Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

Background: The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families.

Methods: The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF).

Common polygenic variation contributes to risk of migraine in the Norfolk Island population.

Migraine has been defined as a common disabling primary headache disorder. Epidemiology studies have provided with the undeniable evidence of genetic components as active players in the development of the disease under a polygenic model in which multiple risk alleles exert modest individual effects. Our objective was to test the contribution of a polygenic effect to migraine risk in the Norfolk Island population using a panel of SNPs reported to be disease associated in published migraine GWAS.

Quantitative physical activity assessment of children and adolescents in a rural population from Eastern Nepal.

Objectives: We report cross-sectional, objectively measured physical activity data for 399 children and adolescents aged 6 to 18 years. We evaluated physical activity of children and adolescents, considered time spent in each activity intensity category, and explored the impact of growth disruption (stunting and wasting) on physical activity patterns.

Methods: Participants wore an Actical (Mini-Mitter, Bend, OR) omnidirectional accelerometer for one week as part of their annual visit to the Jiri Growth Study.

Intergenerational neural mediators of early-life anxious temperament.

Understanding the heritability of neural systems linked to psychopathology is not sufficient to implicate them as intergenerational neural mediators. By closely examining how individual differences in neural phenotypes and psychopathology cosegregate as they fall through the family tree, we can identify the brain systems that underlie the parent-to-child transmission of psychopathology. Although research has identified genes and neural circuits that contribute to the risk of developing anxiety and depression, the specific neural systems that mediate the inborn risk for these debilitating disorders remain unknown.

Interaction between Common Genetic Variants and Total Fat Intake on Low-Density Lipoprotein Peak Particle Diameter: A Genome-Wide Association Study.

Background/aim: Total fat intake has an important impact on the low-density lipoprotein (LDL) peak particle diameter (LDL-PPD) and may interact with nutrient-sensitive single nucleotide polymorphisms (SNPs). The objective was to examine whether there is suggestive evidence of SNP × dietary fat intake interaction effects influencing the LDL-PPD in the Quebec Family Study (QFS) in order to generate hypotheses to be tested in larger studies.

Methods: SNPs from a genome-wide association study (GWAS) using Illumina Human610-Quad BeadChip, total fat intake derived from a 3-day weighted food record, and SNP × total fat intake interaction effects were examined on LDL-PPD in 541 QFS subjects.

Novel epigenetic determinants of type 2 diabetes in Mexican-American families.

Although DNA methylation is now recognized as an important mediator of complex diseases, the extent to which the genetic basis of such diseases is accounted for by DNA methylation is unknown. In the setting of large, extended families representing a minority, high-risk population of the USA, we aimed to characterize the role of epigenome-wide DNA methylation in type 2 diabetes (T2D). Using Illumina HumanMethylation450 BeadChip arrays, we tested for association of DNA methylation at 446 356 sites with age, sex and phenotypic traits related to T2D in 850 pedigreed Mexican-American individuals.

Sequencing strategies and characterization of 721 vervet monkey genomes for future genetic analyses of medically relevant traits.

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.

Evaluation of neurotrophic tyrosine receptor kinase 2 (NTRK2) as a positional candidate gene for variation in estimated glomerular filtration rate (eGFR) in Mexican American participants of San Antonio Family Heart study.

Background: The estimated glomerular filtration rate (eGFR) is a well-known measure of kidney function and is commonly used for the diagnosis and management of patients with chronic kidney disease. The inter-individual variation in eGFR has significant genetic component. However, the identification of underlying genetic susceptibility variants has been challenging.

Axial quantitative ultrasound assessment of pediatric bone quality in eastern Nepal.

Unlabelled: This study presents quantitative ultrasonography (QUS) bone quality data for an underrepresented, south Asian pediatric population from Nepal. Data were collected as part of a longitudinal study of growth and development. This study offers normative data and documents the effect of stunting, wasting, and underweight on the bone properties measured by QUS.

Transcriptomic identification of ADH1B as a novel candidate gene for obesity and insulin resistance in human adipose tissue in Mexican Americans from the Veterans Administration Genetic Epidemiology Study (VAGES).

Type 2 diabetes (T2D) is a complex metabolic disease that is more prevalent in ethnic groups such as Mexican Americans, and is strongly associated with the risk factors obesity and insulin resistance. The goal of this study was to perform whole genome gene expression profiling in adipose tissue to detect common patterns of gene regulation associated with obesity and insulin resistance. We used phenotypic and genotypic data from 308 Mexican American participants from the Veterans Administration Genetic Epidemiology Study (VAGES).

Fast and powerful heritability inference for family-based neuroimaging studies.

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software cannot estimate heritability, and yet standard quantitative genetics tools cannot provide essential neuroimaging inferences, like family-wise error corrected voxel-wise or cluster-wise P-values.

Non-crossover gene conversions show strong GC bias and unexpected clustering in humans.

Although the past decade has seen tremendous progress in our understanding of fine-scale recombination, little is known about non-crossover (NCO) gene conversion. We report the first genome-wide study of NCO events in humans. Using SNP array data from 98 meioses, we identified 103 sites affected by NCO, of which 50/52 were confirmed in sequence data.

An epigenetic map of age-associated autosomal loci in northern European families at high risk for the metabolic syndrome.

Background: The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array.

Shared genetic variance between obesity and white matter integrity in Mexican Americans.

Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18-81 years; 41.3 ± 14.

Genome-wide genetic investigation of serological measures of common infections.

Populations and individuals differ in susceptibility to infections because of a number of factors, including host genetic variation. We previously demonstrated that differences in antibody titer, which reflect infection history, are significantly heritable. Here we attempt to identify the genetic factors influencing variation in these serological phenotypes.

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data.

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods.

Genome-Wide Analyses of Working-Memory Ability: A Review.

Working memory, a theoretical construct from the field of cognitive psychology, is crucial to everyday life. It refers to the ability to temporarily store and manipulate task-relevant information. The identification of genes for working memory might shed light on the molecular mechanisms of this important cognitive ability and-given the genetic overlap between, for example, schizophrenia risk and working-memory ability-might also reveal important candidate genes for psychiatric illness.

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)).

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively.

Common genetic variants influence human subcortical brain structures.

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts.

Effects of copy number variable regions on local gene expression in white blood cells of Mexican Americans.

Only few systematic studies on the contribution of copy number variation to gene expression variation have been published to date. Here we identify effects of copy number variable regions (CNVRs) on nearby gene expression by investigating 909 CNVRs and expression levels of 12059 nearby genes in white blood cells from Mexican-American participants of the San Antonio Family Heart Study. We empirically evaluate our ability to detect the contribution of CNVs to proximal gene expression (presumably in cis) at various window sizes (up to a 10 Mb distance) between the gene and CNV.

Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines.

Imaging genetics is an emerging methodological field that combines genetic information with medical imaging-derived metrics to understand how genetic factors impact observable phenotypes. In order for a trait to be a reasonable phenotype in an imaging genetics study, it must be heritable: at least some proportion of its variance must be due to genetic influences. The Sequential Oligogenic Linkage Analysis Routines (SOLAR) imaging genetics software can estimate the heritability of a trait in complex pedigrees.

Evaluation of estimated genetic values and their application to genome-wide investigation of systolic blood pressure.

The concept of breeding values, an individual's phenotypic deviation from the population mean as a result of the sum of the average effects of the genes they carry, is of great importance in livestock, aquaculture, and cash crop industries where emphasis is placed on an individual's potential to pass desirable phenotypes on to the next generation. As breeding or genetic values (as referred to here) cannot be measured directly, estimated genetic values (EGVs) are based on an individual's own phenotype, phenotype information from relatives, and, increasingly, genetic data. Because EGVs represent additive genetic variation, calculating EGVs in an extended human pedigree is expected to provide a more refined phenotype for genetic analyses.

A variance component-based gene burden test.

We propose a novel variance component approach for the analysis of next-generation sequencing data. Our method is based on the detection of the proportion of the trait phenotypic variance that can be explained by the introduction of a new variance component that accounts for the local gene-specific departure of the empirical kinship relationship matrix, estimated from single-nucleotide polymorphism (SNP) genotypes, from their theoretical expectation based on the genealogical information in the pedigree. We tested our method with simulated phenotypes and imputed SNP genotypes from the Genetic Analysis Workshop 18 data set.