scholarly journals Biology of Perseverative Negative Thinking: The Role of Timing and Folate Intake

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4396
Author(s):  
Nora Eszlari ◽  
Bence Bruncsics ◽  
Andras Millinghoffer ◽  
Gabor Hullam ◽  
Peter Petschner ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Purinergic Signaling ◽  
Folate Intake ◽  
K Channel ◽  
Genetic Associations ◽  
Blastocyst Development ◽  
Eysenck Personality Inventory ◽  
Negative Thinking ◽  
A Genome ◽  
Neuroticism Scale

Past-oriented rumination and future-oriented worry are two aspects of perseverative negative thinking related to the neuroticism endophenotype and associated with depression and anxiety. Our present aim was to investigate the genomic background of these two aspects of perseverative negative thinking within separate groups of individuals with suboptimal versus optimal folate intake. We conducted a genome-wide association study in the UK Biobank database (n = 72,621) on the “rumination” and “worry” items of the Eysenck Personality Inventory Neuroticism scale in these separate groups. Optimal folate intake was related to lower worry, but unrelated to rumination. In contrast, genetic associations for worry did not implicate specific biological processes, while past-oriented rumination had a more specific genetic background, emphasizing its endophenotypic nature. Furthermore, biological pathways leading to rumination appeared to differ according to folate intake: purinergic signaling and circadian regulator gene ARNTL emerged in the whole sample, blastocyst development, DNA replication, and C-C chemokines in the suboptimal folate group, and prostaglandin response and K+ channel subunit gene KCNH3 in the optimal folate group. Our results point to possible benefits of folate in anxiety disorders, and to the importance of simultaneously taking into account genetic and environmental factors to determine personalized intervention in polygenic and multifactorial disorders.

scholarly journals GP.01 Childhood obesity and multiple sclerosis susceptibility: a Mendelian randomization study

2019 ◽  
Vol 46 (s1) ◽  
pp. S6 ◽  
Author(s):  
A Harroud ◽  
RE Mitchell ◽  
JA Morris ◽  
V Forgetta ◽  
SJ Sawcer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Childhood Obesity ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Significant Heterogeneity ◽  
Genetic Associations ◽  
Standard Deviation Increase ◽  
A Genome ◽  
The Individual

Background: Observational studies have reported an association between childhood obesity and a higher risk of multiple sclerosis (MS). However, the difficulties to fully account for confounding and long recall periods make causal inference from these studies challenging. The objective of this study was to assess the contribution of childhood obesity to the development of MS through Mendelian randomization, which uses genetic associations to minimize the risk of confounding. Methods: We selected 23 independent genetic variants strongly associated with childhood body mass index (BMI) in a genome-wide association study (GWAS) which included 47,541 children. The corresponding effects of these variants on risk of MS were obtained from a GWAS of 14,802 MS cases and 26,703 controls. Standard two-sample Mendelian randomization methods were performed, with additional sensitivity analyses to assess the likelihood of bias from genetic pleiotropy. Results: The inverse-variance weighted MR analysis revealed that one standard deviation increase in childhood BMI increased odds of MS by 26% (odds ratio=1.26, 95% confidence interval 1.10-1.45, p=0.001). There was no significant heterogeneity across the individual estimates. Sensitivity analyses were consistent with the main findings and provided no evidence of pleiotropy. Conclusions: This study provides genetic support of a role for increased childhood BMI in the development of MS.

scholarly journals Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

2018 ◽  
Author(s):  
Samuel E. Jones ◽  
Vincent T. van Hees ◽  
Diego R. Mazzotti ◽  
Pedro Marques-Vidal ◽  
Séverine Sabia ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Genome Wide Association Study ◽  
Missense Variant ◽  
Causal Variant ◽  
Self Report ◽  
Accelerometer Data ◽  
Genetic Associations ◽  
A Genome ◽  
The Uk

ABSTRACTSleep is an essential human function but its regulation is poorly understood. Identifying genetic variants associated with quality, quantity and timing of sleep will provide biological insights into the regulation of sleep and potential links with disease. Using accelerometer data from 85,670 individuals in the UK Biobank, we performed a genome-wide association study of 8 accelerometer-derived sleep traits, 5 of which are not accessible through self-report alone. We identified 47 genetic associations across the sleep traits (P<5×10-8) and replicated our findings in 5,819 individuals from 3 independent studies. These included 26 novel associations for sleep quality and 10 for nocturnal sleep duration. The majority of newly identified variants were associated with a single sleep trait, except for variants previously associated with restless legs syndrome that were associated with multiple sleep traits. Of the new associated and replicated sleep duration loci, we were able to fine-map a missense variant (p.Tyr727Cys) in PDE11A, a dual-specificity 3’,5’-cyclic nucleotide phosphodiesterase expressed in the hippocampus, as the likely causal variant. As a group, sleep quality loci were enriched for serotonin processing genes and all sleep traits were enriched for cerebellar-expressed genes. These findings provide new biological insights into sleep characteristics.

scholarly journals Genetic Associations with Subjective Well-Being Also Implicate Depression and Neuroticism

2015 ◽  
Author(s):  
Aysu Okbay ◽  
Bart M. L. Baselmans ◽  
Jan-Emmanuel De Neve ◽  
Patrick Turley ◽  
Michel G. Nivard ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Genome Wide Association Study ◽  
Well Being ◽  
Genome Wide Association ◽  
Subjective Well Being ◽  
Genetic Associations ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Significance

We conducted a genome-wide association study of subjective well-being (SWB) in 298,420 individuals. We also performed auxiliary analyses of depressive symptoms ("DS";N= 161,460) and neuroticism (N= 170,910), both of which have a substantial genetic correlation with SWB (ρ≈-0.8). We identify three SNPs associated with SWB at genome-wide significance. Two of them are significantly associated with DS in an independent sample. In our auxiliary analyses, we identify 13 additional genome-wide-significant associations: two with DS and eleven with neuroticism, including two inversion polymorphisms. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are enriched. The discovery of genetic loci associated with the three phenotypes we study has proven elusive; our findings illustrate the payoffs from studying them jointly.

Genetic associations with taxane-induced neuropathy by a genome-wide association study (GWAS) in E5103.

2011 ◽  
Vol 29 (15_suppl) ◽  
pp. 1000-1000 ◽  
Author(s):  
B. P. Schneider ◽  
L. Li ◽  
K. Miller ◽  
D. Flockhart ◽  
M. Radovich ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genetic Associations ◽  
Genome Wide ◽  
A Genome

297 Genetic associations of ICD in parkinson’s disease

2018 ◽  
Vol 89 (10) ◽  
pp. A47.2-A47
Author(s):  
Rees Richard ◽  
Hubbard Leon ◽  
Ben-Shlomo Yoav ◽  
Grosset Donald ◽  
Williams Nigel ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Genome Wide Association Study ◽  
Early Stage ◽  
Age At Onset ◽  
Genetic Associations ◽  
Longitudinal Assessment ◽  
Genetic Determinants ◽  
Genome Wide ◽  
A Genome

IntroductionImpuse Control Disorders (ICD) are a potentially devastating side-effect of dopaminergic therapy in Parkinson’s disease (PD). We explore the genetic factors associated with ICD in Tracking Parkinson’s/PRoBaND – a UK-wide cohort of early-stage PD.MethodsParticipants were diagnosed with PD within 3 years and had longitudinal assessment including the Questionnaire for ICD in Parkinson’s (QUIP) for up to 5 years. We defined cases as having any positive response to the QUIP (lax criteria) or 2 positive responses in any domain (strict criteria). We performed a candidate-gene analysis based on systematic review, followed by a genome-wide association study. We used age at onset, gender, and three significant principle components as covariates.ResultsAfter clinical and genetic quality control steps, we analysed 1602 participants. Prevalence was significantly affected by classification criteria (strict/lax): ICD – 26.8%/11.1%, IRB 29.3%/27.2%, any 31.7%/41.9%. Six SNPs in dopamine, glutamate and adreno- receptor genes achieved nominal significance (p<0.05) in the candidate study. We have identified several SNPs in the GWAS that approach genome wide significance (p<5 × 10–7).ConclusionsThis work is the first genome-wide study of genetic determinants of ICD. Our findings support the hypothesis of genetic determinants of ICD in Parkinson’s and further work will allow understanding of the biology of ICD.

scholarly journals Genetics of fasting and postprandial metabolite levels are overlapping

2018 ◽  
Vol 50 (4) ◽  
pp. 235-236
Author(s):  
Ruifang Li-Gao ◽  
Renée de Mutsert ◽  
Frits R. Rosendaal ◽  
Ko Willems van Dijk ◽  
Dennis O. Mook-Kanamori
Keyword(s):  
Association Study ◽  
Human Body ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genetic Associations ◽  
Mixed Meal ◽  
Genome Wide ◽  
A Genome ◽  
Metabolite Concentrations

In 2015, a genome-wide association study described 59 independent signals that showed strong associations with 85 fasting metabolite concentrations as measured by the Biocrates AbsoluteIDQ p150 kit. However, the human body resides in a nonfasting state for the greater part of the day, and the genetic basis of postprandial metabolite concentrations remains largely unknown. We systematically examined these previously identified genetic associations in postprandial metabolite concentrations after a mixed meal. Of these 85 metabolites, 23 were identified with significant changes after the meal, for which 38 gene-metabolite associations were analyzed. Of these 38 associations, 31 gene-metabolite associations were replicated with postprandial metabolite concentrations. These data indicate that the genetics of fasting and postprandial metabolite levels are significantly overlapping.

scholarly journals Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging

2020 ◽  
Author(s):  
Kaida Ning ◽  
Ben A. Duffy ◽  
Meredith Franklin ◽  
Will Matloff ◽  
Lu Zhao ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Brain Aging ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Imaging Data ◽  
Factors Associated ◽  
Genome Wide ◽  
A Genome ◽  
Validation Tests ◽  
Brain Age

AbstractBrain aging trajectories among those of the same chronological age can vary significantly. Statistical models have been created for estimating the apparent age of the brain, or predicted brain age, with imaging data. Recently, convolutional neural networks (CNNs) have shown the potential to more accurately predict brain age. We trained a CNN on 16,998 UK Biobank subjects, and in validation tests found that it was more accurate than a regression model for predicting brain age. A genome-wide association study was conducted on CNN-derived predicted brain age whereby we identified single nucleotide polymorphisms from four independent loci significantly associated with brain aging. One locus has been previously reported to be associated with brain aging. The three other loci were novel. Our results suggest that a more accurate brain age prediction enables the discovery of novel genetic associations, which may be valuable for identifying other lifestyle factors associated with brain aging.

Genetic variation at the glycosaminoglycan metabolism pathway contributes to the risk of psoriatic arthritis but not psoriasis

2018 ◽  
Vol 78 (3) ◽  
pp. 355-364 ◽  
Author(s):  
Adrià Aterido ◽  
Juan D Cañete ◽  
Jesús Tornero ◽  
Carlos Ferrándiz ◽  
José Antonio Pinto ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Psoriatic Arthritis ◽  
Drug Targets ◽  
Genome Wide Association Study ◽  
New Drugs ◽  
Genetic Associations ◽  
Metabolism Pathway ◽  
A Genome ◽  
Disease Specific ◽  
Pathway Level

ObjectivePsoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting up to 30% of patients with psoriasis (Ps). To date, most of the known risk loci for PsA are shared with Ps, and identifying disease-specific variation has proven very challenging. The objective of the present study was to identify genetic variation specific for PsA.MethodsWe performed a genome-wide association study in a cohort of 835 patients with PsA and 1558 controls from Spain. Genetic association was tested at the single marker level and at the pathway level. Meta-analysis was performed with a case–control cohort of 2847 individuals from North America. To confirm the specificity of the genetic associations with PsA, we tested the associated variation using a purely cutaneous psoriasis cohort (PsC, n=614) and a rheumatoid arthritis cohort (RA, n=1191). Using network and drug-repurposing analyses, we further investigated the potential of the PsA-specific associations to guide the development of new drugs in PsA.ResultsWe identified a new PsA risk single-nucleotide polymorphism at B3GNT2 locus (p=1.10e-08). At the pathway level, we found 14 genetic pathways significantly associated with PsA (pFDR<0.05). From these, the glycosaminoglycan (GAG) metabolism pathway was confirmed to be disease-specific after comparing the PsA cohort with the cohorts of patients with PsC and RA. Finally, we identified candidate drug targets in the GAG metabolism pathway as well as new PsA indications for approved drugs.ConclusionThese findings provide insights into the biological mechanisms that are specific for PsA and could contribute to develop more effective therapies.

scholarly journals A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xiaomin Liu ◽  
Shanmei Tang ◽  
Huanzi Zhong ◽  
Xin Tong ◽  
Zhuye Jie ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Copy Number Variations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Association Analyses ◽  
Genome Wide ◽  
A Genome

AbstractThe gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the Prevotella–Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.

scholarly journals Genome-wide analyses in 1,987,836 participants identify 39 genetic loci associated with sleep apnoea

2020 ◽  
Author(s):  
Adrian I Campos ◽  
Nathan Ingold ◽  
Yunru Huang ◽  
Pik Fang Kho ◽  
Xikun Han ◽  
...  
Keyword(s):  
Complex Traits ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Sleep Apnoea ◽  
Risk Scores ◽  
Genetic Associations ◽  
Genome Wide ◽  
A Genome

Rationale: Sleep apnoea is a complex disorder characterised by periods of halted breathing during sleep. Despite its association with serious health conditions such as cardiovascular disease, the aetiology of sleep apnoea remains understudied, and previous genetic studies have failed to identify replicable genetic risk factors. Objective: To advance our understanding of factors that increase susceptibility to sleep apnoea by identifying novel genetic associations. Methods: We conducted a genome-wide association study (GWAS) meta-analysis of sleep apnoea across five cohorts, and a previously published GWAS of apnoea-hypopnea index (N Total =510,484). Further, we used multi-trait analysis of GWAS (MTAG) to boost statistical power, leveraging the high genetic correlations between apnoea, snoring and body mass index. Replication was performed in an independent sample from 23andMe, Inc (N Total =1,477,352; N cases =175,522). Results: Our results revealed 39 independent genomic loci robustly associated with sleep apnoea risk, and significant genetic correlations with multisite chronic pain, sleep disorders, diabetes, high blood pressure, osteoarthritis, asthma and BMI-related traits. We also derived polygenic risk scores for sleep apnoea in a leave-one-out independent cohort and predicted probable sleep apnoea in participants (OR=1.15 to 1.22; variance explained = 0.4 to 0.9%). Conclusions: We report novel genetic markers robustly associated with sleep apnoea risk and substantial molecular overlap with other complex traits, thus advancing our understanding of the underlying biological mechanisms of susceptibility to sleep apnoea.

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