Fig. 3 Context-dependent inherited risk and the importance of intermediate phenotypes in clinical research. Context-dependent inherited risk and the importance.

Slides:



Advertisements
Similar presentations
Genetic Analysis in Human Disease. Learning Objectives Describe the differences between a linkage analysis and an association analysis Identify potentially.
Advertisements

Allele. Alternate form of a gene gene variant autosome.
The Future of Genetics Research Lesson 7. Human Genome Project 13 year project to sequence human genome and other species (fruit fly, mice yeast, nematodes,
PLANT BIOTECHNOLOGY & GENETIC ENGINEERING (3 CREDIT HOURS) LECTURE 13 ANALYSIS OF THE TRANSCRIPTOME.
Content What is epigenetics?. The Mapping of the Human Genome Project 2000 A working draft but completed in 2003 Only 20,000–25,000 genes! Only 1.5% of.
New research areas in personalised medicines
Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders  Ariel Feiglin, Bryce K. Allen,
EQTLs.
Mendel and the Gene Idea
Notes: Nature Vs. nurture
Sunday, Tuesday & Thursday 2-3
Figure 2. Regional plots and box plots for gene ABO top cis-SNPs whose signal was not attenuated after adjusting for the lead GWAS SNPs. (A) Observed −log10(P)
GCN5 Regulates FGF Signaling and Activates Selective MYC Target Genes during Early Embryoid Body Differentiation  Li Wang, Evangelia Koutelou, Calley.
 The human genome contains approximately genes.  At any given moment, each of our cells has some combination of these genes turned on & others.
Integrated Metabolomics and Genomics
ABO Blood Type: An Example of Genetic Variation
PNPLA3 gene in liver diseases
Genetics Definitions Definition Key Word
Volume 145, Issue 2, Pages (August 2013)
High level GWAS analysis
Dynamic epigenetic enhancer signatures reveal key transcription factors associated with monocytic differentiation states by Thu-Hang Pham, Christopher.
Whole-Embryo Modeling of Early Segmentation in Drosophila Identifies Robust and Fragile Expression Domains  Jonathan Bieler, Christian Pozzorini, Felix.
BET inhibition and depletion repress the expression of BRCA1 and RAD51
The Impact of Network Medicine in Gastroenterology and Hepatology
Fig. 2. Engraftment of CART-EGFRvIII and cytokine modulation in the peripheral blood. Engraftment of CART-EGFRvIII and cytokine modulation in the peripheral.
Fig. 4. Functional annotation of VUS in EGFR.
Fig. 2 TLR8 is aberrantly expressed on pDCs from SSc patients.
Volume 125, Issue 4, Pages (May 2006)
Genetics and genomics of psychiatric disease
Steven R. Brant  Clinical Gastroenterology and Hepatology 
A twin approach to unraveling epigenetics
Volume 68, Issue 2, Pages (October 2010)
Inferring chromatin organization.
The Genetic Architecture of Alopecia Areata
Identification and Validation of Genetic Variants that Influence Transcription Factor and Cell Signaling Protein Levels  Ronald J. Hause, Amy L. Stark,
Volume 7, Issue 1, Pages (April 2014)
INTRODUCTION Nutrigenomics Dr. Muhamad Firdaus
Volume 96, Issue 9, Pages (May 2009)
Parisa Shooshtari, Hailiang Huang, Chris Cotsapas 
Volume 58, Issue 4, Pages (May 2015)
Towfique Raj, Manik Kuchroo, Joseph M
Malika Kumar Freund, Kathryn S
Sherlock: Detecting Gene-Disease Associations by Matching Patterns of Expression QTL and GWAS  Xin He, Chris K. Fuller, Yi Song, Qingying Meng, Bin Zhang,
Intratumoral Heterogeneity of the Epigenome
Genome-wide analysis of p53 occupancy.
Structural Architecture of SNP Effects on Complex Traits
Volume 12, Issue 2, Pages (July 2015)
IPOP Goes the World: Integrated Personalized Omics Profiling and the Road toward Improved Health Care  Jennifer Li-Pook-Than, Michael Snyder  Chemistry.
Lynn Petukhova, Angela M. Christiano 
Genjiro Suzuki, Jonathan S. Weissman, Motomasa Tanaka  Molecular Cell 
Volume 39, Issue 2, Pages (October 2016)
Elanor N. Wainwright, Paola Scaffidi  Trends in Cancer 
Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders  Ariel Feiglin, Bryce K. Allen,
Volume 29, Issue 5, Pages (May 2016)
Fig. 2 Genotype-induced differential gene expression is different in MDMi cells compared to monocytes. Genotype-induced differential gene expression is.
Discovery From Data Repositories H Craig Mak  Nature Biotechnology 29, 46–47 (2011) 2013 /06 /10.
Volume 9, Issue 3, Pages (November 2014)
Genetic Diseases & Pedigrees
Correlation of reovirus RNA/protein with proliferating tumor cells
Osteoarthritis year in review 2016: genetics, genomics and epigenetics
Brandon Ho, Anastasia Baryshnikova, Grant W. Brown  Cell Systems 
Fig. 3. Comparison of prediction performance.
Fig. 4. Long-term persistence of CTL019 cells and polyfunctionality in patients achieving CR. Long-term persistence of CTL019 cells and polyfunctionality.
NEW: Network-Enabled Wisdom in Biology, Medicine, and Health Care
Identification of a ufo1 Candidate Gene from the Mapping Region.
Fig. 4 Identification of C
The Genetics of Transcription Factor DNA Binding Variation
Epigenetic therapy overcomes treatment resistance in T cell prolymphocytic leukemia by Zainul S. Hasanali, Bikramajit Singh Saroya, August Stuart, Sara.
HPV–human protein network map.
Epigenetic mechanisms and the development of asthma
Presentation transcript:

Fig. 3 Context-dependent inherited risk and the importance of intermediate phenotypes in clinical research. Context-dependent inherited risk and the importance of intermediate phenotypes in clinical research. (A) The diagram plots sets of genetic risk variants according to their dependencies on contexts in the macroenvironment (such as life-style factors and exposures to environmental toxins) that, over time, transform microenvironments (in cell and tissue types) to activate DNA variants that then exert their risk-promoting effects on certain CCDs. Some genetic risk variants are environment-independent, and their disease associations may be detected early in life (light purple shading, left and bottom parts of the graph); the effects of other genetic risk variants are age-related (such as epigenetic changes), because exposures to macroenvironments alter microenvironments over time (dark purple background); environment-dependent DNA risk variants become increasingly important for CCD development later in life. Color-coded key for CCDs that are affected by DNA risk variants is shown below the graph at the right. SLE, systemic lupus erythematosus; RA, rheumatoid arthritis; IBD, inflammatory bowel diseases. (B) The importance of intermediate phenotypes in clinical studies of CCDs. Left: Traditional GWAS are based on the idea that genetic variations follow Mendelian inheritance and are relatively infrequent and context-independent, even for complex biological events and diseases. Most CCD-linked variants will not be discovered in this way, because the genetic perturbation (top circle, gray center) is too weak to be sensed by the disease phenotype (top circle, blue outer area). Some DNA risk variants that are context-independent (those that are common in the population) can be revealed with a GWAS design alone [blue bottom circle, large red diamonds shown “above the surface” (horizontal line)]; however, such studies do not explain the full variation in disease phenotypes (blue bottom circle, smaller red diamonds below the surface). Middle: In genetics of gene expression (GGE) studies (top circle), the apprehending of an intermediate phenotype of mRNA abundance (a measure of, for example, gene expression) (top circle, intermediate purple area) from patients and control individuals allows additional DNA variants to be identified from GWAS data sets (top circle, gray center)—in particular those that are context-dependent—thereby explaining more of the variations in disease phenotypes. This is achieved because intermediate gene expression data provide a more proximal sensor of DNA variation than does the clinical phenotype alone (top circle, outer blue area; compare with GWAS design alone). A GGE design thus allows for the inference of disease networks [in bottom circle, nodes (purple)] that harbor several DNA risk variants (shown as red diamonds in the network) linked to disease where these networks act to drive disease phenotypes (blue background). Right: The top circle depicts genetics of gene (gray center), protein (intermediate purple area), and metabolite (intermediate dark turquoise area) expression (GGPME) studies, which provide an even richer collection of proximal sensors of DNA variation that inform the clinical phenotype (top circle, outer blue area). Bottom circle: The identification of several layers of genome-wide measurements that sense the flow of DNA information allows inference of complex full disease networks (in bottom circle) with all disease-linked DNA risk variants (red diamonds) in contrast to networks whose effects are reflected in changes in mRNA concentrations alone. Dark purple, light purple, and dark turquoise network nodes (circles) are derived from genome-wide RNA, protein, and metabolite measurements, respectively; the associated phenotypes are depicted by the blue background. Eric E. Schadt and Johan L. M. Björkegren Sci Transl Med 2012;4:115rv1 Published by AAAS