Search

Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this research, we show that Asparouhov and Muthén's alignment method can be adapted to align data from disparate item sets and response formats. We argue that with these adaptations, the alignment method is well suited for combining data across multiple sites even when they use different measurement instruments. The approach is illustrated using data from the Whole Genome Sequencing in Psychiatric Disorders consortium and a real-data-based simulation is used to verify accurate parameter recovery. Factor alignment appears to increase precision of measurement and validity of scores with respect to external criteria. The resulting parameter estimates may further inform development of more effective and efficient methods to assess the same constructs in prospectively designed studies. [ABSTRACT FROM AUTHOR]

The observation that variants regulating gene expression (expression quantitative trait loci, eQTL) are at a high frequency among SNPs associated with complex traits has made the genome-wide characterization of gene expression an important tool in genetic mapping studies of such traits. As part of a study to identify genetic loci contributing to bipolar disorder and other quantitative traits in members of 26 pedigrees from Costa Rica and Colombia, we measured gene expression in lymphoblastoid cell lines derived from 786 pedigree members. The study design enabled us to comprehensively reconstruct the genetic regulatory network in these families, provide estimates of heritability, identify eQTL, evaluate missing heritability for the eQTL, and quantify the number of different alleles contributing to any given locus. In the eQTL analysis, we utilize a recently proposed hierarchical multiple testing strategy which controls error rates regarding the discovery of functional variants. Our results elucidate the heritability and regulation of gene expression in this unique Latin American study population and identify a set of regulatory SNPs which may be relevant in future investigations of complex disease in this population. Since our subjects belong to extended families, we are able to compare traditional kinship-based estimates with those from more recent methods that depend only on genotype information. [ABSTRACT FROM AUTHOR]

Background: We report here the first genome-wide high-resolution polymorphism resource for non-human primate (NHP) association and linkage studies, constructed for the Caribbean-origin vervet monkey, or African green monkey (Chlorocebus aethiops sabaeus), one of the most widely used NHPs in biomedical research. We generated this resource by whole genome sequencing (WGS) of monkeys from the Vervet Research Colony (VRC), an NIH-supported research resource for which extensive phenotypic data are available. Results: We identified genome-wide single nucleotide polymorphisms (SNPs) by WGS of 721 members of an extended pedigree from the VRC. From high-depth WGS data we identified more than 4 million polymorphic unequivocal segregating sites; by pruning these SNPs based on heterozygosity, quality control filters, and the degree of linkage disequilibrium (LD) between SNPs, we constructed genome-wide panels suitable for genetic association (about 500,000 SNPs) and linkage analysis (about 150,000 SNPs). To further enhance the utility of these resources for linkage analysis, we used a further pruned subset of the linkage panel to generate multipoint identity by descent matrices. Conclusions: The genetic and phenotypic resources now available for the VRC and other Caribbean-origin vervets enable their use for genetic investigation of traits relevant to human diseases. [ABSTRACT FROM AUTHOR]

Background: Investigation of the environmental influences on human behavioral phenotypes is important for our understanding of the causation of psychiatric disorders. However, there are complexities associated with the assessment of environmental influences on behavior. Methods/Principal Findings: We conducted a series of analyses using a prospective, longitudinal study of a nationally representative birth cohort from Finland (the Northern Finland 1966 Birth Cohort). Participants included a total of 3,761 male and female cohort members who were living in Finland at the age of 16 years and who had complete temperament scores. Our initial analyses (Wessman et al., in press) provide evidence in support of four stable and robust temperament clusters. Using these temperament clusters, as well as independent temperament dimensions for comparison, we conducted a data-driven analysis to assess the influence of a broad set of life course measures, assessed pre-natally, in infancy, and during adolescence, on adult temperament. Results: Measures of early environment, neurobehavioral development, and adolescent behavior significantly predict adult temperament, classified by both cluster membership and temperament dimensions. Specifically, our results suggest that a relatively consistent set of life course measures are associated with adult temperament profiles, including maternal education, characteristics of the family's location and residence, adolescent academic performance, and adolescent smoking. Conclusions: Our finding that a consistent set of life course measures predict temperament clusters indicate that these clusters represent distinct developmental temperament trajectories and that information about a subset of life course measures has implications for adult health outcomes. [ABSTRACT FROM AUTHOR]

The area and volume of brain structural features, as assessed by high-resolution three-dimensional magnetic resonance imaging (MRI), are among the most heritable measures relating to the human CNS. We have conducted MRI scanning of all available monkeys>2 years of age (n=357) from the extended multigenerational pedigree of the Vervet Research Colony (VRC). Using a combination of automated and manual segmentation we have quantified several correlated but distinct brain structural phenotypes. The estimated heritabilities (h²) for these measures in theVRCare higher than those reported previously for such features in humans or in othernonhumanprimates: total brain volume (h²=0.99, SE=0.06), cerebral volume (h²=0.98, SE=0.06), cerebellar volume (h²=[0.86, SE=0.09), hippocampal volume (h² =0.95, SE = 0.07) and corpus callosum cross-sectional areas (h² =0.87, SE = 0.07). These findings indicate that, in the controlled environment and with the inbreeding structure of the VRC, additive genetic factors account for almost all of the observed variance in brain structure, and suggest the potential of the VRC for genetic mapping of quantitative trait loci underlying such variance. [ABSTRACT FROM AUTHOR]

The article presents a replication study that evaluates the previous study on genotype-phenotype associations. The study concentrates on the initial discoveries which limit the plethora of false-positive results and determines the valid associations of genotype-phenotype. Three topics were addressed by the investigators, including the assessment of the validity and limitations of any genetic association, criteria for establishing the replication, and publication of high-quality association.

Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10−8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10−117). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10−4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.

Elucidating the molecular mechanisms underlying quantitative neurocognitive phenotypes will further our understanding of the brain''s structural and functional architecture and advance the diagnosis and treatment of the psychiatric disorders that these traits underlie. Although many neurocognitive traits are highly heritable, little progress has been made in identifying genetic variants unequivocally associated with these phenotypes. A major obstacle to such progress is the difficulty in identifying heritable neurocognitive measures that are precisely defined and systematically assessed and represent unambiguous mental constructs, yet are also amenable to the high-throughput phenotyping necessary to obtain adequate power for genetic association studies. In this perspective we compare the current status of genetic investigations of neurocognitive phenotypes to that of other categories of biomedically relevant traits and suggest strategies for genetically dissecting traits that may underlie disorders of brain and behavior. [Copyright &y& Elsevier]

Genetic investigations of psychiatric disease have historically relied on subjectively assessed disease diagnoses to define phenotypes. Recent developments in several areas have provided various new approaches to behavioral disorder phenotyping that promise to advance our understanding of the genetic and environmental etiologies of these traits. Such developments include re-evaluation of the boundaries between different psychiatric categories, implementation of quantitative neurobiological assessments that may serve as endophenotypes, generation of increasingly sophisticated animal behavioral models, and investigation of explicit environmental covariates. At the same time, movement toward large-scale, collaborative efforts is increasing the effectiveness of traditional genetic mapping approaches. [Copyright &y& Elsevier]