Variance Decomposition Approach Research Articles

Quantitative Loci Regulating Plasma Levels of γ Glutamyl Transferase and Albumin and Their Genetic Correlations with Cardiovascular Risk Factors

gamma Glutamyl transferase (GGT) and albumin (ALB) are two markers of liver function. These two proteins have been associated with non-alcoholic fatty liver disease and cardiovascular disease. The objectives of this study were to explore the genetic factors that influence variation in the plasma levels of GGT and ALB and to evaluate their genetic correlations with cardiovascular risk factors. Baboons from the Southwest National Primate Research Center at the Southwest Foundation for Biomedical Research, San Antonio, TX, were used as an animal model. The baboons were fed a standard monkey chow diet ad libitum. Fasting plasma concentrations of GGT, ALB, triglycerides, total cholesterol and LDL cholesterol were measured in 350 pedigreed adult baboons by standard assay procedures. A maximum likelihood-based variance decomposition approach implemented in the computer program SOLAR was used to conduct genetic analyses. The heritabilities of GGT (h(2) = 0.55; P < 0.0001) and ALB (h(2) = 0.42; P < 0.01) were significant. No statistically significant associations were found between GGT and the cardiovascular-related phenotypes. Genetic correlations between ALB and total cholesterol, LDL cholesterol and triglycerides were significant. A QTL (LOD = 2.8) for GGT plasma levels was identified on the baboon homologue of human chromosome 22 between markers D22S304 and D22S280. A QTL (LOD = 2.3) near marker D10S1432 was detected on the baboon homologue of human chromosome 10 for ALB. These results imply that variations in the plasma levels of GGT and ALB are under significant genetic regulation and that a common genetic component influences ALB and cardiovascular risk factor phenotypes.

Pleiotropic effects on subclasses of HDL, adiposity, and glucose metabolism in adult Alaskan Eskimos

The aim of this study was to analyze the heritability and the presence of pleiotropic effects on subfractions of high-density lipoproteins (HDLs) as measured by nuclear magnetic resonance (NMR), parameters for adiposity, and glucose metabolism in adult Alaskan Eskimos. The present family study included 1,214 adult Alaskan Eskimos (537 male/677 female). Body weight, height, circumferences, selected skinfolds, and blood pressure were measured in all participants. Blood samples were collected under fasting conditions for the isolation of plasma. Glucose, insulin, subclasses and size of lipoproteins, triglycerides, total, and HDL cholesterol and lipoprotein (a) were measured in plasma. HbA1c was measured in total blood. Univariate and bivariate quantitative genetic analyses were conducted between HDL subclasses and size and the anthropometric and biochemical measures using the variance decomposition approach. Variation in all the analyzed traits exhibits a significant genetic component. Heritabilities ranged between 0.18 +/- 0.11 for LDL(2) (intermediate) and 0.89 +/- 0.07 for small HDL. No common genetic effects were found on the HDL subclasses (small, intermediate, and large). Small HDL particles were genetically correlated with LDL particles and HbA1c. Negative genetic correlations were observed between intermediate and large HDL subfractions, HDL size and measures of adiposity, and LDL and parameters for glucose metabolism (HbA1, insulin). These observations confirm the presence of possible pleiotropic effects on HDL, adiposity, and cardiovascular risk factors and provide novel insight on the relationship between HDL subclasses, adiposity, and glucose regulation.

Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India

This paper attempts to examine the dynamic relationship between economic growth, nuclear energy consumption, labor and capital for India for the period 1969–2006. Applying the bounds test approach to cointegration developed by Pesaran et al. (2001) we find that there was a short- and a long-run relationship between nuclear energy consumption and economic growth. Using four long-run estimators we also found that nuclear energy consumption has a positive and a statistically significant impact on India's economic growth. Further, applying the Toda and Yamamoto (1995) approach to Granger causality and the variance decomposition approach developed by Pesaran and Shin (1998), we found a positive and a significant uni-directional causality running from nuclear energy consumption to economic growth without feedback. This implies that economic growth in India is dependent on nuclear energy consumption where a decrease in nuclear energy consumption may lead to a decrease in real income. For a fast growing energy-dependent economy this may have far-reaching implications for economic growth. India's economic growth can be frustrated if energy conservation measures are undertaken without due regard to the negative impact they have on economic growth.

Variance decompositions of nonlinear-dynamic stochastic systems

A variance decomposition approach to quantify the effects of stochastic variables in nonlinear-dynamic models is developed. The decomposition is taken temporally with respect to the source of disturbance. The methodology uses Monte-Carlo methods to estimate the variance decomposition using the ANOVA-like procedures proposed in [G.E.B. Archer, A. Saltelli, I.M. Sobol, Sensitivity measures, anova-like techniques and the use of bootstrap, Journal of Statistical Computation and Simulation 58 (1997) 99–120; A. Saltelli, S. Tarantola, K. Chan, A quantitative model-independent method for global sensitivity analysis of model output, Technometrics 41 (1999) 39–56]. The results in this paper generalize the variance decomposition results that are obtained analytically for linear systems.

Potentially predictable patterns of extratropical tropospheric circulation in an ensemble of climate simulations with the COLA AGCM

AbstractA variance decomposition approach to estimate the potentially predictable component of seasonal means has been further developed to separately diagnose the boundary‐forced component and the slowly varying internal dynamics component. This decomposition of the potentially predictable component has been applied to an ensemble of ten 50‐year simulations of the 500 hPa geopotential height field from the Center for Ocean‐Land‐Atmosphere Studies global atmospheric model forced by sea‐surface temperatures. The model performance is analysed for the winter season and compared with the National Centers for Environmental Prediction reanalysis. The majority of the hemispheric potentially predictable patterns, identified as the empirical orthogonal functions of the potentially predictable component of the seasonal mean fields, are captured by the model. These include all the patterns forced by the El Niño–Southern Oscillation in the Southern Hemisphere, and the dominant potentially predictable patterns in the Northern Hemisphere, i.e. the Pacific–North American pattern. However, the boreal winter Western Pacific Oscillation and Tropical Northern Hemisphere pattern, which are well simulated by some other general circulation models, are not well captured. Copyright © 2009 Royal Meteorological Society

Alternative Model Selection Using Forecast Error Variance Decompositions in Wholesale Chicken Markets

Although Vector Autoregressive models are commonly used to forecast prices, specification of these models remains an issue. Questions that arise include choice of variables and lag length. This article examines the use of Forecast Error Variance Decompositions to guide the econometrician's model specification. Forecasting performance of Variance Autoregressive models, generated from Forecast Error Variance Decompositions, is analyzed within wholesale chicken markets. Results show that the Forecast Error Variance Decomposition approach has the potential to provide superior model selections to traditional Granger Causality tests.

Local and landscape effects on temporary pond zooplankton egg banks: conservation implications

Understanding landscape correlates of local habitat integrity and community structure and the identification of spatial scales at which these associations operate are relevant for management and conservation of unique but globally threatened temporary ponds. We use a multivariate variance decomposition approach to determine taxon-specific associations of zooplankton communities banked in dry pond soils (rotifers, cladocerans, copepods) with local habitat features and landscape characteristics across four spatial scales (100 buffer strip, 1, 5, and 10 km scales). Results show similar degrees of correlation between rotifer and cladoceran communities with local habitat conditions (chiefly water quality). This is interpreted according to life-history traits of component species of wetland propagule banks. Associations with landscape features varied between communities with rotifers correlating with landscape structural features only at the buffer scale while cladocerans showed no significant correlations with landscape characteristics across all scales. Copepods were neither significantly associated with local nor landscape characteristics. The results of this study contrast strikingly with our previous population-based study, where populations of Triops cancriformis and Branchinecta orientales were significantly correlated with landuse features at the broadest scale. The combined results suggest that a three-way management scheme could be useful for conservation of zooplankton resting egg banks in this remnant wetland complex. These schemes could focus on the restoration of wetland water quality, the establishment of vegetated buffer strips around the ponds to counteract degradation resulting from runoff, and reforestation and/or the creation of hedgerows in agricultural catchments to avoid impacts resulting from broad-scale diffuse pollution fluxes.

A Variance Decomposition Primer for Accounting Researchers

This pedagogical note introduces the accounting-based variance decomposition methodology of Vuolteenaho (2002) in a relatively simple format for the edification of accounting scholars and Ph.D. students who wish to use variance decomposition in their research. In addition to presenting an example that explicates the variance decomposition approach, we provide well-documented SAS and STATA programs for estimating variance decompositions from cross-sectional time-series data.

Variance decomposition approach to the prediction of the seasonal mean circulation: Comparison with dynamical ensemble prediction using NCEP's CFS

AbstractReanalysis data and a recently developed variance decomposition approach are applied to empirically predict seasonal mean 500 hPa geopotential height anomalies in both the Northern and Southern Hemisphere from the beginning of each season. The predictors are only several popular tropical SST indices and the annular mode indices at one month or one season lead. The statistical prediction is compared with the dynamical ensemble prediction of the National Centers for Environmental Prediction's coupled Climate Forecast System (CFS). It is found that their skills are quite comparable. The advantages and disadvantages of dynamical prediction and statistical prediction are discussed. A strategy for a new statistical–dynamical prediction which combines the advantages of both statistical and dynamical predictions is suggested. Copyright © 2008 Royal Meteorological Society

A Critical Note on the Forecast Error Variance Decomposition

The paper questions the reasonability of using forecast error variance decompositions for assessing the role of different structural shocks in business cycle fluctuations. It is shown that the forecast error variance decomposition is related to a dubious definition of the business cycle. A historical variance decomposition approach is proposed to overcome the problems related to the forecast error variance decomposition.

Genotype-by-diet effects on co-variation in Lp-PLA2 activity and LDL-cholesterol concentration in baboons fed an atherogenic diet

Both lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) activity, a biomarker of inflammation, and concentration of its primary associated lipoprotein, LDL, are correlated with adverse coronary outcomes. We previously reported a quantitative trait locus (QTL) corresponding to HSA2p24.3-p23.2 with pleiotropic effects on Lp-PLA(2) activity and LDL-cholesterol (LDL-C) concentration in baboons fed a basal diet. Here, our goal was to locate pleiotropic QTLs influencing both traits in the same baboons fed a high-cholesterol, high-fat (HCHF) diet, and to assess whether shared genetic effects on these traits differ between diets. We assayed Lp-PLA(2) activity and LDL-C concentration in 683 baboons fed the HCHF diet. We used a bivariate maximum likelihood-based variance components approach in whole-genome linkage screens to locate a QTL [logarithm of odds (LOD) = 3.13, genome-wide P = 0.019] corresponding to HSA19q12-q13.2 with pleiotropic effects on Lp-PLA(2) activity and LDL-C levels in the HCHF diet. We additionally found significant evidence of genetic variance in response to diet for Lp-PLA(2) activity (P = 0.0017) and for LDL-C concentration (P = 0.00001), revealing a contribution of genotype-by-diet interaction to covariation in these two traits. We conclude that the pleiotropic QTLs detected at 2p24.3-p23.2 and 19q12-q13.2 on the basal and HCHF diets, respectively, exert diet-specific effects on covariation in Lp-PLA(2) activity and LDL-C concentration.

The lipoprotein subfraction profile: heritability and identification of quantitative trait loci

The HDL and LDL subclass profile is an emerging cardiovascular risk factor. Yet, the biological and genetic mechanisms controlling the lipoprotein subclass distribution are unclear. Therefore, we aimed 1) to determine the heritability of the entire spectrum of LDL and HDL subclass features and 2) to identify gene loci influencing the lipoprotein subfraction pattern. Using NMR spectroscopy, we analyzed the lipoprotein subclass distribution in 1,275 coronary artery disease patients derived from the Regensburg Myocardial Infarction Family Study. We calculated heritabilities, performed a microsatellite genome scan, and calculated linkage. HDL and LDL subclass profiles showed heritabilities ranging from 23% to 67% (all P < 10(-3)) of traits using univariate calculation. After multivariate adjustment, we found heritabilities of 27-48% (all P < 0.05) for HDL and 21-44% for LDL traits. The linkage analysis revealed a significant logarithm of the odds (LOD) score (3.3) for HDL particle concentration on chromosome 18 and a highly suggestive signal for HDL particle size on chromosome 12 (2.9). After multivariate adjustment, we found a significant maximum LOD score of 3.7 for HDL size. Our study is the first to analyze heritability and linkage for the entire spectrum of LDL and HDL subclass features. Our findings may lead to the identification of genes controlling the lipoprotein subclass distribution.

Genetics of variation in adiponectin in pedigreed baboons: evidence for pleiotropic effects on adipocyte volume and serum adiponectin

To detect and localize the effects of genes influencing variation in adiponectin mRNA and protein levels, we conducted statistical genetic analyses of circulating concentrations of adiponectin and adiponectin (ADIPOQ) mRNA expression in omental adipose tissue in adult, pedigreed baboons (Papio anubis). An omental adipose tissue biopsy and blood sample were collected from 427 baboons from the colony at the Southwest Foundation for Biomedical Research, San Antonio, TX. Total RNA was isolated from adipose tissue and adiponectin mRNA levels were assayed by real-time, quantitative reverse transcriptase-PCR. Adiponectin, insulin, glucose, cholesterol, high-density lipoproteins and triglycerides were measured in fasting serum. Quantitative genetic analyses were conducted for adiponectin mRNA and serum protein using a maximum likelihood-based variance decomposition approach. A genome-wide linkage analysis was conducted using adiponectin mRNA and protein levels as phenotypes. Significant heritability was estimated for ADIPOQ mRNA levels (h2=0.19+/-0.07, P=0.01) and protein levels (h2=0.28+/-0.14, P=0.003). Genetic correlations were found between adiponectin protein and body weight (rho(G)=-0.51, P=0.03), cell volume (rho(G)=-0.73, P=0.04), serum triglycerides (rho(G)=-0.67, P=0.03), and between adiponectin mRNA and glucose (rho(G)=0.93, P<0.01). A logarithm of odds score of 2.9 was found for ADIPOQ mRNA levels on baboon chromosome 4p, which is orthologous to human 6p21. There is a significant genetic component affecting variation in the analyzed traits, and common genes may be influencing adiponectin expression, adipocyte volume, body weight and circulating triglycerides. The region on 6p21 has been linked to diabetes-related phenotypes in human studies.

Geographic Concentration and China's Agricultural Export Instability

This paper investigates the impacts of geographic concentration on China's agricultural export instability with a multiple-region variance decomposition approach. The decomposition results suggest that China's agricultural export concentration into the Japanese market greatly lowers agricultural export instability, while concentration into the Hong Kong, South Korea, ASEAN, the US, and Russian Federation markets increases export instability. China's exports to the EU also lower its agricultural export instability. Further decomposition results indicate that the impacts of geographic concentration on different agricultural product export instabilities are different.

Statistical Prediction of Seasonal Mean Southern Hemisphere 500-hPa Geopotential Heights

Abstract A recently developed variance decomposition approach is applied to predict seasonal mean 500-hPa geopotential height anomalies in the Southern Hemisphere. In terms of predictability of both the winter and summer height fields, the Southern Oscillation and the Southern Annular Mode are identified as the first and second most important factors affecting the variability. Based on this study, a statistical prediction scheme has been developed. The linear trend in the leading empirical orthogonal function of the height field, the November Southern Annular Mode index, the austral spring Niño-3 index, and the November Coral Sea index are identified as the main predictors for the summer height field, while the March–May Southern Annular Mode index, the May Niño-4 index, and the austral autumn central Indian Ocean index are the main predictors for the winter height field. The predictive skill in forecasts of National Centers for Environmental Prediction–National Center for Atmospheric Research and European Centre for Medium-Range Weather Forecasts reanalysis 500-hPa geopotential height anomaly fields, in terms of a spatiotemporal anomaly correlation, is considerably higher than a single prediction achieved by a coupled general circulation seasonal forecast model.

A method for constructing skillful seasonal forecasts using slow modes of climate variability

A methodology for constructing skillful statistical seasonal forecasts of climate fields is described and applied to predict the Southern Hemisphere summer mean sea level pressure anomalies for the period 1993--2004. The method employs a recently developed variance decomposition approach, which allows a separation of the predictable and unpredictable components of climate variation. The proposed forecast scheme is based on finding predictors for the amplitude time series of the dominant slow (or predictable) modes of interannual climate variation.

The Genes Influencing Adiponectin Levels Also Influence Risk Factors for Metabolic Syndrome and Type 2 Diabetes

Results from previous studies suggest that adiponectin levels are associated with risk factors for cardiovascular disease and type 2 diabetes mellitus; however, the genetic and/or environmental components of this relationship have not been characterized. The aims of this study were (1) to assess the presence of pleiotropy between adiponectin levels and risk factors for cardiovascular disease and (2) to study the association of circulating levels of adiponectin with risk factors for cardiovascular disease in the absence and presence of obesity in Mexican American adults from the San Antonio Family Heart Study. Body composition and circulating levels of adiponectin, leptin, and lipid subfractions and measurements of glucose metabolism were measured in 898 subjects. The mean and standard error of the circulating levels of adiponectin was 8.7 +/- 3.2 microg/ml. Bivariate quantitative analyses between adiponectin levels and phenotypes related to cardiovascular disease and type 2 diabetes mellitus were conducted using the variance decomposition approach implemented in SOLAR. A second analysis in unrelated subjects compared these risk factors between sex- and age-matched lean and obese subjects with high and low adiponectin levels. We found significant evidence of pleiotropy (i.e., shared genetic effects) between plasma levels of adiponectin and well-established risk factors for cardiovascular disease and type 2 diabetes mellitus. Individuals with low adiponectin levels per body weight had more adverse risk profiles. These findings offer new insights into the genetic connection between increasing adiposity and risk for cardiovascular disease and type 2 diabetes mellitus, and they suggest that adiponectin may be an important risk factor for the development of these conditions.

Sex‐specific QTL effects on variation in paraoxonase 1 (PON1) activity in Mexican Americans

Paraoxonase 1 (PON1), a high-density lipoprotein-associated enzyme known to protect against cellular damage from toxic agents, may also have antioxidant properties. PON1 activity levels have been reported to differ by sex in human and animal studies with females exhibiting higher basal levels. We measured PON1 activity frozen serum for 1,406 individuals in over 40 extended pedigrees from the San Antonio Family Heart Study (SAFHS). We used a maximum likelihood-based, variance decomposition approach implemented in SOLAR to test for genotype-by-sex (G x S) interaction on variation in PON1 activity and to determine if any of the four PON1 quantitative trait loci (QTL) previously reported by us for this population might account for sex differences in PON1 activity levels. The residual additive genetic correlation (rho(G) = 0.82) between males and females is significantly different from 1 (P = 0.009), suggesting that some of the genes that influence PON1 activity act differently in females and males or, possibly, that a different combination of genes influences this trait in each sex. In addition to the QTL at or near the PON structural locus on 7q21-22, three other potential QTLs were evaluated for sex-specific effects: one each on chromosomes 12, 17 and 19. The QTL on chromosome 17 (LOD = 2.32, P = 0.0003; flanked by microsatellite marker loci D17S974 and D17S969) shows a significant (P = 0.005) sex-specific effect on PON1 activity; accounting for 6% of the additive genetic variance in males and 20% in females. This study represents the first formal statistical genetic test for G x S interactions on normal quantitative variation in PON1 activity in humans.

An Evaluation of the Relative Importance of Parent-Only and Subsidiary Earnings in Japan: A Variance Decomposition Approach

ABSTRACT: This paper investigates the relative importance of parent-only and subsidiary earnings in Japanese firms using a variance decomposition methodology. The findings generally indicate that subsidiary return on equity (ROE) news has a greater effect in driving current stock returns than parent-only ROE news. In addition, we show that as subsidiary companies’ performance becomes relatively important as an indicator of consolidated performance, the market pays greater attention to subsidiary ROE news. Finally, we show that the market does not pay greater attention to subsidiary earnings when consolidated earnings are negative. In that case, parent-only earnings become a good indicator of consolidated performance.

Linkage analysis of circulating levels of adiponectin in hispanic children

Adiponectin, a hormone produced exclusively by adipose tissue, is inversely associated with insulin resistance and proinflammatory conditions. The aim of this study was to find quantitative trait loci (QTLs) that affect circulating levels of adiponectin in Hispanic children participating in the VIVA LA FAMILIA Study by use of a systematic genome scan. The present study included extended families with at least one overweight child between 4 and 19 years old. Overweight was defined as body mass index (BMI) 95th percentile. Fasting blood was collected from 466 children from 127 families. Adiponectin was assayed by radioimmunoassay (RIA) technique in fasting serum. A genome-wide scan on circulating levels of adiponectin as a quantitative phenotype was conducted using the variance decomposition approach. The highest logarithm of odds (LOD) score (4.2) was found on chromosome 11q23.2-11q24.2, and a second significant signal (LOD score=3.0) was found on chromosome 8q12.1-8q21.3. In addition, a signal suggestive of linkage (LOD score=2.5) was found between 18q21.3 and 18q22.3. After adjustment for BMI-Z score, the LOD score on chromosome 11 remained unchanged, but the signals on chromosomes 8 and 18 dropped to 1.6 and 1.7, respectively. Two other signals suggestive of linkage were found on chromosome 3 (LOD score=2.1) and 10 (LOD score=2.5). Although the region on chromosome 11 has been associated with obesity and diabetes-related traits in adult populations, this is the first observation of linkage in this region for adiponectin levels. Our suggestive linkages on chromosomes 10 and 3 replicate results for adiponectin seen in other populations. The influence of loci on chromosomes 18 and 8 on circulating adiponectin seemed to be mediated by BMI in the present study. Our genome scan in children has identified a novel QTL and replicated QTLs in chromosomal regions previously shown to be linked with obesity and type 2 diabetes (T2D)-related phenotypes in adults. The genetic contribution of loci to adiponectin levels may vary across different populations and age groups. The strong linkage signal on chromosome 11 is most likely underlain by a gene(s) that may contribute to the high susceptibility of these Hispanic children to obesity and T2D.