Browsing by Author "Morris, Andrew P."
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Item Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions(2017) Shungin, Dmitry; Deng, Wei Q.; Varga, Tibor V.; Luan, Jian'an; Mihailov, Evelin; Metspalu, Andres; GIANT Consortium; Morris, Andrew P.; Forouhi, Nita G.; Lindgren, Cecilia; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Hallmans, Göran; Chu, Audrey Y.; Justice, Anne E.; Graff, Mariaelisa; Winkler, Thomas W.; Rose, Lynda M.; Langenberg, Claudia; Cupples, L. Adrienne; Kilpeläinen, Tuomas O.; Scott, Robert A.; Mägi, Reedik; Paré, Guillaume; Franks, Paul W.; Ridker, Paul M.; Wareham, Nicholas J.; Ong, Ken K.; Loos, Ruth J. F.; Chasman, Daniel I.; Ingelsson, ErikPhenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann–Whitney = 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10−9 and 8.52×10−7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.Item The genetic architecture of sporadic and multiple consecutive miscarriage(Nature Communications, 2020-11-25) Laisk, Triin; Soares, Ana Luiza G.; Lindgren, Cecilia M.; Ferreira, Teresa; Painter, Jodie N.; Censin, Jenny C.; Laber, Samantha; Bacelis, Jonas; Chen, Chia-Yen; Lepamets, Maarja; Lawlor, Deborah A.; Mägi, Reedik; Medland, Sarah E.; Granne, Ingrid; Walters, Robin G.; Nielsen, Rasmus; Neale, Benjamin M.; Martin, Nicholas G.; Li, Liming; Jacobsson, Bo; Conrad, Donald F.; Chen, Zhengming; Werge, Thomas; Zondervan, Krina; Snieder, Harold; Salumets, Andres; Seminara, Stephanie; Lippincott, Margaret; Nyholt, Dale R.; Nordentoft, Merete; Njølstad, Pål R.; Mortensen, Preben B.; Mors, Ole; Morris, Andrew P.; Montgomery, Grant W.; Metspalu, Andres; Lind, Penelope A.; Kukushkina, Viktorija; Kartsonaki, Christiana; Juodakis, Julius; Johansson, Stefan; Jin, Xin; Hougaard, David M.; Helgeland, Øyvind; Bybjerg-Grauholm, Jonas; Gordon, Scott D.; Børglum, Anders D.; Becker, Christian M.; Yang, Ling; Andersen, Marianne S.; Southcombe, Jennifer; Ramu, Avinash; Millwood, Iona Y.; Liu, Siyang; Lin, KuangMiscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10−8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10−8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10−9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10−8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.