogeneity is useful to document in the synthesis of data from GWA investigations and can offer valuable insights for further clarification of gene-disease associations

Direct reprogramming of human fibroblasts into dopaminergic neuron-like cells

Transplantation of exogenous dopaminergic neuron (DA neurons) is a promising approach for treating Parkinson's disease (PD). However, a major stumbling block has been the lack of a reliable source of donor DA neurons. Here we show that a combination of five transcriptional factors Mash1, Ngn2, Sox2, Nurr1, and Pitx3 can directly and effectively reprogram human fibroblasts into DA neuron-like cells. The reprogrammed cells stained positive for various markers for DA neurons. They also showed characteristic DA uptake and production properties. Moreover, they exhibited DA neuron-specific electrophysiological profiles. Finally, they provided symptomatic relief in a rat PD model. Therefore, our directly reprogrammed DA neuron-like cells are a promising source of cell-replacement therapy for PD

Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain

Our knowledge of the transcriptome has become much more complex since the days of the central dogma of molecular biology. We now know that splicing takes place to create potentially thousands of isoforms from a single gene, and we know that RNA does not always faithfully recapitulate DNA if RNA editing occurs. Collectively, these observations show that the transcriptome is amazingly rich with intricate regulatory mechanisms for overall gene expression, splicing, and RNA editing. Genetic variability can play a role in controlling gene expression, which can be identified by examining expression quantitative trait loci (eQTLs). eQTLs are genomic regions where genetic variants, including single nucleotide polymorphisms (SNPs) show a statistical association with expression of mRNA transcripts. In humans, many SNPs are also associated with disease, and have been identified using genome wide association studies (GWAS) but the biological effects of those SNPs are usually not known. If SNPs found in GWAS are also found in eQTLs, then one could hypothesize that expression levels may contribute to disease risk. Performing eQTL analysis with GWAS SNPs in both blood and brain, specifically the frontal cortex and the cerebellum, we found both shared and tissue unique eQTLS. The identification of tissue-unique eQTLs supports the argument that choice of tissue type is important in eQTL studies (Paper I). Aging is a complex process with the mechanisms underlying aging still being poorly defined. There is evidence that the transcriptome changes with age, and hence we used the brain dataset from our first paper as a discovery set, with an additional replication dataset, to investigate any aging-gene expression associations. We found evidence that many genes were associated with aging. We further found that there were more statically significant expression changes in the frontal cortex versus the cerebellum, indicating that brain regions may age at different rates. As the brain is a heterogeneous tissue including both neurons and non-neuronal cells, we used LCM to capture Purkinje cells as a representative neuronal type and repeated the age analysis. Looking at the discovery, replication and Purkinje cell datasets we found five genes with strong, replicated evidence of age-expression associations (Paper II). Being able to capture and quantify the depth of the transcriptome has been a lengthy process starting with methods that could only measure a single gene to genome-wide techniques such as microarray. A recently developed technology, RNA-Seq, shows promise in its ability to capture expression, splicing, and editing and with its broad dynamic range quantification is accurate and reliable. RNA-Seq is, however, data intensive and a great deal of computational expertise is required to fully utilize the strengths of this method. We aimed to create a small, well-controlled, experiment in order to test the performance of this relatively new technology in the brain. We chose embryonic versus adult cerebral cortex, as mice are genetically homogenous and there are many known differences in gene expression related to brain development that we could use as benchmarks for analysis testing. We found a large number of differences in total gene expression between embryonic and adult brain. Rigorous technical and biological validation illustrated the accuracy and dynamic range of RNA-Seq. We were also able to interrogate differences in exon usage in the same dataset. Finally we were able to identify and quantify both well-known and novel A-to-I edit sites. Overall this project helped us develop the tools needed to build usable pipelines for RNA-Seq data processing (Paper III). Our studies in the developing brain (Paper III) illustrated that RNA-Seq was a useful unbiased method for investigating RNA editing. To extend this further, we utilized a genetically modified mouse model to study the transcriptomic role of the RNA editing enzyme ADAR2. We found that ADAR2 was important for editing of the coding region of mRNA as a large proportion of RNA editing sites in coding regions had a statistically significant decrease in editing percentages in Adar2 -/-Gria2 R/R mice versus controls. However, despite indications in the literature that ADAR2 may also be involved in splicing and expression regulatory machinery we found no changes in gene expression or exon utilization in Adar2 -/-Gria2 R/R mice as compared to their littermate controls (Paper IV). In our final study, based on the methods developed in Papers III and IV, we revisited the idea of age related gene expression associations from Paper II. We used a subset of human frontal cortices for RNA sequencing. Interestingly we found more gene expression changes with aging compared to the previous data using microarrays in Paper II. When the significant gene lists were analysed for gene ontology enrichment, we found that there was a large number of downregulated genes involved in synaptic function while those that were upregulated had enrichment in immune function. This dataset illustrates that the aging brain may be predisposed to the processes found in neurodegenerative diseases (Paper V)