Biology subjects

Ribases, M.

Publications and source records attributed to Ribases, M..

4 recordsLinked to original sources

bioRxiv2019

The Role of Gene Encoding Variation of DRD4 in the Relationship between Inattention and Seasonal Daylight

Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=-0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R-carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.

genetics↗

bioRxiv2019

Identification of risk variants and characterization of the polygenic architecture of disruptive behavior disorders in the context of ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). ADHD comorbid with DBDs (ADHD+DBDs) is a complex phenotype with a risk component that can be attributed to common genetic variants. Here we report a large GWAS meta-analysis of ADHD+DBDs based on seven cohorts in total including 3,802 cases and 31,305 controls. Three genome-wide significant loci were identified on chromosomes 1, 7, and 11. A GWAS meta-analysis including a Chinese cohort supported the locus on chromosome 11 to be a strong risk locus for ADHD+DBDs across European and Chinese ancestries (rs7118422, P=3.15x10-10, OR=1.17). This locus was not associated with ADHD without DBDs in a secondary GWAS of 13,583 ADHD cases and 22,314 controls, suggesting that the locus is a specific risk locus for the comorbid phenotype.\n\nWe found a higher SNP heritability for ADHD+DBDs (h2SNP =0.34) when compared to ADHD without DBDs (h2SNP =0.20). Genetic correlations of ADHD+DBDs with aggressive (rg =0.81) and anti-social behaviors (rg=0.82) were high, and polygenic risk score analyses revealed a significant increased burden of variants associated with ADHD and aggression in individuals with ADHD+DBDs compared to ADHD without DBDs. Our results suggests that ADHD+DBDs represent a more severe phenotype with respect to the genetic risk load than ADHD without DBDs, in line with previous studies, and that the risk load to some extent can be explained by variants associated with aggressive behavior.

genomics↗

bioRxiv2018

The Subtype Specificity of Genetic Loci Associated with Stroke in 16,664 cases and 32,792 controls

BackgroundGenome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes.\n\nMethodsWe performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel.\n\nResultsSixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes.\n\nConclusionsHeterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

genetics↗

bioRxiv2018

Genome-wide association analysis of lifetime cannabis use (N=184,765) identifies new risk loci, genetic overlap with mental health, and a causal influence of schizophrenia on cannabis use

Cannabis use is a heritable trait [1] that has been associated with adverse mental health outcomes. To identify risk variants and improve our knowledge of the genetic etiology of cannabis use, we performed the largest genome-wide association study (GWAS) meta-analysis for lifetime cannabis use (N=184,765) to date. We identified 4 independent loci containing genome-wide significant SNP associations. Gene-based tests revealed 29 genome-wide significant genes located in these 4 loci and 8 additional regions. All SNPs combined explained 10% of the variance in lifetime cannabis use. The most significantly associated gene, CADM2, has previously been associated with substance use and risk-taking phenotypes [2-4]. We used S-PrediXcan to explore gene expression levels and found 11 unique eGenes. LD-score regression uncovered genetic correlations with smoking, alcohol use and mental health outcomes, including schizophrenia and bipolar disorder. Mendelian randomisation analysis provided evidence for a causal positive influence of schizophrenia risk on lifetime cannabis use.

genetics↗