Genetics of Depression

2017 ◽  
Author(s):  
Douglas F. Levinson ◽  
Walter E. Nichols
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Complex Trait ◽  
Current Evidence ◽  
Genome Wide Association Studies ◽  
Adverse Life Events ◽  
Major Depressive ◽  
Genome Wide ◽  
Increase Risk ◽  
And Function

Major depressive disorder (MDD) is a common and heterogeneous complex trait. Twin heritability is 35%–40%, perhaps higher in severe/recurrent cases. Adverse life events (particularly during childhood) increase risk. Current evidence suggests some overlap in genetic factors among MDD, bipolar disorder, and schizophrenia. Large genome-wide association studies (GWAS) are now proving successful. Polygenic effects of common SNPs are substantial. Findings implicate genes with effects on synaptic development and function, including two obesity-associated genes (NEGR1 and OLFM4), but not previous “candidate genes.” It can now be expected that larger GWAS samples will produce additional associations that shed new light on MDD genetics.

scholarly journals Stratifying depression by neuroticism: revisiting a diagnostic tradition using GWAS data

2019 ◽  
Author(s):  
Mark J. Adams ◽  
David M. Howard ◽  
Michelle Luciano ◽  
Toni-Kim Clarke ◽  
Gail Davies ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Genetic Variance ◽  
Genetic Factors ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Major Depressive ◽  
Genome Wide ◽  
Genetic Contributions

AbstractMajor depressive disorder and neuroticism share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression. We analysed two sets of summary statistics from genome-wide association studies of depression (from the Psychiatric Genomics Consortium and 23andMe) and compared them to GWAS of neuroticism (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only neuroticism, or with both. Second, we estimated partial genetic correlations to test whether the depression’s genetic link with other phenotypes was explained by shared overlap with neuroticism. We found evidence that most genetic variants associated with depression are likely to be shared with neuroticism. The overlapping common genetic variance of depression and neuroticism was negatively genetically correlated with cognitive function and positively genetically correlated with several psychiatric disorders. We found that the genetic contributions unique to depression, and not shared with neuroticism, were correlated with inflammation, cardiovascular disease, and sleep patterns. Our findings demonstrate that, while genetic risk factors for depression are largely shared with neuroticism, there are also non-neuroticism related features of depression that may be useful for further patient or phenotypic stratification.

scholarly journals Genetic Determinants of Paget’s Disease of Bone

2021 ◽  
Author(s):  
Navnit S. Makaram ◽  
Stuart H. Ralston
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Paget’S Disease ◽  
Paget's Disease ◽  
Paget’S Disease Of Bone ◽  
Genome Wide Association Studies ◽  
Paget's Disease Of Bone ◽  
Genome Wide ◽  
Family Based

Abstract Purpose of Review To provide an overview of the role of genes and loci that predispose to Paget’s disease of bone and related disorders. Recent Findings Studies over the past ten years have seen major advances in knowledge on the role of genetic factors in Paget’s disease of bone (PDB). Genome wide association studies have identified six loci that predispose to the disease whereas family based studies have identified a further eight genes that cause PDB. This brings the total number of genes and loci implicated in PDB to fourteen. Emerging evidence has shown that a number of these genes also predispose to multisystem proteinopathy syndromes where PDB is accompanied by neurodegeneration and myopathy due to the accumulation of abnormal protein aggregates, emphasising the importance of defects in autophagy in the pathogenesis of PDB. Summary Genetic factors play a key role in the pathogenesis of PDB and the studies in this area have identified several genes previously not suspected to play a role in bone metabolism. Genetic testing coupled to targeted therapeutic intervention is being explored as a way of halting disease progression and improving outcome before irreversible skeletal damage has occurred.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

scholarly journals A description of large-scale metabolomics studies: increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling

2012 ◽  
Vol 215 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Georg Homuth ◽  
Alexander Teumer ◽  
Uwe Völker ◽  
Matthias Nauck
Keyword(s):  
Blood Cells ◽  
Large Scale ◽  
Genetic Factors ◽  
Association Studies ◽  
Transcriptional Profiling ◽  
Genome Wide Association Studies ◽  
Protein Levels ◽  
Future Developments ◽  
Genome Wide ◽  
Metabolome Data

The metabolome, defined as the reflection of metabolic dynamics derived from parameters measured primarily in easily accessible body fluids such as serum, plasma, and urine, can be considered as the omics data pool that is closest to the phenotype because it integrates genetic influences as well as nongenetic factors. Metabolic traits can be related to genetic polymorphisms in genome-wide association studies, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures primarily caused by nongenetic factors. Similarly, correlation of metabolome data with transcriptional or/and proteome profiles of blood cells also produces valuable data, by revealing associations between metabolic changes and mRNA and protein levels. In the last years, the progress in correlating genetic variation and metabolome profiles was most impressive. This review will therefore try to summarize the most important of these studies and give an outlook on future developments.

scholarly journals Germline Genetic Factors Influence Outcome of Interferon Alpha Therapy in Polycythemia Vera

Blood ◽  
2020 ◽  
Author(s):  
Roland Jäger ◽  
Heinz Gisslinger ◽  
Elisabeth Fuchs ◽  
Edith Bogner ◽  
Jelena D. Milosevic Feenstra ◽  
...  
Keyword(s):  
Polycythemia Vera ◽  
Interferon Alpha ◽  
Genetic Factors ◽  
Myeloproliferative Neoplasms ◽  
Association Studies ◽  
Study Cohort ◽  
Molecular Response ◽  
Genome Wide Association Studies ◽  
Association Analyses ◽  
Genome Wide

Interferon alpha (IFNα) based therapies can induce hematologic and molecular responses in polycythemia vera (PV); however, patients do not respond equally. Germline genetic factors have previously been implicated in differential drug response. We addressed the effect of common germline polymorphisms on hematologic and molecular response (HR/MR) in PV therapy within the PROUD-PV and CONTINUATION-PV studies including 122 patients with PV receiving ropeginterferon alfa-2b. Genome-wide association studies using longitudinal data on HR and MR over 36 months follow-up did not reveal any associations at genome-wide significance. Further, we performed targeted association analyses at the interferon lambda 4 (IFNL4) locus, well known for its role in hepatitis C viral clearance and recently reported to influence HR during therapy of myeloproliferative neoplasms. While we did not observe any association of IFNL4 polymorphisms with HR in our study cohort, we demonstrated a statistically significant effect of the functionally causative IFNL4 diplotype (haplotype pair including the protein-coding variants rs368234815/rs117648444) on MR (p=3.91x10-4; OR=10.80; 95%CI:[2.39-69.97]) as reflected in differential JAK2V617F mutational burden changes according to IFNL4 diplotype status. Stratification of PV patients based on IFNL4 functionality may allow for optimizing patient management during IFNα treatment.

Pathophysiology and genetic factors in moyamoya disease

2009 ◽  
Vol 26 (4) ◽  
pp. E4 ◽  
Author(s):  
Achal S. Achrol ◽  
Raphael Guzman ◽  
Marco Lee ◽  
Gary K. Steinberg
Keyword(s):  
Moyamoya Disease ◽  
Genetic Factors ◽  
Association Studies ◽  
Vascular Anomalies ◽  
Future Research ◽  
Incomplete Penetrance ◽  
Genome Wide Association Studies ◽  
Research Directions ◽  
Genome Wide ◽  
Future Research Directions

Moyamoya disease is an uncommon cerebrovascular condition characterized by progressive stenosis of the bilateral internal carotid arteries with compensatory formation of an abnormal network of perforating blood vessels providing collateral circulation. The etiology and pathogenesis of moyamoya disease remain unclear. Evidence from histological studies, proteomics, and endothelial progenitor cell analyses suggests new theories underlying the cause of vascular anomalies, including moyamoya disease. Familial moyamoya disease has been noted in as many as 15% of patients, indicating an autosomal dominant inheritance pattern with incomplete penetrance. Genetic analyses in familial moyamoya disease and genome-wide association studies represent promising strategies for elucidating the pathophysiology of this condition. In this review, the authors discuss recent studies that have investigated possible mechanisms underlying the etiology of moyamoya disease, including stem cell involvement and genetic factors. They also discuss future research directions that promise not only to offer new insights into the origin of moyamoya disease but to enhance our understanding of new vessel formation in the CNS as it relates to stroke, vascular anomalies, and tumor growth.

scholarly journals Genetics of hypertension: discoveries from the bench to human populations

2014 ◽  
Vol 306 (1) ◽  
pp. F1-F11 ◽  
Author(s):  
Nora Franceschini ◽  
Thu H. Le
Keyword(s):  
Association Studies ◽  
Complex Trait ◽  
Experimental Models ◽  
Sodium Reabsorption ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Blood Pressure Homeostasis ◽  
Genome Wide ◽  
Clinical Hypertension ◽  
Renal Sodium Reabsorption

Hypertension is a complex trait that is influenced by both heritable and environmental factors. The search for genes accounting for the susceptibility to hypertension has driven parallel efforts in human research and in research using experimental animals in controlled environmental settings. Evidence from rodent models of genetic hypertension and human Mendelian forms of hypertension and hypotension have yielded mechanistic insights into the pathways that are perturbed in blood pressure homeostasis, most of which converge at the level of renal sodium reabsorption. However, the bridging of evidence from these very diverse approaches to identify mechanisms underlying hypertension susceptibility and the translation of these findings to human populations and public health remain a challenge. Furthermore, findings from genome-wide association studies still require functional validation in experimental models. In this review, we highlight results and implications from key studies in experimental and clinical hypertension to date.

scholarly journals Bench Research Informed by GWAS Results

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3184
Author(s):  
Nikolay V. Kondratyev ◽  
Margarita V. Alfimova ◽  
Arkadiy K. Golov ◽  
Vera E. Golimbet
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Reverse Genetics ◽  
Genetic Factors ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually ‘highly polygenic’. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise ‘wet biologists’ with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Sign in / Sign up

Export Citation Format

Share Document