Microglia in Brain Development, Homeostasis, and Neurodegeneration

2019 ◽  
Vol 53 (1) ◽  
pp. 263-288 ◽  
Author(s):  
Christopher J. Bohlen ◽  
Brad A. Friedman ◽  
Borislav Dejanovic ◽  
Morgan Sheng
Keyword(s):  
Alzheimer Disease ◽  
Brain Development ◽  
Neurodegenerative Disease ◽  
Human Genetics ◽  
Association Studies ◽  
Therapeutic Interventions ◽  
Genome Wide Association Studies ◽  
Expression Studies ◽  
Genome Wide ◽  
Gene Expression Studies

Advances in human genetics have implicated a growing number of genes in neurodegenerative diseases, providing insight into pathological processes. For Alzheimer disease in particular, genome-wide association studies and gene expression studies have emphasized the pathogenic contributions from microglial cells and motivated studies of microglial function/dysfunction. Here, we summarize recent genetic evidence for microglial involvement in neurodegenerative disease with a focus on Alzheimer disease, for which the evidence is most compelling. To provide context for these genetic discoveries, we discuss how microglia influence brain development and homeostasis, how microglial characteristics change in disease, and which microglial activities likely influence the course of neurodegeneration. In all, we aim to synthesize varied aspects of microglial biology and highlight microglia as possible targets for therapeutic interventions in neurodegenerative disease.

scholarly journals GREP: genome for REPositioning drugs

2019 ◽  
Vol 35 (19) ◽  
pp. 3821-3823 ◽  
Author(s):  
Saori Sakaue ◽  
Yukinori Okada
Keyword(s):  
Large Scale ◽  
Human Genetics ◽  
Association Studies ◽  
Enrichment Analysis ◽  
Supplementary Information ◽  
Clinical Indication ◽  
Genome Wide Association Studies ◽  
Expression Studies ◽  
Gene Expression Studies ◽  
Approved Drugs

AbstractSummaryMaking use of accumulated genetic knowledge for clinical practice is our next goal in human genetics. Here we introduce GREP (Genome for REPositioning drugs), a standalone python software to quantify an enrichment of the user-defined set of genes in the target of clinical indication categories and to capture potentially repositionable drugs targeting the gene set. We show that genes identified by the large-scale genome-wide association studies were robustly enriched in the approved drugs to treat the trait of interest. This enrichment analysis was also highly applicable to other sets of biological genes such as those identified by gene expression studies and genes somatically mutated in cancers. This software should accelerate investigators to reposition drugs to other indications with the guidance of known genomics.Availability and implementationGREP is available at https://github.com/saorisakaue/GREP as a python source code.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals JEPEGMIX2: improved gene-level joint analysis of eQTLs in cosmopolitan cohorts

2017 ◽  
Author(s):  
Chris Chatzinakos ◽  
Donghyung Lee ◽  
Bradley T Webb ◽  
Vladimir I Vladimirov ◽  
Kenneth S Kendler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Studies ◽  
Supplementary Information ◽  
Joint Analysis ◽  
Genome Wide Association Studies ◽  
Expression Studies ◽  
Genome Wide ◽  
Gene Level ◽  
Supplementary Material ◽  
Gene Expression Studies

AbstractMotivationTo increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make statistical inferences based on i) summary statistics from genome-wide association studies (GWAS) and ii) linkage disequilibrium (LD) patterns from a relevant reference panel. While most such tools assume homogeneous cohorts, our Gene-level Joint Analysis of functional SNPs in Cosmopolitan Cohorts (JEPEGMIX) method accommodates cosmopolitan cohorts by using heterogeneous panels. However, JEPGMIX relies on brain eQTLs from older gene expression studies and does not adjust for background enrichment in GWAS signals.ResultsWe propose JEPEGMIX2, an extension of JEPEGMIX. When compared to JPEGMIX, it uses i) cis-eQTL SNPs from the latest expression studies and ii) brains specific (sub)tissues and tissues other than brain. JEPEGMIX2 also i) avoids accumulating averagely enriched polygenic information by adjusting for background enrichment and ii), to avoid an increase in false positive rates for studies with numerous highly enriched (above the background) genes, it outputs gene q-values based on Holm adjustment of [email protected] informationSupplementary material is available at Bioinformatics online.

scholarly journals Physical activity and risk of Alzheimer disease

Neurology ◽  
2020 ◽  
Vol 95 (13) ◽  
pp. e1897-e1905
Author(s):  
Sebastian E. Baumeister ◽  
André Karch ◽  
Martin Bahls ◽  
Alexander Teumer ◽  
Michael F. Leitzmann ◽  
...  
Keyword(s):  
Physical Activity ◽  
Alzheimer Disease ◽  
Association Studies ◽  
Vigorous Physical Activity ◽  
Primary Study ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Inverse Variance ◽  
Study Population

ObjectiveEvidence from observational studies for the effect of physical activity on the risk of Alzheimer disease (AD) is inconclusive. We performed a 2-sample mendelian randomization analysis to examine whether physical activity is protective for AD.MethodsSummary data of genome-wide association studies on physical activity and AD were used. The primary study population included 21,982 patients with AD and 41,944 cognitively normal controls. Eight single nucleotide polymorphisms (SNPs) known at p < 5 × 10−8 to be associated with average accelerations and 8 SNPs associated at p < 5 × 10−7 with vigorous physical activity (fraction of accelerations >425 milligravities) served as instrumental variables.ResultsThere was no association between genetically predicted average accelerations with the risk of AD (inverse variance weighted odds ratio [OR] per SD increment: 1.03, 95% confidence interval 0.97–1.10, p = 0.332). Genetic liability for fraction of accelerations >425 milligravities was unrelated to AD risk.ConclusionThe present study does not support a causal association between physical activity and risk of AD.

scholarly journals Gene expression levels as endophenotypes in genome-wide association studies of Alzheimer disease

Neurology ◽  
2010 ◽  
Vol 74 (6) ◽  
pp. 480-486 ◽  
Author(s):  
F. Zou ◽  
M. M. Carrasquillo ◽  
V. S. Pankratz ◽  
O. Belbin ◽  
K. Morgan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Expression Levels ◽  
Genome Wide ◽  
Gene Expression Levels

scholarly journals Animal Models of GWAS-Identified Type 2 Diabetes Genes

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Gabriela da Silva Xavier ◽  
Elisa A. Bellomo ◽  
James A. McGinty ◽  
Paul M. French ◽  
Guy A. Rutter
Keyword(s):  
Type 2 Diabetes ◽  
Animal Models ◽  
Mouse Models ◽  
Human Genetics ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide ◽  
Increased Risk

More than 65loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D). Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notablyTCF7L2andZnT8/SLC30A8, have to date been examined in mouse models. We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.

scholarly journals A suppressor locus for MODY3-diabetes

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Miguel A. Garcia-Gonzalez ◽  
Claire Carette ◽  
Alessia Bagattin ◽  
Magali Chiral ◽  
Munevver Parla Makinistoglu ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Human Genetics ◽  
Association Studies ◽  
Genetic Locus ◽  
Genome Wide Association Studies ◽  
Fasting Glycemia ◽  
Genome Wide ◽  
A Genome ◽  
Resistant Strains ◽  
Type 3

Abstract Maturity Onset Diabetes of the Young type 3 (MODY3), linked to mutations in the transcription factor HNF1A, is the most prevalent form of monogenic diabetes mellitus. HNF1alpha-deficiency leads to defective insulin secretion via a molecular mechanism that is still not completely understood. Moreover, in MODY3 patients the severity of insulin secretion can be extremely variable even in the same kindred, indicating that modifier genes may control the onset of the disease. With the use of a mouse model for HNF1alpha-deficiency, we show here that specific genetic backgrounds (C3H and CBA) carry a powerful genetic suppressor of diabetes. A genome scan analysis led to the identification of a major suppressor locus on chromosome 3 (Moda1). Moda1 locus contains 11 genes with non-synonymous SNPs that significantly interacts with other loci on chromosomes 4, 11 and 18. Mechanistically, the absence of HNF1alpha in diabetic-prone (sensitive) strains leads to postnatal defective islets growth that is remarkably restored in resistant strains. Our findings are relevant to human genetics since Moda1 is syntenic with a human locus identified by genome wide association studies of fasting glycemia in patients. Most importantly, our results show that a single genetic locus can completely suppress diabetes in Hnf1a-deficiency.

scholarly journals Issues with data transformation in genome-wide association studies for phenotypic variability

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 200 ◽  
Author(s):  
Xia Shen ◽  
Lars Rönnegård
Keyword(s):  
Statistical Power ◽  
Human Genetics ◽  
Association Studies ◽  
Phenotypic Variability ◽  
Data Transformation ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
The Real ◽  
Genome Wide

The purpose of this correspondence is to discuss and clarify a few points about data transformation used in genome-wide association studies, especially for phenotypic variability. By commenting on the recent publication by Sun et al. in the American Journal of Human Genetics, we emphasize the importance of statistical power in detecting functional loci and the real meaning of the scale of the phenotype in practice.

The Oxford Handbook of Molecular Psychology

2014 ◽  
Keyword(s):  
Social Issues ◽  
Association Studies ◽  
Copy Number Variations ◽  
Research Approach ◽  
Genome Wide Association Studies ◽  
Research Areas ◽  
Molecular Approaches ◽  
Expression Studies ◽  
Neural Underpinnings ◽  
Gene Expression Studies

Determining the biological bases for behavior—and the extent to which we can observe and explain their neural underpinnings—requires a bold, broadly defined research methodology. The interdisciplinary entries in this handbook are organized around the principle of “molecular psychology,” which unites cutting-edge research from such wide-ranging disciplines as clinical neuroscience and genetics, psychology, behavioral neuroscience, and neuroethology. For the first time in a single volume, leaders from diverse research areas present their work in which they use molecular approaches to investigate social behavior, psychopathology, emotion, cognition, and stress in healthy volunteers, patient populations, and an array of nonhuman species including nonhuman primates, rodents, insects, and fish. Chapters draw on molecular methods covering candidate genes, genome-wide association studies, copy number variations, gene expression studies, and epigenetics while addressing the ethical, legal, and social issues to emerge from this new and exciting research approach.

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