Cortisol is an important stress hormone affected by a variety of biological and environmental factors, such as the circadian rhythm, exercise and psychological stress. Cortisol is mostly measured using blood or saliva samples. A number of genetic variants have been found to contribute to cortisol levels with these methods. While the effects of several specific single genetic variants is known, the joint genome-wide contribution to cortisol levels is unclear. Our aim was to estimate the amount of cortisol variance explained by common single nucleotide polymorphisms, i.e. the SNP heritability, using a variety of cortisol measures, cohorts and analysis approaches. We analyzed morning plasma (n=5705) and saliva levels (n=1717), as well as diurnal saliva levels (n=1541), in the Rotterdam Study using genomic restricted maximum likelihood estimation. Additionally, linkage disequilibrium score regression was fitted on the results of genome-wide association studies (GWAS) performed by the CORNET consortium on morning plasma cortisol (n=12,597) and saliva cortisol (n=7703). No significant SNP heritability was detected for any cortisol measure, sample or analysis approach. Point estimates ranged from 0% to 9%. Morning plasma cortisol in the CORNET cohorts, the sample with the most power, had a 6% [95%CI: 0-13%] SNP heritability. The results consistently suggest a low SNP heritability of these acute and short-term measures of cortisol. The low SNP heritability may reflect the substantial environmental and, in particular, situational component of these cortisol measures. Future GWAS will require very large sample sizes. Alternatively, more long-term cortisol measures such as hair cortisol samples are needed to discover further genetic pathways regulating cortisol concentrations.
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http://dx.doi.org/10.1016/j.psyneuen.2017.08.011 | DOI Listing |
Prog Neuropsychopharmacol Biol Psychiatry
January 2025
Institute of Brain Science, National Yang-Ming Chiao Tung University, Taipei 11221, Taiwan; Brain Research Center, National Yang-Ming Chiao Tung University, Taipei 11221, Taiwan; Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan. Electronic address:
While the etiology of schizophrenia (SZ) remains elusive, its diverse phenotypes suggest the involvement of distinct functional cortical areas, and the heritability of SZ implies the underlying genetic factors. This study aimed to integrate imaging and molecular analyses to elucidate the genetic underpinnings of SZ. We investigated the local cortical structural pattern changes in Brodmann areas (BAs) by calculating the cortical structural pattern index (SPI) using magnetic resonance imaging analysis from 194 individuals with SZ and 330 controls.
View Article and Find Full Text PDFPlants (Basel)
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Plant Breeding, Wageningen University & Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.
Faba bean ( L.) is a valuable ingredient in plant-based foods such as meat and dairy analogues. However, its typical taste and aroma are considered off-flavours in these food applications, representing a bottleneck during processing.
View Article and Find Full Text PDFAnimals (Basel)
January 2025
Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
Goats are essential to the dairy industry in Shaanxi, China, with udder traits playing a critical role in determining milk production and economic value for breeding programs. However, the direct measurement of these traits in dairy goats is challenging and resource-intensive. This study leveraged genotyping imputation to explore the genetic parameters and architecture of udder traits and assess the efficiency of genomic prediction methods.
View Article and Find Full Text PDFCommun Biol
January 2025
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, so together may provide a more complete picture of sleep health, while illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches.
View Article and Find Full Text PDFBMC Cancer
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Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China.
Background: Genome-wide association studies (GWAS) provide a powerful method for identifying the loci and genes that contribute to disease. However, in many cases, the specific cell types and states that confer disease risk through these genes remain unknown. Determining this relationship is crucial for identifying pathogenic processes and developing therapeutic strategies.
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