Variants associated withHHIP expression have sex-differential effects on lung function

Publisher Copyright: © 2020 Fawcett KA et al.Background: Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females. Methods: We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium. Results: Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P<5x10 -8) interactions with sex on lung function, and 21 showed suggestive interactions (P<1x10 -6). The strongest signal, from rs7697189 (chr4:145436894) on forced expiratory volume in 1 second (FEV 1) (P=3.15x10 -15), was replicated (P=0.016) in SpiroMeta. The C allele increased FEV 1 more in males (untransformed FEV 1 β=0.028 [SE 0.0022] litres) than females (β=0.009 [SE 0.0014] litres), and this effect was not accounted for by differential effects on height, smoking or pubertal age. rs7697189 resides upstream of the hedgehog-interacting protein ( HHIP) gene and was previously associated with lung function and HHIP lung expression. We found HHIP expression was significantly different between the sexes (P=6.90x10 -6), but we could not detect sex differential effects of rs7697189 on expression. Conclusions: We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the HHIP gene. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.Peer reviewe

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects.

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

Funding Information: This research has been conducted using the UK Biobank Resource. This research has been conducted using the Danish National Biobank resource. The authors are grateful to the Raine Study participants and their families, and to the Raine Study research staff for cohort co-ordination and data collection. QIMR is grateful to the twins and their families for their generous participation in these studies. We would like to thank staff at the Queensland Institute of Medical Research: Anjali Henders, Dixie Statham, Lisa Bowdler, Ann Eldridge, and Marlene Grace for sample collection, processing and genotyping, Scott Gordon, Brian McEvoy, Belinda Cornes and Beben Benyamin for data QC and preparation, and David Smyth and Harry Beeby for IT support. HBCS Acknowledgements: We thank all study participants as well as everybody involved in the Helsinki Birth Cohort Study. Helsinki Birth Cohort Study has been supported by grants from the Academy of Finland, the Finnish Diabetes Research Society, Folkhälsan Research Foundation, Novo Nordisk Foundation, Finska Läkaresällskapet, Juho Vainio Foundation, Signe and Ane Gyllenberg Foundation, University of Helsinki, Ministry of Education, Ahokas Foundation, Emil Aaltonen Foundation. Finrisk study is grateful for the THL DNA laboratory for its skillful work to produce the DNA samples used in this study and thanks the Sanger Institute and FIMM genotyping facilities for genotyping the samples. We thank the MOLGENIS team and Genomics Coordination Center of the University Medical Center Groningen for software development and data management, in particular Marieke Bijlsma and Edith Adriaanse. This work was supported by the Leenards Foundation (to Z.K.), the Swiss National Science Foundation (31003A_169929 to Z.K., Sinergia grant CRSII33-133044 to AR), Simons Foundation (SFARI274424 to AR) and SystemsX.ch (51RTP0_151019 to Z.K.). A.R.W., H.Y. and T.M.F. are supported by the European Research Council grant: 323195:SZ-245. M.A.T., M.N.W. and An.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). For full funding information of all participating cohorts see Supplementary Note 2. Publisher Copyright: © 2017 The Author(s).There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (> 2.4 cm), weight ( 5 kg), and body mass index (BMI) (> 3.5 kg/m(2)). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m2 for each Mb of total deletion burden (P = 2.5 x 10(-10), 6.0 x 10(-5), and 2.9 x 10(-3)). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Peer reviewe

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

Correction to: Nature Geneticshttps://doi.org/10.1038/s41588-023-01314-0, published online 13 March 2023. In the version of the article initially published, the sample sizes in the main text and Supplementary Tables 1 and 2 were incorrect. In the abstract, the last paragraph of the Introduction, the first paragraph of the Results, the top box in Figure 1a and the Supplementary Information, the total sample size has been corrected from 580,869 to 588,452 participants and the size of the European cohort from 468,062 to 475,645. Some of the effect sizes in Supplementary Table 14 (columns W, Z, AC, AF) had the wrong sign. There was also an error in Supplementary Table 3 where the sample size instead of the variant count was shown for EXCEED. The errors do not affect the conclusions of the study. Additionally, two acknowledgments for use of INTERVAL pQTL and Lung eQTL consortium data were omitted from the Supplementary Information. These errors have been corrected in the Supplementary Information and HTML and PDF versions of the article

Hair Cortisol in Twins : Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes

A. Palotie on työryhmän jäsen.Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.Peer reviewe

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Variants associated with HHIP expression have sexdifferential effects on lung function

Background: Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females.Methods: We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium.Results: Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P-8) interactions with sex on lung function, and 21 showed suggestive interactions (P-6). The strongest signal, from rs7697189 (chr4:145436894) on forced expiratory volume in 1 second (FEV1) (P=3.15x10-15), was replicated (P=0.016) in SpiroMeta. The C allele increased FEV1 more in males (untransformed FEV1 β=0.028 [SE 0.0022] litres) than females (β=0.009 [SE 0.0014] litres), and this effect was not accounted for by differential effects on height, smoking or pubertal age. rs7697189 resides upstream of the hedgehog-interacting protein (HHIP) gene and was previously associated with lung function and HHIP lung expression. We found HHIP expression was significantly different between the sexes (P=6.90x10-6), but we could not detect sex differential effects of rs7697189 on expression.Conclusions: We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the HHIP gene. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.</p

Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets

Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratio per 1 s.d. of the risk score (∼6 alleles) (95% confidence interval) = 1.24 (1.20-1.27), P = 5.05 × 10‾⁴⁹), and we observed a 3.7-fold difference in COPD risk between individuals in the highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in genes for development, elastic fibers and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.This work was funded by a Medical Research Council (MRC) strategic award to M.D.T., I.P.H., D.S. and L.V.W. (MC_PC_12010). This research has been conducted using the UK Biobank Resource under application 648. This article presents independent research funded partially by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health. This research used the ALICE and SPECTRE High-Performance Computing Facilities at the University of Leicester. Additional acknowledgments and funding details can be found in the Supplementary Note

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