scholarly journals The genetic relationship between female reproductive traits and six psychiatric disorders

2018 ◽  
Author(s):  
Guiyan Ni ◽  
Azmeraw Amare ◽  
Xuan Zhou ◽  
Natalie Mills ◽  
Jacob Gratten ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Reproductive Traits ◽  
P Value ◽  
Age At First Birth ◽  
Potential Implication ◽  
Positive Effects ◽  
Female Reproductive Traits ◽  
Shared Genetic

ABSTRACTFemale reproductive behaviors have an important implication in evolutionary fitness and health of offspring. Previous studies have shown that age at first birth of women (AFB) is genetically associated with schizophrenia (SCZ). However, for most other psychiatric disorders and reproductive traits, the latent shared genetic architecture is largely unknown. Here we used the second wave of UK Biobank data (N=220,685) to evaluate the association between five female reproductive traits and polygenetic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N=429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with AFB (genetic correlation of −0.68 ± 0.03 with p-value = 1.86E-89), age at first sexual intercourse (AFS) (−0.56 ± 0.03 with p-value = 3.42E-60), number of live births (NLB) (0.36 ± 0.04 with p-value = 4.01E-17) and age at menopause (−0.27 ± 0.04 with p-value = 5.71E-13). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (genetic correlation of 0.35 ± 0.06), ED and AFS (0.19 0.06), Major depressive disorder (MDD) and AFB (−0.27 ± 0.07), MDD and AFS (− 0.27 ± 0.03) and SCZ and AFS (−0.10 ± 0.03). Our findings reveal the shared genetic architecture between the five reproductive traits in women and six psychiatric disorders, which have a potential implication that helps to improve reproductive health in women, hence better child outcomes. Our findings may also explain, at least in part, an evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.

scholarly journals Shared genetic architecture and casual relationship between leptin levels and type 2 diabetes: large-scale cross-trait meta-analysis and Mendelian randomization analysis

2020 ◽  
Vol 8 (1) ◽  
pp. e001140
Author(s):  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Large Scale ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Shared Genetic

ObjectiveWe aimed to estimate genetic correlation, identify shared loci and test causality between leptin levels and type 2 diabetes (T2D).Research design and methodsOur study consists of three parts. First, we calculated the genetic correlation of leptin levels and T2D or glycemic traits by using linkage disequilibrium score regression analysis. Second, we conducted a large-scale genome-wide cross-trait meta-analysis using cross-phenotype association to identify shared loci between trait pairs that showed significant genetic correlations in the first part. In the end, we carried out a bidirectional MR analysis to find out whether there is a causal relationship between leptin levels and T2D or glycemic traits.ResultsWe found positive genetic correlations between leptin levels and T2D (Rg=0.3165, p=0.0227), fasting insulin (FI) (Rg=0.517, p=0.0076), homeostasis model assessment-insulin resistance (HOMA-IR) (Rg=0.4785, p=0.0196), as well as surrogate estimates of β-cell function (HOMA-β) (Rg=0.4456, p=0.0214). We identified 12 shared loci between leptin levels and T2D, 1 locus between leptin levels and FI, 1 locus between leptin levels and HOMA-IR, and 1 locus between leptin levels and HOMA-β. We newly identified eight loci that did not achieve genome-wide significance in trait-specific genome-wide association studies. These shared genes were enriched in pancreas, thyroid gland, skeletal muscle, placenta, liver and cerebral cortex. In addition, we found that 1-SD increase in HOMA-IR was causally associated with a 0.329 ng/mL increase in leptin levels (β=0.329, p=0.001).ConclusionsOur results have shown the shared genetic architecture between leptin levels and T2D and found causality of HOMA-IR on leptin levels, shedding light on the molecular mechanisms underlying the association between leptin levels and T2D.

scholarly journals Hearing difficulty is linked to Alzheimer’s disease by common genetic vulnerability, not shared genetic architecture

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Fatin N. Zainul Abidin ◽  
Helena R. R. Wells ◽  
Andre Altmann ◽  
Sally J. Dawson
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Age Related ◽  
Hearing Difficulty ◽  
Shared Genetic

AbstractAge-related hearing loss was recently established as the largest modifiable risk factor for Alzheimer’s disease (AD), however, the reasons for this link remain unclear. We investigate shared underlying genetic associations using results from recent large genome-wide association studies (GWAS) on adult hearing difficulty and AD. Genetic correlation and Mendelian randomization (MR) analysis do not support a genetic correlation between the disorders, but suggest a direct causal link from AD genetic risk to hearing difficulty, driven by APOE. Systematic MR analyses on the effect of other traits revealed shared effects of glutamine, gamma-glutamylglutamine, and citrate levels on reduced risk of both hearing difficulty and AD. In addition, pathway analysis on GWAS risk variants suggests shared function in neuronal signalling pathways as well as etiology of diabetes and cardiovascular disease. However, after multiple testing corrections, neither analysis led to statistically significant associations. Altogether, our genetic-driven analysis suggests hearing difficulty and AD are linked by a shared vulnerability in molecular pathways rather than by a shared genetic architecture.

scholarly journals Genetic and Causal Relationship Between Coffee Intake and Cardiometabolic Risks: Cross-Phenotype Association And Mendelian Randomization Analysis

2020 ◽  
Author(s):  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang
Keyword(s):  
Genetic Structure ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
P Value ◽  
Coffee Intake ◽  
Randomization Analysis ◽  
Cardiometabolic Traits ◽  
Shared Genetic

Abstract Background: Many epidemiological studies have shown that there is a significant association between coffee intake and cardiometabolic diseases, which may be due to the common genetic structure or causal relationship. Methods: We used linkage disequilibrium score regression analysis to calculate the genetic correlation between coffee intake and 23 cardiometabolic traits (diseases), and then used cross-phenotype association analysis to identify the shared genetic loci for the trait pairs with significant genetic correlation. Besides, a bi-directional Mendelian Randomization analysis was used to explore the causal relationship between coffee intake and 23 cardiometabolic traits (diseases).Results: Coffee intake has a significant genetic correlation (after Bonferroni correction) with body mass index (BMI) (Rg = 0.3713, P-value = 4.13ⅹ10-64), body fat percentage (BF%) (Rg = 0.2810, P-value = 1.81ⅹ10-13), type 2 diabetes (T2D) (unadjusted for BMI) (Rg = 0.1189, P-value = 8.80ⅹ10-6), heart failure (HF) (Rg = 0.2626, P-value = 6.00ⅹ10-9), atrial fibrillation (AF) (Rg = 0.1007, P-value = 4.30ⅹ10-5). There are 203, 18, 86, 13, 38 independent shared loci between coffee intake and BMI, BF%, T2D, HF, AF, respectively, among which 22, 2, 23, 4,13 loci do not achieve genome-wide significance in single trait GWAS. Coffee intake has significant causal effect on BMI (b = 0.0717, P-value = 2.33ⅹ10-5), T2D (unadjusted for BMI, OR = 1.27, P-value = 1.46ⅹ10-7), and intracerebral haemorrhage (ICH) (all types ICH: OR = 1.86, P-value = 3.37ⅹ10-4; deep ICH: OR = 2.12, P-value = 2.93ⅹ10-4 ). And BMI (b = 0.3694, P-value=3.64ⅹ10-154), BF% (b = 0.5500, P-value = 1.68ⅹ10-4), T2D (adjusted for BMI, b = -0.0252, P-value = 4.83ⅹ10-6) and triglycerides (TG) (b = -0.1209, P-value = 4.56ⅹ10-15) have significant causal effect on coffee intake.Conclusions: Our study identified the shared genetic structure and causal relationship between coffee intake and several cardiometabolic traits (diseases), providing a new insight into the mechanism of coffee intake and cardiometabolic traits (diseases).

Genetic Correlation Analysis and Transcriptome-wide Association Study Suggest the Overlapped Genetic Mechanism between Gout and Attention-deficit Hyperactivity Disorder: L’analyse de corrélation génétique et l’étude d’association à l’échelle du transcriptome suggèrent un mécanisme génétique superposé entre la goutte et le trouble de déficit de l’attention avec hyperactivité

2020 ◽  
pp. 070674372097084
Author(s):  
Om Prakash Kafle ◽  
Xi Wang ◽  
Shiqiang Cheng ◽  
Miao Ding ◽  
Ping Li ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Association Study ◽  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Candidate Genes ◽  
Attention Deficit ◽  
Enrichment Analysis ◽  
P Value ◽  
Pathway Enrichment Analysis ◽  
Hyperactivity Disorder

Objectives: Gout is a common inflammatory arthritis, which is caused by hyperuricemia. Limited efforts have been paid to systematically explore the relationships between gout and common psychiatric disorders. Methods: Genome-wide association study summary data of gout were obtained from the GeneATLAS, which contained 452,264 participants including 3,528 gout cases. Linkage disequilibrium score regression (LDSC) was first conducted to evaluate the genetic relationships between gout and 5 common psychiatric disorders. Transcriptome-wide association studies (TWAS) was then conducted to explore the potential biological mechanism underlying the observed genetic correlation between gout and attention-deficit hyperactivity disorder (ADHD). The Database for Annotation, Visualization and Integrated Discovery online functional annotation system was applied for pathway enrichment analysis and gene ontology enrichment analysis. Results: LDSC analysis observed significant genetic correlation between gout and ADHD (genetic correlation coefficients = 0.29, standard error = 0.09 and P value = 0.0015). Further TWAS of gout identified 105 genes with P value < 0.05 in muscle skeleton and 228 genes with P value < 0.05 in blood. TWAS of ADHD also detected 300 genes with P value < 0.05 in blood. Further comparing the TWAS results identified 9 common candidate genes shared by gout and ADHD, such as CD300C ( P gout = 0.0040; P ADHD = 0.0226), KDM6B ( P gout = 0.0074; P ADHD = 0.0460), and BST1 ( P gout = 0.0349; P ADHD = 0.03560). Conclusion: We observed genetic correlation between gout and ADHD and identified multiple candidate genes for gout and ADHD.

scholarly journals Causal effect of C-reactive protein and vitamin D on human cerebral anatomy observed among genetically correlated biomarkers in blood

2021 ◽  
Author(s):  
Dylan James Kiltschewskij ◽  
William R Reay ◽  
Murray J Cairns
Keyword(s):  
Vitamin D ◽  
Psychiatric Disorders ◽  
Cortical Thickness ◽  
Genetic Architecture ◽  
Causal Effect ◽  
Causal Relationships ◽  
C Reactive Protein ◽  
Biochemical Traits ◽  
Reactive Protein ◽  
Shared Genetic

Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex, which frequently vary with clinically relevant factors including antipsychotic treatment, duration of illness and age of onset. While the underlying variables mediating these structural changes are poorly understood, recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in a number of psychiatric disorders which could be mediated by changes in the cerebral cortex. In the current study, we leveraged publicly available genome-wide association study (GWAS) data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area at both the global and regional levels. Linkage disequilibrium score regression identified a total of 20 significant and 156 suggestive genetically correlated biochemical-cortical trait pairings, of which six exhibited strong evidence for causality in a latent causal variable model. Interestingly, a negative causal relationship was identified between a unit increase in serum C-reactive protein levels and thickness of the lingual and lateral occipital regions that was also supported by Mendelian randomisation, while circulating vitamin D (25-hydroxyvitamin D) levels exhibited a positive causal effect on temporal pole thickness. Taken together, our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical thickness in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.

scholarly journals Age at first birth in women is genetically associated with increased risk of schizophrenia

2017 ◽  
Author(s):  
Guiyan Ni ◽  
Jacob Gratten ◽  
Naomi R. Wray ◽  
S. Hong Lee ◽  
Keyword(s):  
Mental Health ◽  
Genetic Correlation ◽  
Genetic Risk ◽  
P Value ◽  
Social Risk ◽  
Age At First Birth ◽  
First Birth ◽  
Older Parents ◽  
Increased Risk ◽  
The Uk

ABSTRACTPrevious studies have shown an increased risk for a range of mental health issues in children born to both younger and older parents compared to children of average-aged parents. However, until recently, it was not clear if these increased risks are due to psychosocial factors associated with age or if parents at higher genetic risk for psychiatric disorders tend to have children at an earlier or later age. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age of mothers at the birth of their first child (AFB). Here, we use independent data from the UK Biobank (N=38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, end to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value=1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value=3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE=0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE=0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.

scholarly journals The genetic relationship between female reproductive traits and six psychiatric disorders

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Guiyan Ni ◽  
Azmeraw T. Amare ◽  
Xuan Zhou ◽  
Natalie Mills ◽  
Jacob Gratten ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Relationship ◽  
Reproductive Traits ◽  
Female Reproductive Traits

scholarly journals Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders and known risk factors

2021 ◽  
Author(s):  
Niamh Mullins ◽  
Jooeun Kang ◽  
Adrian I. Campos ◽  
Jonathan R.I. Coleman ◽  
Alexis C. Edwards ◽  
...  
Keyword(s):  
Risk Factors ◽  
Suicide Attempt ◽  
Psychiatric Disorders ◽  
Genetic Architecture ◽  
Shared Genetic

scholarly journals Genetic correlation and causality of cancers and Parkinson’s disease

2020 ◽  
Author(s):  
Konstantin Senkevich ◽  
Sara Bandres-Ciga ◽  
Eric Yu ◽  
Upekha E. Liyanage ◽  
Alastair J Noyce ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Genetic Architecture ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Shared Genetic

AbstractBackground and objectivesMost cancers appear with reduced frequency in Parkinson’s disease (PD), but the prevalence of melanoma and brain cancers are often reported to be increased. Shared genetic architecture and causal relationships to explain these associations have not been fully explored.MethodsLinkage disequilibrium score regression (LDSC) was applied for five cancer studies with available genome-wide association studies (GWAS) summary statistics to examine genetic correlations with PD. Additionally, we used GWAS summary statistics of 15 different types of cancers as exposures and two-sample Mendelian randomization to study the causal relationship with PD (outcome).ResultsLDSC analysis revealed a potential genetic correlation between PD and melanoma, breast cancer and prostate cancer. There was no evidence to support a causal relationship between the studied cancers and PD.ConclusionsOur results suggest shared genetic architecture between PD and melanoma, breast, and prostate cancers, but no obvious causal relationship between cancers and PD.

scholarly journals The shared genetic architecture between epidemiological and behavioral traits with lung cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rowland W. Pettit ◽  
Jinyoung Byun ◽  
Younghun Han ◽  
Quinn T. Ostrom ◽  
Jacob Edelson ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Fluid Intelligence ◽  
Lung Cancer Risk ◽  
Genetic Correlations ◽  
The Body ◽  
Full Time ◽  
Shared Genetic

AbstractThe complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = − 0.41, h2 = 0.10, p = 1.33 × 10–16), increased fluid intelligence scores (rg = − 0.25, h2 = 0.22, p = 4.54 × 10–8), and the age at which full time education was completed (rg = − 0.45, h2 = 0.11, p = 1.24 × 10–20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10–9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.

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