Evidence for shared genetic risk factors between lymphangioleiomyomatosis and pulmonary function

Lymphangioleiomyomatosis; Risk factors; Pulmonary functionLinfangioleiomiomatosis; Factores de riesgo; Función pulmonarLimfangioleiomiomatosi; Factors de risc; Funció pulmonarIntroduction Lymphangioleiomyomatosis (LAM) is a rare low-grade metastasising disease characterised by cystic lung destruction. The genetic basis of LAM remains incompletely determined, and the disease cell-of-origin is uncertain. We analysed the possibility of a shared genetic basis between LAM and cancer, and LAM and pulmonary function. Methods The results of genome-wide association studies of LAM, 17 cancer types and spirometry measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio and peak expiratory flow (PEF)) were analysed for genetic correlations, shared genetic variants and causality. Genomic and transcriptomic data were examined, and immunodetection assays were performed to evaluate pleiotropic genes. Results There were no significant overall genetic correlations between LAM and cancer, but LAM correlated negatively with FVC and PEF, and a trend in the same direction was observed for FEV1. 22 shared genetic variants were uncovered between LAM and pulmonary function, while seven shared variants were identified between LAM and cancer. The LAM-pulmonary function shared genetics identified four pleiotropic genes previously recognised in LAM single-cell transcriptomes: ADAM12, BNC2, NR2F2 and SP5. We had previously associated NR2F2 variants with LAM, and we identified its functional partner NR3C1 as another pleotropic factor. NR3C1 expression was confirmed in LAM lung lesions. Another candidate pleiotropic factor, CNTN2, was found more abundant in plasma of LAM patients than that of healthy women. Conclusions This study suggests the existence of a common genetic aetiology between LAM and pulmonary function

Multi-Ancestry Genome-Wide Association Analyses Improve Resolution of Genes and Pathways Influencing Lung Function and Chronic Obstructive Pulmonary Disease Risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies

Single-Trait and Multi-Trait Genome-Wide Association Analyses Identify Novel Loci for Blood Pressure in African-Ancestry Populations

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P \u3c 1.25×10−8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies

Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Abstract Background Many disease phenotypes are outcomes of the complicated interplay between multiple genes, and multiple phenotypes are affected by a single or multiple genotypes. Therefore, joint analysis of multiple phenotypes and multiple markers has been considered as an efficient strategy for genome-wide association analysis, and in this work we propose an omnibus family-based association test for the joint analysis of multiple genotypes and multiple phenotypes. Results The proposed test can be applied for both quantitative and dichotomous phenotypes, and it is robust under the presence of population substructure, as long as large-scale genomic data is available. Using simulated data, we showed that our method is statistically more efficient than the existing methods, and the practical relevance is illustrated by application of the approach to obesity-related phenotypes. Conclusions The proposed method may be more statistically efficient than the existing methods. The application was developed in C++ and is available at the following URL: http://healthstat.snu.ac.kr/software/mfqls/

Lack of Association between Oxytocin Receptor (OXTR) Gene Polymorphisms and Alexithymia: Evidence from Patients with Obsessive-Compulsive Disorder

<div><p>Oxytocin receptor gene single nucleotide polymorphisms have been associated with structural and functional alterations in brain regions, which involve social-emotional processing. Therefore, oxytocin receptor gene polymorphisms may contribute to individual differences in alexithymia, which is considered to be a dysfunction of emotional processing. The aim of this study was to evaluate the association between oxytocin receptor gene single nucleotide polymorphisms or haplotypes and alexithymia in patients with obsessive-compulsive disorder. We recruited 355 patients with obsessive-compulsive disorder (234 men, 121 women). Alexithymia was measured by using the Toronto Alexithymia Scale. We performed single-marker and haplotype association analyses with eight single nucleotide polymorphisms (rs237885, rs237887, rs2268490, rs4686301, rs2254298, rs13316193, rs53576, and rs2268498) in the oxytocin receptor gene. There were no significant associations between any of the eight single nucleotide polymorphism of the oxytocin receptor gene and alexithymia. In addition, a six-locus haplotype block (rs237885-rs237887-rs2268490-rs4686301-rs2254298-rs13316193) was not significantly associated with alexithymia. These findings suggest that genetic variations in the oxytocin receptor gene may not explain a significant part of alexithymia in patients with obsessive-compulsive disorder.</p></div

Risk assessment for hypertension and hypertension complications incidences using a Bayesian network

The Bayesian network is a useful method for modeling healthcare issues since it can graphically represent causal relationships among variables and provide probabilistic information. We apply this method to conduct hypertension and hypertension complications incidence analyses using the National Health Insurance Corporation (NHIC) sample cohort database from 2002 to 2010, which contains more than a million prescribers' information, including socio-demographic information, health check-up records, and other information related to medical treatments and medical expenses in South Korea. We select significant factors that affect hypertension and its complications incidence using Cox regression, and perform Bayesian network analysis with respect to those factors. We investigate the causality for hypertension and its complications incidence, and then calculate the conditional probabilities about nodes of interest. In addition, we evaluate performance to predict the incidence of hypertension and its complications. We conclude that the Bayesian network method has several notable advantages. Firstly, it can demonstrate which factors affect hypertension and its complications incidence and how they are related to each other. Secondly, it can calculate conditional probability; thus, we can perform qualitative and quantitative analyses at the same time