Strongest associated SNPs detected by GWASs in the HRS discovery sample and comparisons in the ELSA replication sample, for immediate recall level (IR-L) and change (IR-C) and residual delayed recall level (rDR-L) and change (rDR-C).

<p>Strongest associated SNPs detected by GWASs in the HRS discovery sample and comparisons in the ELSA replication sample, for immediate recall level (IR-L) and change (IR-C) and residual delayed recall level (rDR-L) and change (rDR-C).</p

Regional plots showing meta-analyses results for rDR-L.

<p>(A) Results with the top associated SNP in the <i>APOE</i> region labeled. Two conditional meta-analyses were performed for rDR-L, (B) estimating the association with the <i>APOE</i> SNP shown (rs769449), conditioning on the top <i>TOMM40</i> SNP (rs2075650); and (C) estimating the association with the <i>TOMM40</i> SNP shown (rs2075650), conditioning on the top <i>APOE</i> SNP (rs769449). The y-axis shows -log₁₀ P-values; x-axis shows position of genes on chromosome 19 with SNPs 400-kb in both directions of the SNP of interest. The diamond represents the top SNP of interest. The circles represent each genotyped SNP in this region; the circle color indicates pairwise linkage disequilibrium (LD) in relation to the top SNP (calculated from hg19/1000 Genomes Nov 2014 EUR). The solid (blue) line indicates the recombination rate.</p

Characteristics of HRS participants at the first assessment point, tested for immediate and delayed recall between 1996 and 2012, in the HRS full and Non-Hispanic White (NHW) genotypic samples.

<p>Characteristics of HRS participants at the first assessment point, tested for immediate and delayed recall between 1996 and 2012, in the HRS full and Non-Hispanic White (NHW) genotypic samples.</p

P-values for all 1,198,956 SNP associations from GWAS on the HRS genetic sample.

<p>(A) Level of Immediate Recall (IR-L); (B) Change in Immediate Recall (IR-C); (C) Level of Residualized Delayed Recall (rDR-L); (D) Change in Residualized Delayed Recall (rDR-C). For these figures, the upper (red) horizontal line demarcates the threshold of p = -log(5.0x10^-08) and the lower (blue) horizontal line demarcates p = -log(1x10^-05). SNPs are arranged by their chromosomal position (x-axis).</p

Regional plots showing results of the meta-analyses of IR-C.

<p>(A) Meta-analysis results with the top SNP in <i>TOMM40</i> (rs157582) shown; (B) results when estimating the association with the <i>TOMM40</i> SNP shown (rs157582), conditioning on the top <i>APOE</i> SNP (rs769449); and (C) results when estimating the association with the <i>APOE</i> SNP (rs769449), conditioning on the top <i>TOMM40</i> SNP (rs157582). The y-axis shows -log₁₀ P-values; x-axis shows position of genes on chromosome 19 with SNPs 400-kb in both directions of the SNP of interest. The diamond represents the top SNP of interest. The circles represent each genotyped SNP in this region; the circle color indicates pairwise linkage disequilibrium (LD) in relation to the top SNP (calculated from hg19/1000 Genomes Nov 2014 EUR). The solid (blue) line indicates the recombination rate.</p

Scores (as words recalled) for immediate, delayed, and residualized delayed recall among 20,650 participants in the HRS.

<p>Scores (as words recalled) for immediate, delayed, and residualized delayed recall among 20,650 participants in the HRS.</p

Age-adjusted values for estimated immediate recall (IR), delayed recall (DR), and residual delayed recall (rDR) in HRS.

<p>Age-adjusted values for estimated immediate recall (IR), delayed recall (DR), and residual delayed recall (rDR) in HRS.</p

Presentation_1_Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.PDF

<p>Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.</p

Table_1_Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.CSV

<p>Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.</p