INSIG1 influences obesity-related hypertriglyceridemia in humans

In our analysis of a quantitative trait locus (QTL) for plasma triglyceride (TG) levels [logarithm of odds (LOD) = 3.7] on human chromosome 7q36, we examined 29 single nucleotide polymorphisms (SNPs) across INSIG1, a biological candidate gene in the region. Insulin-induced genes (INSIGs) are feedback mediators of cholesterol and fatty acid synthesis in animals, but their role in human lipid regulation is unclear. In our cohort, the INSIG1 promoter SNP rs2721 was associated with TG levels (P = 2 × 10−3 in 1,560 individuals of the original linkage cohort, P = 8 × 10−4 in 920 unrelated individuals of the replication cohort, combined P = 9.9 × 10−6). Individuals homozygous for the T allele had 9% higher TG levels and 2-fold lower expression of INSIG1 in surgical liver biopsy samples when compared with individuals homozygous for the G allele. Also, the T allele showed additional binding of nuclear proteins from HepG2 liver cells in gel shift assays. Finally, the variant rs7566605 in INSIG2, the only homolog of INSIG1, enhances the effect of rs2721 (P = 0.00117). The variant rs2721 alone explains 5.4% of the observed linkage in our cohort, suggesting that additional, yet-undiscovered genes and sequence variants in the QTL interval also contribute to alterations in TG levels in humans

Epigenetic Age Acceleration Assessed with Human White-Matter Images

Item does not contain fulltextThe accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (rhopheno = -0.119, p = 0.028), with evidence of shared genetic (rhogene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging

Quartz Tuning Fork: Thermometer, Pressure- and Viscometer for Helium Liquids

Commercial quartz oscillators of the tuning-fork type with a resonant frequency of ∼ 32 kHz have been investigated in helium liquids. The oscillators are found to have at best Q values in the range 10⁵–10⁶, when measured in vacuum below 1.5 K. However, the variability is large and for very low temperature operation the sensor has to be preselected. We explore their properties in the regime of linear viscous hydrodynamic response in normal and superfluid ³He and ⁴He, by comparing measurements to the hydrodynamic model of the sensor

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. 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. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction