scholarly journals Shared Genetic Factors Underlie Migraine and Depression

2016 ◽  
Vol 19 (4) ◽  
pp. 341-350 ◽  
Author(s):  
Yuanhao Yang ◽  
Huiying Zhao ◽  
Andrew C. Heath ◽  
Pamela A. F. Madden ◽  
Nicholas G. Martin ◽  
...  
Keyword(s):  
Depressive Disorder ◽  
Genetic Correlation ◽  
Genetic Factors ◽  
International Headache Society ◽  
Diagnostic Measures ◽  
Diagnostic And Statistical Manual ◽  
Twin Models ◽  
Id Migraine ◽  
Genetically Determined ◽  
Shared Genetic

Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterize the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine™ screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine, or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53–60%) and 42% (95% CI: 37–46%), respectively. A significant additive genetic correlation (rG = 0.36, 95% CI: 0.29–0.43) and bivariate heritability (h2 = 5.5%, 95% CI: 3.6–7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h2 (13.3%, 95% CI: 7.0–24.5%) and rG (0.51, 95% CI: 0.37–0.69) estimates significantly increased when analyzing the more narrow clinically accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms.

scholarly journals Familial Aggregation of Migraine and Depression: Insights From a Large Australian Twin Sample

2016 ◽  
Vol 19 (4) ◽  
pp. 312-321 ◽  
Author(s):  
Yuanhao Yang ◽  
Huiying Zhao ◽  
Andrew C. Heath ◽  
Pamela A. F. Madden ◽  
Nicholas G. Martin ◽  
...  
Keyword(s):  
Depressive Disorder ◽  
Familial Aggregation ◽  
International Headache Society ◽  
Self Report ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Relative Risks ◽  
Increased Risk ◽  
Ihs Criteria ◽  
Id Migraine

Objectives: This research examined the familial aggregation of migraine, depression, and their co-occurrence.Methods: Diagnoses of migraine and depression were determined in a sample of 5,319 Australian twins. Migraine was diagnosed by either self-report, the ID migraine™ Screener, or International Headache Society (IHS) criteria. Depression was defined by fulfilling either major depressive disorder (MDD) or minor depressive disorder (MiDD) based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. The relative risks (RR) for migraine and depression were estimated in co-twins of twin probands reporting migraine or depression to evaluate their familial aggregation and co-occurrence.Results: An increased RR of both migraine and depression in co-twins of probands with the same trait was observed, with significantly higher estimates within monozygotic (MZ) twin pairs compared to dizygotic (DZ) twin pairs. For cross-trait analysis, the RR for migraine in co-twins of probands reporting depression was 1.36 (95% CI: 1.24–1.48) in MZ pairs and 1.04 (95% CI: 0.95–1.14) in DZ pairs; and the RR for depression in co-twins of probands reporting migraine was 1.26 (95% CI: 1.14–1.38) in MZ pairs and 1.02 (95% CI: 0.94–1.11) in DZ pairs. The RR for strict IHS migraine in co-twins of probands reporting MDD was 2.23 (95% CI: 1.81–2.75) in MZ pairs and 1.55 (95% CI: 1.34–1.79) in DZ pairs; and the RR for MDD in co-twins of probands reporting IHS migraine was 1.35 (95% CI: 1.13–1.62) in MZ pairs and 1.06 (95% CI: 0.93–1.22) in DZ pairs.Conclusions: We observed significant evidence for a genetic contribution to familial aggregation of migraine and depression. Our findings suggest a bi-directional association between migraine and depression, with an increased risk for depression in relatives of probands reporting migraine, and vice versa. However, the observed risk for migraine in relatives of probands reporting depression was considerably higher than the reverse. These results add further support to previous studies suggesting that patients with comorbid migraine and depression are genetically more similar to patients with only depression than patients with only migraine.

scholarly journals Investigating the source of increased bipolar and major depressive disorder polygenic risk in multiplex schizophrenia families

2021 ◽  
Author(s):  
Mohammad Ahangari ◽  
Robert Kirkpatrick ◽  
Tan-Hoang Nguyen ◽  
Nathan Gillespie ◽  
Irish Schizophrenia Genomics Consortium ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Affective Disorders ◽  
Genetic Factors ◽  
Genetic Correlations ◽  
Polygenic Risk Score ◽  
Major Depressive ◽  
Polygenic Risk

Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia (SCZ), and genetic studies show substantial genetic correlation among SCZ, bipolar disorder (BIP) and major depressive disorder (MDD). However, the nature of this genetic overlap in polygenic risk score (PRS) analyses of multiplex families has not been fully dissected. In the current study, we investigated the polygenic risk burden of BIP and MDD in a sample of 257 multiplex SCZ families (N=1,005) and population controls (N=2,205). Furthermore, due to the strong genetic correlation among SCZ, BIP, and MDD, we examined whether increased BIP or MDD PRS in members of multiplex SCZ families can be attributed to latent genetic factors unique to BIP or MDD, or latent genetic factors that each of these two disorders share with SCZ. Our results indicate that members of multiplex SCZ families have an increased PRS for BIP and MDD, however, this observation is largely attributable to latent genetic factors that BIP or MDD share with SCZ, rather than latent genetic factors unique to them. These results provide new insight for cross-disorder PRS analyses of psychiatric disorders, by cautioning that for complete interpretation of observed cross-disorder PRS enrichment, we should account for genetic correlations across psychiatric disorders. Our findings further indicates that members of multiplex SCZ families may have an increased genetic vulnerability to both psychotic and affective disorders, and for full assessment of an individual genetic risk, familial backgrounds should be taken into consideration.

scholarly journals Interhemispheric Relationship of Genetic Influence on Human Brain Connectivity

2020 ◽  
Vol 31 (1) ◽  
pp. 77-88
Author(s):  
Suyu Zhong ◽  
Long Wei ◽  
Chenxi Zhao ◽  
Liyuan Yang ◽  
Zengru Di ◽  
...  
Keyword(s):  
Human Brain ◽  
Genetic Correlation ◽  
Genetic Factors ◽  
Brain Connectivity ◽  
Genetic Correlations ◽  
Disease States ◽  
Left And Right ◽  
Genetically Determined ◽  
Relationship Of ◽  
Insight Into

Abstract To understand the origins of interhemispheric differences and commonalities/coupling in human brain wiring, it is crucial to determine how homologous interregional connectivities of the left and right hemispheres are genetically determined and related. To address this, in the present study, we analyzed human twin and pedigree samples with high-quality diffusion magnetic resonance imaging tractography and estimated the heritability and genetic correlation of homologous left and right white matter (WM) connections. The results showed that the heritability of WM connectivity was similar and coupled between the 2 hemispheres and that the degree of overlap in genetic factors underlying homologous WM connectivity (i.e., interhemispheric genetic correlation) varied substantially across the human brain: from complete overlap to complete nonoverlap. Particularly, the heritability was significantly stronger and the chance of interhemispheric complete overlap in genetic factors was higher in subcortical WM connections than in cortical WM connections. In addition, the heritability and interhemispheric genetic correlations were stronger for long-range connections than for short-range connections. These findings highlight the determinants of the genetics underlying WM connectivity and its interhemispheric relationships, and provide insight into genetic basis of WM connectivity asymmetries in both healthy and disease states.

scholarly journals Shared genetic liability between major depressive disorder and osteoarthritis

2022 ◽  
Vol 11 (1) ◽  
pp. 12-22
Author(s):  
Fuquan Zhang ◽  
Shuquan Rao ◽  
Ancha Baranova
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Fine Mapping ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Major Depressive ◽  
Genetic Liability ◽  
Randomization Analysis ◽  
Shared Genetic

Aims Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations. Methods Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases. Results MDD has a significant genetic correlation with OA (rg = 0.29) and the two diseases share a considerable proportion of causal variants. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on OA (bxy = 0.24) and genetic liability to OA conferred a causal effect on MDD (bxy = 0.20). Cross-trait meta-analyses identified 29 shared genomic loci between MDD and OA. Together with fine-mapping of transcriptome-wide association signals, our results suggest that Estrogen Receptor 1 ( ESR1), SRY-Box Transcription Factor 5 ( SOX5), and Glutathione Peroxidase 1 ( GPX1) may have therapeutic implications for both MDD and OA. Conclusion The study reveals substantial shared genetic liability between MDD and OA, which may confer risk for one another. Our findings provide a novel insight into phenotypic relationships between MDD and OA. Cite this article: Bone Joint Res 2022;11(1):12–22.

scholarly journals Pleiotropic effects drive correlation between body mass index and cortical myelination

2018 ◽  
Author(s):  
Lisa Ronan ◽  
Nenad Medic ◽  
Paul C Fletcher
Keyword(s):  
Body Mass Index ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Body Mass ◽  
Genetic Factors ◽  
Monozygotic Twins ◽  
Pleiotropic Effects ◽  
Phenotypic Correlation ◽  
Neurocognitive Decline ◽  
Shared Genetic

AbstractBackgroundEpidemiological studies have reported significant associations between obesity and neurocognitive decline. Understanding these associations will require deeper analyses of how body mass index (BMI) and brain structure are related. Here we explore the extent to which shared genetic factors (pleiotropy) govern the association between BMI and cortical myelination.MethodsStatistical models of bivariate heritability were applied to structural MR image data from a cohort of monozyogotic and dizygotic twins. Estimates of phenotypic and genetic correlation between BMI and cortical myelination were derived. A co-twin control design based on monozygotic twins was used to test the hypothesis of a causal relationship between BMI and myelination. The variation in the genetic correlation across the cortex was compared with the average statistical enrichment of genes associated with obesity derived from data from the Allen brain atlas.ResultsStatistically significant phenotypic and genetic correlation between BMI and cortical myelination was observed across the cortex. Taking the heritability of each trait into account, approximately 80% of the phenotypic correlation between the traits was accounted for by shared genetic factors.Intra-pair differences between traits in monozygotic twins failed to support a causal relationship. Moreover, variation in genetic correlation across the cortex was significantly associated with the statistical enrichment of genes related to obesity.ConclusionsThese results support the hypothesis that pleiotropic effects drive the association between BMI and cortical myelination. This observation may help to explain the co-occurrence of obesity in neurocognitive decline and mental health disorders characterized by changes in myelination and oligodendrocyte function.

scholarly journals Unravelling Genetic Factors Underlying Corticobasal Syndrome: A Systematic Review

Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 171
Author(s):  
Federica Arienti ◽  
Giulia Lazzeri ◽  
Maria Vizziello ◽  
Edoardo Monfrini ◽  
Nereo Bresolin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Diagnostic Algorithm ◽  
Behavioral Changes ◽  
Corticobasal Syndrome ◽  
Cochrane Library ◽  
Radiological Features ◽  
Genetically Determined

Corticobasal syndrome (CBS) is an atypical parkinsonian presentation characterized by heterogeneous clinical features and different underlying neuropathology. Most CBS cases are sporadic; nevertheless, reports of families and isolated individuals with genetically determined CBS have been reported. In this systematic review, we analyze the demographical, clinical, radiological, and anatomopathological features of genetically confirmed cases of CBS. A systematic search was performed using the PubMed, EMBASE, and Cochrane Library databases, included all publications in English from 1 January 1999 through 1 August 2020. We found forty publications with fifty-eight eligible cases. A second search for publications dealing with genetic risk factors for CBS led to the review of eight additional articles. GRN was the most common gene involved in CBS, representing 28 out of 58 cases, followed by MAPT, C9ORF72, and PRNP. A set of symptoms was shown to be significantly more common in GRN-CBS patients, including visuospatial impairment, behavioral changes, aphasia, and language alterations. In addition, specific demographical, clinical, biochemical, and radiological features may suggest mutations in other genes. We suggest a diagnostic algorithm to help in identifying potential genetic cases of CBS in order to improve the diagnostic accuracy and to better understand the still poorly defined underlying pathogenetic process.

scholarly journals Investigating regions of shared genetic variation in attention deficit/hyperactivity disorder and major depressive disorder: a GWAS meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Victoria Powell ◽  
Joanna Martin ◽  
Anita Thapar ◽  
Frances Rice ◽  
Richard J. L. Anney
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Attention Deficit ◽  
Meta Analysis ◽  
Major Depressive ◽  
Hyperactivity Disorder ◽  
High Level ◽  
Genomic Regions

AbstractAttention deficit/hyperactivity disorder (ADHD) demonstrates a high level of comorbidity with major depressive disorder (MDD). One possible contributor to this is that the two disorders show high genetic correlation. However, the specific regions of the genome that may be responsible for this overlap are unclear. To identify variants associated with both ADHD and MDD, we performed a meta-analysis of GWAS of ADHD and MDD. All genome wide significant (p < 5 × 10–8) SNPs in the meta-analysis that were also strongly associated (p < 5 × 10–4) independently with each disorder were followed up. These putatively pleiotropic SNPs were tested for additional associations across a broad range of phenotypes. Fourteen linkage disequilibrium-independent SNPs were associated with each disorder separately (p < 5 × 10–4) and in the cross-disorder meta-analysis (p < 5 × 10–8). Nine of these SNPs had not been highlighted previously in either individual GWAS. Evidence supported nine of the fourteen SNPs acting as eQTL and two as brain eQTL. Index SNPs and their genomic regions demonstrated associations with other mental health phenotypes. Through conducting meta-analysis on ADHD and MDD only, our results build upon the previously observed genetic correlation between ADHD and MDD and reveal novel genomic regions that may be implicated in this overlap.

scholarly journals Genome-wide genetic links between amyotrophic lateral sclerosis and autoimmune diseases

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chun Yu Li ◽  
Tian Mi Yang ◽  
Ru Wei Ou ◽  
Qian Qian Wei ◽  
Hui Fang Shang
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Autoimmune Diseases ◽  
Genetic Correlation ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide ◽  
Shared Risk ◽  
Lateral Sclerosis ◽  
Shared Genetic

Abstract Background Epidemiological and clinical studies have suggested comorbidity between amyotrophic lateral sclerosis (ALS) and autoimmune disorders. However, little is known about their shared genetic architecture. Methods To examine the relation between ALS and 10 autoimmune diseases, including asthma, celiac disease (CeD), Crohn’s disease (CD), inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), and ulcerative colitis (UC), and identify shared risk loci, we first estimated the genetic correlation using summary statistics from genome-wide association studies, and then analyzed the genetic enrichment leveraging the conditional false discovery rate statistical method. Results We identified a significant positive genetic correlation between ALS and CeD, MS, RA, and SLE, as well as a significant negative genetic correlation between ALS and IBD, UC, and CD. Robust genetic enrichment was observed between ALS and CeD and MS, and moderate enrichment was found between ALS and UC and T1D. Thirteen shared genetic loci were identified, among which five were suggestively significant in another ALS GWAS, namely rs3828599 (GPX3), rs3849943 (C9orf72), rs7154847 (G2E3), rs6571361 (SCFD1), and rs9903355 (GGNBP2). By integrating cis-expression quantitative trait loci analyses in Braineac and GTEx, we further identified GGNBP2, ATXN3, and SLC9A8 as novel ALS risk genes. Functional enrichment analysis indicated that the shared risk genes were involved in four pathways including membrane trafficking, vesicle-mediated transport, ER to Golgi anterograde transport, and transport to the Golgi and subsequent modification. Conclusions Our findings demonstrate a specific genetic correlation between ALS and autoimmune diseases and identify shared risk loci, including three novel ALS risk genes. These results provide a better understanding for the pleiotropy of ALS and have implications for future therapeutic trials.

Identification of Potential Pleiotropic Genes for Immune and Skeletal Diseases Using Multivariate MetaCCA Analysis

2021 ◽  
Vol 23 ◽  
Author(s):  
Pei He ◽  
Rong- Rong Cao ◽  
Fei- Yan Deng ◽  
Shu- Feng Lei
Keyword(s):  
Association Study ◽  
Canonical Correlation ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Summary Statistics ◽  
Immune Disease ◽  
Histocompatibility Complex ◽  
Genome Wide ◽  
Genetic Mechanisms ◽  
Shared Genetic

Background: Immune and skeletal systems physiologically and pathologically interact with each other. The immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia and fracture) Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. Versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA. Results: About 157 (p<8.19E-6), 319 (p<3.90E-6) and 77 (p<9.72E-6) potential pleiotropic genes were identified shared by two immune disease, four skeletal diseases, and all of the six diseases, respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal diseases, including HLA-B, TSBP1 and TSBP1-AS1 (p<E-300) were located in the major histocompatibility complex (MHC) region. Nineteen of 77 putative pleiotropic genes identified by metaCCA analysis were associated with at least one disease in the VEGAS2 analysis. Specifically, majority (18) of these 19 putative validated pleiotropic genes were associated with RA. Conclusion: The metaCCA method identified some pleiotropic genes shared by the immune and skeletal diseases. These findings help to improve our understanding of the shared genetic mechanisms and signaling pathways underlying immune and skeletal diseases.

Depressive Disorders: Update on Diagnosis, Etiology, and Treatment

2018 ◽  
Author(s):  
Isabelle E. Bauer ◽  
Antonio L Teixeira ◽  
Marsal Sanches ◽  
Jair C. Soares
Keyword(s):  
Depressive Disorder ◽  
Depressive Disorders ◽  
Treatment Strategies ◽  
Premenstrual Dysphoric Disorder ◽  
Brain Volumes ◽  
Somatic Therapy ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
History Of ◽  
Persistent Depressive Disorder

This review discusses the changes in the diagnostic criteria for depressive disorders as outlined in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), and recent findings exploring the etiology of and treatment strategies for these disorders. Depressive disorders are typically characterized by depression in the absence of a lifetime history of mania or hypomania. New developments in the DSM-5 include the recognition of new types of depressive disorders, such as disruptive mood dysregulation disorder, persistent depressive disorder, premenstrual dysphoric disorder, and the addition of catatonic features as a specifier for persistent depressive disorder. These diagnostic changes have important implications for the prognosis and treatment of this condition. A thorough understanding of both the clinical phenotype and the biosignature of these conditions is essential to provide individualized, long-term, effective treatments to affected individuals.  This review contains 1 table and 52 references Key words: brain volumes, depressive disorders, DSM-5, hormones, inflammation, neuropeptides, somatic therapy, stress

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