960 resultados para Variance.


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The root-lesion nematode Pratylenchus thornei causes substantial loss to bread wheat production in the northern grain region of Australia and other parts of the world. West Asia and North Africa (WANA) wheat accessions with partial resistance to P. thornei were analysed for mode of inheritance in a half-diallel crossing design of F1 hybrids (10 parents) and F2 populations (7 parents). General combining ability was more important than specific combining ability as indicated by components of variance ratios of 0.93 and 0.95 in diallel ANOVA of the F1 and F2 generations, respectively. General combining ability values of the 'resistant' parents were predictive of the mean nematode numbers of their progeny in crosses with the susceptible Australian cv. Janz at the F1 (R populations showed relatively continuous distributions. Heritability was 0.68 for F2 populations in the half-diallel of resistant parents and 0.82-0.92 for 5 'resistant' parent/Janz doubled-haploid populations (narrow-sense heritability on a line mean basis). The results indicate polygenic inheritance of P. thornei resistance with a minimum of from 2 to 6 genes involved in individual F populations of 5 resistant parents crossed with Janz. Morocco 426 and Iraq 43 appear to be the best of the parents tested for breeding for resistance to P. thornei. None of the P. thornei-resistant WANA accessions was resistant to Pratylenchus neglectus.

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In order to investigate the effect of long term recurrent selection on the pattern of gene diversity, thirty randomly-selected individuals from the progenitors (p) and four selection cycles (C0, C3, C6 and C11) were sampled for DNA analysis from the tropical maize (Zea mays L.) breeding populations, Atherton 1 (AT1) and Atherton 2 (AT2). Fifteen polymorphic Simple Sequence Repeat markers amplified a total of 284 and 257 alleles in AT1 and AT2 populations, respectively. Reductions in the number of alleles were observed at advanced selection cycles. About 11 and 12% of the alleles in AT1 and AT2 populations respectively, were near to fixation. However, a higher number of alleles (37% in AT1 and 33% in AT2) were close to extinction. Fisher's exact test and analysis of molecular variance (AMOVA) showed significant population differentiations. Gene diversity estimates and AMOVA revealed increased genetic differentiations at the expense of loss of heterozygosity. Population differentiations were mainly due to fixation of complementary alleles at a locus in the two breeding populations. The estimates of effective population at an advanced selection cycle were close to the population size predicted by the breeding method.

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Purpose – Preliminary cost estimates for construction projects are often the basis of financial feasibility and budgeting decisions in the early stages of planning and for effective project control, monitoring and execution. The purpose of this paper is to identify and better understand the cost drivers and factors that contribute to the accuracy of estimates in residential construction projects from the developers’ perspective. Design/methodology/approach – The paper uses a literature review to determine the drivers that affect the accuracy of developers’ early stage cost estimates and the factors influencing the construction costs of residential construction projects. It used cost variance data and other supporting documentation collected from two case study projects in South East Queensland, Australia, along with semi-structured interviews conducted with the practitioners involved. Findings – It is found that many cost drivers or factors of cost uncertainty identified in the literature for large-scale projects are not as apparent and relevant for developers’ small-scale residential construction projects. Specifically, the certainty and completeness of project-specific information, suitability of historical cost data, contingency allowances, methods of estimating and the estimator’s level of experience significantly affect the accuracy of cost estimates. Developers of small-scale residential projects use pre-established and suitably priced bills of quantities as the prime estimating method, which is considered to be the most efficient and accurate method for standard house designs. However, this method needs to be backed with the expertise and experience of the estimator. Originality/value – There is a lack of research on the accuracy of developers’ early stage cost estimates and the relevance and applicability of cost drivers and factors in the residential construction projects. This research has practical significance for improving the accuracy of such preliminary cost estimates.

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Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

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Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

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A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) approximately 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for approximately 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

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Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

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Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 +/- 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 +/- 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 +/- 0.06 s.e.), and ADHD and major depressive disorder (0.32 +/- 0.07 s.e.), low between schizophrenia and ASD (0.16 +/- 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

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Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were: (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10), and; (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD.

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Pharmacogenetics deals with genetically determined variation in drug response. In this context, three phase I drug-metabolizing enzymes, CYP2D6, CYP2C9, and CYP2C19, have a central role, affecting the metabolism of about 20-30% of clinically used drugs. Since genes coding for these enzymes in human populations exhibit high genetic polymorphism, they are of major pharmacogenetic importance. The aims of this study were to develop new genotyping methods for CYP2D6, CYP2C9, and CYP2C19 that would cover the most important genetic variants altering the enzyme activity, and, for the first time, to describe the distribution of genetic variation at these loci on global and microgeographic scales. In addition, pharmacogenetics was applied to a postmortem forensic setting to elucidate the role of genetic variation in drug intoxications, focusing mainly on cases related to tricyclic antidepressants, which are commonly involved in fatal drug poisonings in Finland. Genetic variability data were obtained by genotyping new population samples by the methods developed based on PCR and multiplex single-nucleotide primer extension reaction, as well as by collecting data from the literature. Data consisted of 138, 129, and 146 population samples for CYP2D6, CYP2C9, and CYP2C19, respectively. In addition, over 200 postmortem forensic cases were examined with respect to drug and metabolite concentrations and genotypic variation at CYP2D6 and CYP2C19. The distribution of genetic variation within and among human populations was analyzed by descriptive statistics and variance analysis and by correlating the genetic and geographic distances using Mantel tests and spatial autocorrelation. The correlation between phenotypic and genotypic variation in drug metabolism observed in postmortem cases was also analyzed statistically. The genotyping methods developed proved to be informative, technically feasible, and cost-effective. Detailed molecular analysis of CYP2D6 genetic variation in a global survey of human populations revealed that the pattern of variation was similar to those of neutral genomic markers. Most of the CYP2D6 diversity was observed within populations, and the spatial pattern of variation was best described as clinal. On the other hand, genetic variants of CYP2D6, CYP2C9, and CYP2C19 associated with altered enzymatic activity could reach extremely high frequencies in certain geographic regions. Pharmacogenetic variation may also be significantly affected by population-specific demographic histories, as seen within the Finnish population. When pharmacogenetics was applied to a postmortem forensic setting, a correlation between amitriptyline metabolic ratios and genetic variation at CYP2D6 and CYP2C19 was observed in the sample material, even in the presence of confounding factors typical for these cases. In addition, a case of doxepin-related fatal poisoning was shown to be associated with a genetic defect at CYP2D6. Each of the genes studied showed a distinct variation pattern in human populations and high frequencies of altered activity variants, which may reflect the neutral evolution and/or selective pressures caused by dietary or environmental exposure. The results are relevant also from the clinical point of view since the genetic variation at CYP2D6, CYP2C9, and CYP2C19 already has a range of clinical applications, e.g. in cancer treatment and oral anticoagulation therapy. This study revealed that pharmacogenetics may also contribute valuable information to the medicolegal investigation of sudden, unexpected deaths.

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Type 1 diabetes (T1D) is a common, multifactorial disease with strong familial clustering. In Finland, the incidence of T1D among children aged 14 years or under is the highest in the world. The increase in incidence has been approximately 2.4% per year. Although most new T1D cases are sporadic the first-degree relatives are at an increased risk of developing the same disease. This study was designed to examine the familial aggregation of T1D and one of its serious complications, diabetic nephropathy (DN). More specifically the study aimed (1) to determine the concordance rates of T1D in monozygotic (MZ) and dizygotic (DZ) twins and to estimate the relative contributions of genetic and environmental factors to the variability in liability to T1D as well as to study the age at onset of diabetes in twins; (2) to obtain long-term empirical estimates of the risk of T1D among siblings of T1D patients and the factors related to this risk, especially the effect of age at onset of diabetes in the proband and the birth cohort effect; (3) to establish if DN is aggregating in a Finnish population-based cohort of families with multiple cases of T1D, and to assess its magnitude and particularly to find out whether the risk of DN in siblings is varying according to the severity of DN in the proband and/or the age at onset of T1D: (4) to assess the recurrence risk of T1D in the offspring of a Finnish population-based cohort of patients with childhood onset T1D, and to investigate potential sex-related effects in the transmission of T1D from the diabetic parents to their offspring as well as to study whether there is a temporal trend in the incidence. The study population comprised of the Finnish Young Twin Cohort (22,650 twin pairs), a population-based cohort of patients with T1D diagnosed at the age of 17 years or earlier between 1965 and 1979 (n=5,144) and all their siblings (n=10,168) and offspring (n=5,291). A polygenic, multifactorial liability model was fitted to the twin data. Kaplan-Meier analyses were used to provide the cumulative incidence for the development of T1D and DN. Cox s proportional hazards models were fitted to the data. Poisson regression analysis was used to evaluate temporal trends in incidence. Standardized incidence ratios (SIRs) between the first-degree relatives of T1D patients and background population were determined. The twin study showed that the vast majority of affected MZ twin pairs remained discordant. Pairwise concordance for T1D was 27.3% in MZ and 3.8% in DZ twins. The probandwise concordance estimates were 42.9% and 7.4%, respectively. The model with additive genetic and individual environmental effects was the best-fitting liability model to T1D, with 88% of the phenotypic variance due to genetic factors. The second paper showed that the 50-year cumulative incidence of T1D in the siblings of diabetic probands was 6.9%. A young age at diagnosis in the probands considerably increased the risk. If the proband was diagnosed at the age of 0-4, 5-9, 10-14, 15 or more, the corresponding 40-year cumulative risks were 13.2%, 7.8%, 4.7% and 3.4%. The cumulative incidence increased with increasing birth year. However, SIR among children aged 14 years or under was approximately 12 throughout the follow-up. The third paper showed that diabetic siblings of the probands with nephropathy had a 2.3 times higher risk of DN compared with siblings of probands free of nephropathy. The presence of end stage renal disease (ESRD) in the proband increases the risk three-fold for diabetic siblings. Being diagnosed with diabetes during puberty (10-14) or a few years before (5-9) increased the susceptibility for DN in the siblings. The fourth paper revealed that of the offspring of male probands, 7.8% were affected by the age of 20 compared with 5.3% of the offspring of female probands. Offspring of fathers with T1D have 1.7 times greater risk to be affected with T1D than the offspring of mothers with T1D. The excess risk in the offspring of male fathers manifested itself through the higher risk the younger the father was when diagnosed with T1D. Young age at onset of diabetes in fathers increased the risk of T1D greatly in the offspring, but no such pattern was seen in the offspring of diabetic mothers. The SIR among offspring aged 14 years or under remained fairly constant throughout the follow-up, approximately 10. The present study has provided new knowledge on T1D recurrence risk in the first-degree relatives and the risk factors modifying the risk. Twin data demonstrated high genetic liability for T1D and increased heritability. The vast majority of affected MZ twin pairs, however, remain discordant for T1D. This study confirmed the drastic impact of the young age at onset of diabetes in the probands on the increased risk of T1D in the first-degree relatives. The only exception was the absence of this pattern in the offspring of T1D mothers. Both the sibling and the offspring recurrence risk studies revealed dynamic changes in the cumulative incidence of T1D in the first-degree relatives. SIRs among the first-degree relatives of T1D patients seems to remain fairly constant. The study demonstrates that the penetrance of the susceptibility genes for T1D may be low, although strongly influenced by the environmental factors. Presence of familial aggregation of DN was confirmed for the first time in a population-based study. Although the majority of the sibling pairs with T1D were discordant for DN, its presence in one sibling doubles and presence of ESRD triples the risk of DN in the other diabetic sibling. An encouraging observation was that although the proportion of children to be diagnosed with T1D at the age of 4 or under is increasing, they seem to have a decreased risk of DN or at least delayed onset.

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The worldwide health burden caused by the tobacco epidemic highlights the importance of study-ing determinants of smoking behaviour and key factors sustaining nicotine dependence. Despite vast-ranging preventive efforts, smoking remains one of the most deleterious health behaviours, and its genetic and environmental factors warrant continuous investigation. The heritability of smoking behaviour and nicotine dependence has been suggested to be relatively high. Earlier smoking behaviour, nicotine dependence, socio-economic position and demographic factors have all been shown to be associated with smoking cessation. This thesis aimed to examine various aspects of smoking behaviour and nicotine dependence from an epidemiological and genetic per-spective. Data for Studies I and IV were obtained from the Older Finnish Twin Cohort, a postal health sur-vey conducted in 1975, 1981 and 1990 on same-sexed pairs and in 1996-1997 on male-female adult pairs. The number of ever-smoking participants was 8941 in Study I and 3069 in Study IV. Data for Studies II and III came from the Family Study of Cigarette Smoking - Vulnerability to Nicotine Addiction. This study is linked to the Older Finnish Twin Cohort with new data collec-tion during 2001-2006 that focused on smoking twin pairs and their family members. The meas-ures included intensive telephone interviews, blood samples and additional postal questionnaires. The numbers of ever-smoking participants was 1370 in Study II and 529 in Study III. Study I examined whether a genetic component underlies smoking behaviour among Finnish adults. Genetic factors were important in the amount smoked and smoking cessation, with about half of the phenotypic differences explained by genetic variance. A novel finding was that genetic influences on amount smoked and smoking cessation were largely independent of genetic influ-ences on age at initiation. This result has implications for defining phenotypes in the search for genes underlying smoking behaviour. Furthermore, even if smoking initiation is postponed to a later age, potential vulnerability to subsequent nicotine dependence cannot be completely inhib-ited. Study II investigated the effect of genetic and environmental factors on nicotine dependence, as measured by the novel multidimensional Nicotine Dependence Syndrome Scale (NDSS). This scale was validated in the Finnish data. The NDSS correlated highly with other established nico-tine dependence scales (FTND and DSM-IV), suggesting that this new scale would be a feasible and valid measure for identifying nicotine-dependent smokers among the ever-smoking popula-tion. About one-third of the phenotypic variation in nicotine dependence in this sample was ex-plained by genetic influences. Study III aimed at identifying chromosomal regions harbouring genes that influence smoking be-haviour and nicotine dependence. Linkage analysis of family data revealed that for smoker and nicotine dependence phenotypes as well as for co-morbidity between nicotine dependence and alcohol use signals on specific chromosome regions (chromosomes 2q33, 5q12, 5q34 7q21, 7q31, 10q25, 11p15, 20p13) exist. Results further support the hypothesis that smoking behaviour phe-notypes have a genetic background. Study IV examined associations of smoking behaviour, socio-economic position and transition of marital status with smoking cessation. Indicators of socio-economic position were important pre-dictors of smoking cessation even when adjusted for previous smoking behaviour. Getting married was associated with an increased probability of cessation in men, a finding confirmed among dis-cordant twin pairs. Thus, having a partner appears to have a positive impact on smoking cessation. In conclusion, nicotine dependence and smoking behaviour demonstrate significant genetic liabil-ity, but also substantial environmental influences among Finnish adults. Smoking initiation should be prevented or at least postponed to a later age. Although genetic factors are important in nicotine dependence and smoking behaviour, societal actions still have a primary role in tobacco control and smoking prevalence. Future studies should examine the complex interactions between genetic and environmental factors in nicotine dependence.

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Androgenetic alopecia (AGA) is a highly heritable condition and the most common form of hair loss in humans. Susceptibility loci have been described on the X chromosome and chromosome 20, but these loci explain a minority of its heritable variance. We conducted a large-scale meta-analysis of seven genome-wide association studies for early-onset AGA in 12,806 individuals of European ancestry. While replicating the two AGA loci on the X chromosome and chromosome 20, six novel susceptibility loci reached genome-wide significance (p = 2.62x10(-)(9)-1.01x10(-)(1)(2)). Unexpectedly, we identified a risk allele at 17q21.31 that was recently associated with Parkinson's disease (PD) at a genome-wide significant level. We then tested the association between early-onset AGA and the risk of PD in a cross-sectional analysis of 568 PD cases and 7,664 controls. Early-onset AGA cases had significantly increased odds of subsequent PD (OR = 1.28, 95% confidence interval: 1.06-1.55, p = 8.9x10(-)(3)). Further, the AGA susceptibility alleles at the 17q21.31 locus are on the H1 haplotype, which is under negative selection in Europeans and has been linked to decreased fertility. Combining the risk alleles of six novel and two established susceptibility loci, we created a genotype risk score and tested its association with AGA in an additional sample. Individuals in the highest risk quartile of a genotype score had an approximately six-fold increased risk of early-onset AGA [odds ratio (OR) = 5.78, p = 1.4x10(-)(8)(8)]. Our results highlight unexpected associations between early-onset AGA, Parkinson's disease, and decreased fertility, providing important insights into the pathophysiology of these conditions.

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There is evidence across several species for genetic control of phenotypic variation of complex traits1, 2, 3, 4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ~170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5, 6, 7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ~0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9, 10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

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State and parameter estimations of non-linear dynamical systems, based on incomplete and noisy measurements, are considered using Monte Carlo simulations. Given the measurements. the proposed method obtains the marginalized posterior distribution of an appropriately chosen (ideally small) subset of the state vector using a particle filter. Samples (particles) of the marginalized states are then used to construct a family of conditionally linearized system of equations and thus obtain the posterior distribution of the states using a bank of Kalman filters. Discrete process equations for the marginalized states are derived through truncated Ito-Taylor expansions. Increased analyticity and reduced dispersion of weights computed over a smaller sample space of marginalized states are the key features of the filter that help achieve smaller sample variance of the estimates. Numerical illustrations are provided for state/parameter estimations of a Duffing oscillator and a 3-DOF non-linear oscillator. Performance of the filter in parameter estimation is also assessed using measurements obtained through experiments on simple models in the laboratory. Despite an added computational cost, the results verify that the proposed filter generally produces estimates with lower sample variance over the standard sequential importance sampling (SIS) filter.