genetic correlation
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2022 ◽  
Author(s):  
Zhen Zhang ◽  
Li Liu ◽  
Huijie Zhang ◽  
Chun'e Li ◽  
Yujing Chen ◽  
...  

Abstract Background Pain symptoms are common in the patients with depression. Comparing with the general population, the pain in depression patients has more complex biological mechanism. We aim to explore the etiological mechanism of pain in depression patients from the perspective of genetics. Methods Utilizing the UK Biobank samples with self-reported depression status or PHQ score ≥10, we conducted genome-wide association study (GWAS) of seven pain traits (N=1,133-58,349). The GWAS summary were then integrated with two different reference protein weights (ROS/MAP and Banner) for proteome-wide association study (PWAS) using the FUSION pipeline. Additionally, LDSC analysis was performed to explore the genetic correlation between pain traits in depression patients and common psychiatry disorders. And biological processes and functions that related to pain associated genes in depression patients were analyzed by gene set enrichment analysis. Results GWAS identified 3 significant genes associated with different pain traits in depression patients, including TRIOBP (PGWAS= 4.48× 10−8) for stomach or abdominal pain, SLC9A9(PGWAS= 2.77× 10−8) for multisite chronic pain (MCP) and ADGRF1 (PGWAS= 1.51× 10−8) for neck or shoulder pain. PWAS also identified multiple candidate genes associated with different pain traits in depression patients, such as TPRG1L (permutation-based PPWAS−Banner= 3.38× 10−2) and SIRPA (permutation-based PPWAS−Banner= 3.65×10−2) for MCP etc. LDSC analysis results showed that MCP was positively correlated with attention-deficit hyperactivity disorder (ADHD) (genetic correlation(rg) = 0.123, PLDSC = 0.039) and post-traumatic stress disorder (PTSD) (rg = 0.217, PLDSC = 0.029). Conclusions We reported multiple novel candidate genes and genetic correlations for pain traits in depression patients, providing novel clues for understanding the genetic mechanisms underlying the pain in depression patients.


2022 ◽  
Vol 11 (1) ◽  
pp. 12-22
Author(s):  
Fuquan Zhang ◽  
Shuquan Rao ◽  
Ancha Baranova

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.


Author(s):  
Chunyu Li ◽  
Tianmi Yang ◽  
Ruwei Ou ◽  
Huifang Shang

Epidemiological and clinical studies have suggested comorbidity between schizophrenia and several neurodegenerative disorders. However, little is known whether there exists shared genetic architecture. To explore their relationship from a genetic and transcriptomic perspective, we applied polygenic and linkage disequilibrium-informed methods to examine the genetic correlation between schizophrenia and amyotrophic lateral sclerosis (ALS), Parkinson’s disease, Alzheimer’s disease and frontotemporal dementia. We further combined genome-wide association summary statistics with large-scale transcriptomic datasets, to identify putative shared genes and explore related pathological tissues. We identified positive and significant correlation between schizophrenia and ALS at genetic (correlation 0.22; 95% CI: 0.16–0.28; p = 4.00E-04) and transcriptomic (correlation 0.08; 95% CI: 0.04–0.11; p = 0.034) levels. We further demonstrated that schizophrenia- and ALS-inferred gene expression overlap significantly in four tissues including skin, small intestine, brain cortex and lung, and highlighted three genes, namely GLB1L3, ZNHIT3 and TMEM194A as potential mediators of the correlation between schizophrenia and ALS. Our findings revealed overlapped gene expression profiles in specific tissues between schizophrenia and ALS, and identified novel potential shared genes. These results provided a better understanding for the pleiotropy of schizophrenia, and paved way for future studies to further elucidate the molecular drivers of schizophrenia.


2021 ◽  
Author(s):  
Alexander Glaser ◽  
Zhuqing Shi ◽  
Jun Wei ◽  
Nadia A. Lanman ◽  
Skylar Ladson-Gary ◽  
...  

AbstractBackgroundThe association between benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remains controversial, largely due to inherent detection bias in traditional observational studies. The objective of this study is to assess their association using inherited SNPs.MethodsSubjects were White men from the large population-based UK Biobank (UKB). Association between BPH and PCa was tested: 1) phenotypical correlation using chi-square test, 2) genetic correlation (rg) based on 1,126,841 polymorphic SNPs across the genome using linkage disequilibrium score regression (LDSR), and 3) cross-disease genetic associations based on known risk-associated SNPs (15 for BPH and 239 for PCa), individually and cumulatively as measured by genetic risk score (GRS).FindingsAmong 214,717 White men in the UKB, 24,623 (11.47%) and 14,311 (6.67%) had a diagnosis of BPH and PCa, respectively. Diagnoses of these two diseases were significantly correlated, χ2=1862.80, P<1E-299. A significant genetic correlation was found, rg (95% confidence interval (CI))=0.27 (0.15-0.39), P=9.17E-06. In addition, significant cross-disease genetic associations for established risk-associated SNPs were also found. Among the 250 established GWAS-significant SNPs of PCa or BPH, 51 were significantly associated with risk of the other disease at P<0.05, significantly more than expected by chance (N=12), P=3.04E-7 (χ2-test). Furthermore, significant cross-disease GRS associations were also found; GRSBPH was significantly associated with PCa risk (odds ratio (OR)=1.26 (1.18-1.36), P=1.62E-10), and GRSPCa was significantly associated with BPH risk (OR=1.03 (1.02-1.04), P=8.57E-06). Moreover, GRSBPH was significantly and inversely associated with lethal PCa risk in a PCa case-case analysis (OR=0.58 (0.41-0.81), P=1.57E-03). In contrast, GRSPCa was not significantly associated with lethal PCa (OR=0.99 (0.94-1.04), P=0.79).InterpretationBPH and PCa share common inherited genetics which suggests the phenotypical association of these two diseases in observational studies is not entirely caused by detection bias. This novel finding may have implications in disease etiology and risk stratification.FundingNone.


2021 ◽  
Vol 15 ◽  
Author(s):  
Haimiao Chen ◽  
Jiahao Qiao ◽  
Ting Wang ◽  
Zhonghe Shao ◽  
Shuiping Huang ◽  
...  

Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs.Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer’s Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways.Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as “urea cycle” (P = 0.036), “arginine biosynthesis” (P = 0.004) on AD and “phenylalanine, tyrosine and tryptophan biosynthesis” (P = 0.046) on ALS.Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases.


2021 ◽  
pp. 1-11
Author(s):  
Joeri J. Meijsen ◽  
Hanyang Shen ◽  
Mytilee Vemuri ◽  
Natalie L. Rasgon ◽  
Karestan C. Koenen ◽  
...  

Abstract Background Women experience major depression and post-traumatic stress disorder (PTSD) approximately twice as often as men. Estrogen is thought to contribute to sex differences in these disorders, and reduced estrogen is also known to be a key driver of menopause symptoms such as hot flashes. Moreover, estrogen is used to treat menopause symptoms. In order to test for potential shared genetic influences between menopause symptoms and psychiatric disorders, we conducted a genome-wide association study (GWAS) of estrogen medication use (as a proxy for menopause symptoms) in the UK Biobank. Methods The analysis included 232 993 women aged 39–71 in the UK Biobank. The outcome variable for genetic analyses was estrogen medication use, excluding women using hormonal contraceptives. Trans-ancestry GWAS meta-analyses were conducted along with genetic correlation analyses on the European ancestry GWAS results. Hormone usage was also tested for association with depression and PTSD. Results GWAS of estrogen medication use (compared to non-use) identified a locus in the TACR3 gene, which was previously linked to hot flashes in menopause [top rs77322567, odds ratio (OR) = 0.78, p = 7.7 × 10−15]. Genetic correlation analyses revealed shared genetic influences on menopause symptoms and depression (rg = 0.231, s.e.= 0.055, p = 2.8 × 10−5). Non-genetic analyses revealed higher psychiatric symptoms scores among women using estrogen medications. Conclusions These results suggest that menopause symptoms have a complex genetic etiology which is partially shared with genetic influences on depression. Moreover, the TACR3 gene identified here has direct clinical relevance; antagonists for the neurokinin 3 receptor (coded for by TACR3) are effective treatments for hot flashes.


2021 ◽  
Vol 12 ◽  
Author(s):  
Ellen Lai ◽  
Alexa L. Danner ◽  
Thomas R. Famula ◽  
Anita M. Oberbauer

Lameness is an animal welfare issue that incurs substantial financial and environmental costs. This condition is commonly caused by digital dermatitis (DD), sole ulcers (SU), and white line disease (WLD). Susceptibility to these three foot disorders is due in part to genetics, indicating that genomic selection against these foot lesions can be used to reduce lameness prevalence. It is unclear whether selection against foot lesions will lead to increased susceptibility to other common diseases such as mastitis and metritis. Thus, the aim of this study was to determine the genetic correlation between causes of lameness and other common health disorders to identify loci contributing to the correlation. Genetic correlation estimates between SU and DD and between SU and WLD were significantly different from zero (p &lt; 0.05), whereas estimates between DD and mastitis, DD and milk fever, and SU and metritis were suggestive (p &lt; 0.1). All five of these genetic correlation estimates were positive. Two-trait genome-wide association studies (GWAS) for each of these five pairs of traits revealed common regions of association on BTA1 and BTA8 for pairs that included DD or SU as one of the traits, respectively. Other regions of association were unique to the pair of traits and not observed in GWAS for other pairs of traits. The positive genetic correlation estimates between foot disorders and other health disorders imply that selection against foot disorders may also decrease susceptibility to other health disorders. Linkage disequilibrium blocks defined around significant and suggestive SNPs from the two-trait GWAS included genes and QTL that were functionally relevant, supporting that these regions included pleiotropic loci.


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