Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UKBiobank

Our sleep timing preference, or chronotype, is a manifestation of our internal biological clock. Variation in chronotype has been linked to sleep disorders, cognitive and physical performance, and chronic disease. Here, we perform a genome-wide association study of self-reported chronotype within the UKBiobank cohort (n=100,420). We identify 12 new genetic loci that implicate known components of the circadian clock machinery and point to previously unstudied genetic variants and candidate genes that might modulate core circadian rhythms or light-sensing pathways. Pathway analyses highlight central nervous and ocular systems and fear-response related processes. Genetic correlation analysis suggests chronotype shares underlying genetic pathways with schizophrenia, educational attainment and possibly BMI. Further, Mendelian randomization suggests that evening chronotype relates to higher educational attainment. These results not only expand our knowledge of the circadian system in humans, but also expose the influence of circadian characteristics over human health and life-history variables such as educational attainment.

Download Full-text

A Genome-Wide Association Study of Educational Attainment

SSRN Electronic Journal ◽

10.2139/ssrn.1655023 ◽

2010 ◽

Cited By ~ 1

Author(s):

Jonathan Beauchamp ◽

David Cesarini ◽

Matthijs J. H. M. van der Loos ◽

P. Koellinger ◽

Patrick J. F. Groenen ◽

...

Keyword(s):

Educational Attainment ◽

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

Download Full-text

Educational Attainment: A Genome Wide Association Study in 9538 Australians

PLoS ONE ◽

10.1371/journal.pone.0020128 ◽

2011 ◽

Vol 6 (6) ◽

pp. e20128 ◽

Cited By ~ 15

Author(s):

Nicolas W. Martin ◽

Sarah E. Medland ◽

Karin J. H. Verweij ◽

S. Hong Lee ◽

Dale R. Nyholt ◽

...

Keyword(s):

Educational Attainment ◽

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

Download Full-text

Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia

10.1101/114405 ◽

2017 ◽

Cited By ~ 2

Author(s):

V. Bansal ◽

M. Mitjans ◽

C.A.P. Burik ◽

R.K. Linnér ◽

A. Okbay ◽

...

Keyword(s):

Educational Attainment ◽

Association Study ◽

Genetic Heterogeneity ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Clear Pattern ◽

Replication Cohort ◽

Genome Wide ◽

Study Results ◽

Higher Educational Attainment

ABSTRACTHigher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigated possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1,169 controls; 1,067 cases) with deeply phenotyped SZ patients. We found strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Genetic heterogeneity of SZ contributes to this finding. We demonstrate this by showing that the polygenic prediction of clinical SZ symptoms can be improved by taking the sign concordance of loci for EA and SZ into account. Furthermore, using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ.

Download Full-text

Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia

Molecular Psychiatry ◽

10.1038/s41380-020-00898-x ◽

2020 ◽

Cited By ~ 1

Author(s):

Alessandro Gialluisi ◽

Till F. M. Andlauer ◽

Nazanin Mirza-Schreiber ◽

Kristina Moll ◽

Jessica Becker ◽

...

Keyword(s):

Bipolar Disorder ◽

Educational Attainment ◽

Association Study ◽

Developmental Dyslexia ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Standard Deviation Increase ◽

Genome Wide ◽

Common Genetic Variants ◽

A Genome

Abstract Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40–60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10−6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20–25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10−13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10−43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10−22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10−12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10−4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10−7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10−29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.

Download Full-text

A genome-wide association study implicates multiple mechanisms influencing raised urinary albumin–creatinine ratio

Human Molecular Genetics ◽

10.1093/hmg/ddz243 ◽

2019 ◽

Vol 28 (24) ◽

pp. 4197-4207 ◽

Cited By ~ 2

Author(s):

Francesco Casanova ◽

Jessica Tyrrell ◽

Robin N Beaumont ◽

Yingjie Ji ◽

Samuel E Jones ◽

...

Keyword(s):

Association Study ◽

Genome Wide Association Study ◽

Genetic Risk Score ◽

Genome Wide Association ◽

Creatinine Ratio ◽

Microvascular Damage ◽

Albumin Creatinine Ratio ◽

Genome Wide ◽

A Genome ◽

Pathway Analyses

Abstract Raised albumin–creatinine ratio (ACR) is an indicator of microvascular damage and renal disease. We aimed to identify genetic variants associated with raised ACR and study the implications of carrying multiple ACR-raising alleles with metabolic and vascular-related disease. We performed a genome-wide association study of ACR using 437 027 individuals from the UK Biobank in the discovery phase, 54 527 more than previous studies, and followed up our findings in independent studies. We identified 62 independent associations with ACR across 56 loci (P < 5 × 10–8), of which 20 were not previously reported. Pathway analyses and the identification of 20 of the 62 variants (at r2 > 0.8) coinciding with signals for at least 16 related metabolic and vascular traits, suggested multiple pathways leading to raised ACR levels. After excluding variants at the CUBN locus, known to alter ACR via effects on renal absorption, an ACR genetic risk score was associated with a higher risk of hypertension, and less strongly, type 2 diabetes and stroke. For some rare genotype combinations at the CUBN locus, most individuals had ACR levels above the microalbuminuria clinical threshold. Contrary to our hypothesis, individuals carrying more CUBN ACR-raising alleles, and above the clinical threshold, had a higher frequency of vascular disease. The CUBN allele effects on ACR were twice as strong in people with diabetes—a result robust to an optimization-algorithm approach to simulating interactions, validating previously reported gene–diabetes interactions (P ≤ 4 × 10–5). In conclusion, a variety of genetic mechanisms and traits contribute to variation in ACR.

Download Full-text