Genetic correlations between COVID-19 and a variety of traits and diseases.
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ABSTRACT:
SUBMITTER: Chang X
PROVIDER: S-EPMC8081576 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.
| S-EPMC4797329 | biostudies-literature
Project description:Objective:The aim of the study was to comprehensively explore the genetic susceptibility correlations among diseases and traits from large-scale individual genotype data. Materials and Methods:Based on a knowledge base of genetic variants significantly (P?<?5?×?10 -8 ) linked with human phenotypes, genetic risk scores (GRSs) of diseases or traits were calculated for 2504 individuals with whole-genome sequencing data from the 1000 Genomes Project. Associations between diseases/traits were statistically evaluated by pairwise correlation analysis of GRSs. Overlaps between the genetic susceptibility correlations and disease comorbidity associations from hospital claims data in more than 30 million patients in United States were assessed. Results:Correlation analysis of GRSs revealed 823 significant correlations among 78 diseases and 89 traits (false discovery rate adjusted P -value or Q -value?<?0.01). It is noticeable that GRSs were correlated in 464 associations (56.4%) even if they were combinations of distinct sets of risk variants without chromosomal linkage, suggesting the presence of genetic interactions beyond chromosome position. When 312 significant genetic susceptibility correlations between diseases were compared to nationwide disease comorbidity correlations obtained from data from 32 million Medicare claims in the United States, 108 overlaps (34.6%) were found that had both genetic susceptibility and epidemiologic comorbid correlations. Conclusion:The study suggests that common genetic background exists between diseases and traits with epidemiologic associations. The GRS correlation approach provides a rich source of candidate associations among diseases and traits from the genetic perspective, warranting further epidemiologic studies.
| S-EPMC7651975 | biostudies-literature
Project description:Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.
| S-EPMC5841449 | biostudies-literature
Project description:BACKGROUND AND OBJECTIVES:Metabolic syndrome is a cluster of risk factors associated with CKD. By studying the genetic and environmental influences on how traits of metabolic syndrome correlate with CKD, the understanding of the etiological relationships can be improved. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:From the population-based TwinGene project within the Swedish Twin Registry, 4721 complete twin pairs (9442 European ancestry participants) were included in this cross-sectional twin study. Metabolic syndrome-related continuous traits were measured, and the binary components as well as the status of metabolic syndrome were defined according to the National Cholesterol Education Program-Adult Treatment Panel III. The eGFR was calculated by cystatin C-based equations from the CKD epidemiology collaboration group, and CKD was defined by eGFR<60 ml/min per 1.73 m2. Genetic and environmental contributions to the correlations between traits of metabolic syndrome and CKD were estimated by using twin-based bivariate structural equation models. RESULTS:The correlation between metabolic syndrome and eGFR-defined CKD was 0.16 (95% confidence interval [95% CI], 0.12 to 0.20), out of which 51% (95% CI, 12% to 90%) was explained by genes, whereas 15% (95% CI, 0% to 42%) and 34% (95% CI, 16% to 52%) was explained by the shared and nonshared environment, respectively. The genetic and environmental correlations between metabolic syndrome and CKD were 0.29 (95% CI, 0.07 to 0.51) and 0.27 (95% CI, 0.13 to 0.41), respectively. For the correlation between abdominal obesity and eGFR, 69% (95% CI, 10% to 100%) was explained by genes and 23% (95% CI, 5% to 41%) was explained by environment. The genetic correlation between abdominal obesity and eGFR was -0.30 (95% CI, -0.54 to -0.06), whereas the environmental correlation was -0.14 (95% CI, -0.22 to -0.06). CONCLUSIONS:Both genes and environment contribute to the correlation between metabolic syndrome and eGFR-defined CKD. The genetic contribution is particularly important to the correlation between abdominal obesity and eGFR.
| S-EPMC6832046 | biostudies-literature
Project description:The evolution of elaborate forms of parental care is an important topic in behavioral ecology, yet the factors shaping the evolution of complex suites of parental and offspring traits are poorly understood. Here, we use a multivariate quantitative genetic approach to study phenotypic and genetic correlations between parental and offspring traits in the burying beetle Nicrophorus vespilloides. To this end, we recorded 2 prenatal traits (clutch size and egg size), 2 postnatal parental behaviors (direct care directed toward larvae and indirect care directed toward resource maintenance), 1 offspring behavior (begging), and 2 measures of breeding success (larval dispersal mass and number of dispersing larvae). Females breeding on larger carcasses provided less direct care but produced larger larvae than females breeding on smaller carcasses. Furthermore, there were positive phenotypic correlations between clutch size, direct, and indirect care. Both egg size and direct care were positively correlated with dispersal mass, whereas clutch size was negatively correlated with dispersal mass. Clutch size and number of dispersed larvae showed genetic variance both in terms of differences between populations of origin and significant heritabilities. However, we found no evidence of genetic variance underlying other parental or offspring traits. Our results suggest that correlations between suites of parental traits are driven by variation in individual quality rather than trade-offs, that some parental traits promote offspring growth while others increase the number of offspring produced, and that parental and offspring traits might respond slowly to selection due to low levels of additive genetic variance.
| S-EPMC5255903 | biostudies-literature
Project description:IMPORTANCE:Late-onset Alzheimer disease (AD), the most common form of dementia, places a large burden on families and society. Although epidemiological and clinical evidence suggests a relationship between inflammation and AD, their relationship is not well understood and could have implications for treatment and prevention strategies. OBJECTIVE:To determine whether a subset of genes involved with increased risk of inflammation are also associated with increased risk for AD. DESIGN, SETTING, AND PARTICIPANTS:In a genetic epidemiology study conducted in July 2015, we systematically investigated genetic overlap between AD (International Genomics of Alzheimer's Project stage 1) and Crohn disease, ulcerative colitis, rheumatoid arthritis, type 1 diabetes, celiac disease, and psoriasis using summary data from genome-wide association studies at multiple academic clinical research centers. P values and odds ratios from genome-wide association studies of more than 100?000 individuals were from previous comparisons of patients vs respective control cohorts. Diagnosis for each disorder was previously established for the parent study using consensus criteria. MAIN OUTCOMES AND MEASURES:The primary outcome was the pleiotropic (conjunction) false discovery rate P value. Follow-up for candidate variants included neuritic plaque and neurofibrillary tangle pathology; longitudinal Alzheimer's Disease Assessment Scale cognitive subscale scores as a measure of cognitive dysfunction (Alzheimer's Disease Neuroimaging Initiative); and gene expression in AD vs control brains (Gene Expression Omnibus data). RESULTS:Eight single-nucleotide polymorphisms (false discovery rate P?<?.05) were associated with both AD and immune-mediated diseases. Of these, rs2516049 (closest gene HLA-DRB5; conjunction false discovery rate P?=?.04 for AD and psoriasis, 5.37?×?10-5 for AD, and 6.03?×?10-15 for psoriasis) and rs12570088 (closest gene IPMK; conjunction false discovery rate P?=?.009 for AD and Crohn disease, P?=?5.73?×?10-6 for AD, and 6.57?×?10-5 for Crohn disease) demonstrated the same direction of allelic effect between AD and the immune-mediated diseases. Both rs2516049 and rs12570088 were significantly associated with neurofibrillary tangle pathology (P?=?.01352 and .03151, respectively); rs2516049 additionally correlated with longitudinal decline on Alzheimer's Disease Assessment Scale cognitive subscale scores (? [SE], 0.405 [0.190]; P?=?.03). Regarding gene expression, HLA-DRA and IPMK transcript expression was significantly altered in AD brains compared with control brains (HLA-DRA: ? [SE], 0.155 [0.024]; P?=?1.97?×?10-10; IPMK: ? [SE], -0.096 [0.013]; P?=?7.57?×?10-13). CONCLUSIONS AND RELEVANCE:Our findings demonstrate genetic overlap between AD and immune-mediated diseases and suggest that immune system processes influence AD pathogenesis and progression.
| S-EPMC4905783 | biostudies-literature
Project description:For a long time the relationship between inflammatory bowel diseases (IBDs) and psoriasis has been investigated by epidemiological studies. It is only starting from the 1990s that genetic and immunological aspects have been focused on. Psoriasis and IBD are strictly related inflammatory diseases. Skin and bowel represent, at the same time, barrier and connection between the inner and the outer sides of the body. The most important genetic correlations involve the chromosomal loci 6p22, 16q, 1p31, and 5q33 which map several genes involved in innate and adaptive immunity. The genetic background represents the substrate to the common immune processes involved in psoriasis and IBD. In the past, psoriasis and IBD were considered Th1-related disorders. Nowadays the role of new T cells populations has been highlighted. A key role is played by Th17 and T-regs cells as by the balance between these two cells types. New cytokines and T cells populations, as IL-17A, IL-22, and Th22 cells, could play an important pathogenetic role in psoriasis and IBD. The therapeutic overlaps further support the hypothesis of a common pathogenesis.
| S-EPMC3736484 | biostudies-literature
Project description:Although some studies reported the comprehensive mRNA expression analysis of coronavirus disease 2019 (COVID-19) using blood samples to understand its pathogenesis, the characteristics of RNA expression in COVID-19 and sepsis have not been compared. We compared the transcriptome expression of whole blood samples from patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patients with sepsis caused by other bacteria who entered the intensive care unit to clarify the COVID-19-specific RNA expression and understand its pathogenesis. Transcriptomes related to mitochondria were upregulated in COVID-19, whereas those related to neutrophils were upregulated in sepsis. However, the transcriptomes related to neutrophils were upregulated in both COVID-19 and sepsis compared to in healthy controls, whereas the mitochondrial transcriptomes were upregulated in COVID-19 and downregulated in sepsis compared to in healthy controls. Moreover, sepsis showed sub-optimal intrinsic apoptotic features compared with COVID-19. The transcriptome expression of COVID-19 has been examined in vitro but has not been widely validated using human specimens. This study improves the understanding of the pathogenesis of COVID-19 and can contribute to the development of treatments.
2022-11-29 | GSE199816 | GEO
Project description:BackgroundAge-related macular degeneration (AMD) is a common condition of vision loss with disease development strongly influenced by environmental and genetic factors. Recently, 34 loci were associated with AMD at genome-wide significance. So far, little is known about a genetic overlap between AMD and other complex diseases or disease-relevant traits.MethodsFor each of 60 complex diseases/traits with publicly available genome-wide significant association data, the lead genetic variant per independent locus was extracted and a genetic score was calculated for each disease/trait as the weighted sum of risk alleles. The association with AMD was estimated based on 16,144 AMD cases and 17,832 controls using logistic regression.ResultsOf the respective disease/trait variance, the 60 genetic scores explained on average 4.8% (0.27-20.69%) and 16 of them were found to be significantly associated with AMD (Q-values < 0.01, p values from < 1.0 × 10-16 to 1.9 × 10-3). Notably, an increased risk for AMD was associated with reduced risk for cardiovascular diseases, increased risk for autoimmune diseases, higher HDL and lower LDL levels in serum, lower bone-mineral density as well as an increased risk for skin cancer. By restricting the analysis to 1824 variants initially used to compute the 60 genetic scores, we identified 28 novel AMD risk variants (Q-values < 0.01, p values from 1.1 × 10-7 to 3.0 × 10-4), known to be involved in cardiovascular disorders, lipid metabolism, autoimmune diseases, anthropomorphic traits, ocular disorders, and neurological diseases. The latter variants represent 20 novel AMD-associated, pleiotropic loci. Genes in the novel loci reinforce previous findings strongly implicating the complement system in AMD pathogenesis.ConclusionsWe demonstrate a substantial overlap of the genetics of several complex diseases/traits with AMD and provide statistically significant evidence for an additional 20 loci associated with AMD. This highlights the possibility that so far unrelated pathologies may have disease pathways in common.
| S-EPMC5368911 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other