A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium
Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates a...
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Journal article |
| Published: |
Nature Publishing Group
2016
|
| _version_ | 1826307344038887424 |
|---|---|
| author | Ried, J Jeff, J Mahajan, A Goel, A Mahajan, A Farrall, M Ferreira, T Jalilzadeh-Afshari, S Kyriakou, T Lindgren, C Morris, A Watkins, H Rayner, N McCarthy, M Et al. |
| author_facet | Ried, J Jeff, J Mahajan, A Goel, A Mahajan, A Farrall, M Ferreira, T Jalilzadeh-Afshari, S Kyriakou, T Lindgren, C Morris, A Watkins, H Rayner, N McCarthy, M Et al. |
| author_sort | Ried, J |
| collection | OXFORD |
| description | Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analyzed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways. |
| first_indexed | 2024-03-07T07:00:52Z |
| format | Journal article |
| id | oxford-uuid:ffb534c7-63bd-4eb7-a95f-086127a17ab1 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T07:00:52Z |
| publishDate | 2016 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | oxford-uuid:ffb534c7-63bd-4eb7-a95f-086127a17ab12022-03-27T13:47:05ZA principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT ConsortiumJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ffb534c7-63bd-4eb7-a95f-086127a17ab1Symplectic Elements at OxfordNature Publishing Group2016Ried, JJeff, JMahajan, AGoel, AMahajan, AFarrall, MFerreira, TJalilzadeh-Afshari, SKyriakou, TLindgren, CMorris, AWatkins, HRayner, NMcCarthy, MEt al.Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analyzed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways. |
| spellingShingle | Ried, J Jeff, J Mahajan, A Goel, A Mahajan, A Farrall, M Ferreira, T Jalilzadeh-Afshari, S Kyriakou, T Lindgren, C Morris, A Watkins, H Rayner, N McCarthy, M Et al. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title | A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title_full | A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title_fullStr | A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title_full_unstemmed | A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title_short | A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape in >170,000 individuals of the GIANT Consortium |
| title_sort | principal component meta analysis on multiple anthropometric traits identifies novel loci for body shape in gt 170 000 individuals of the giant consortium |
| work_keys_str_mv | AT riedj aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT jeffj aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mahajana aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT goela aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mahajana aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT farrallm aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT ferreirat aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT jalilzadehafsharis aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT kyriakout aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT lindgrenc aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT morrisa aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT watkinsh aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT raynern aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mccarthym aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT etal aprincipalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT riedj principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT jeffj principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mahajana principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT goela principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mahajana principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT farrallm principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT ferreirat principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT jalilzadehafsharis principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT kyriakout principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT lindgrenc principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT morrisa principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT watkinsh principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT raynern principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT mccarthym principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium AT etal principalcomponentmetaanalysisonmultipleanthropometrictraitsidentifiesnovellociforbodyshapeingt170000individualsofthegiantconsortium |