Ontology highlight
ABSTRACT: Background
Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank.Results
Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation.Conclusion
We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.
SUBMITTER: Bradfield JP
PROVIDER: S-EPMC10790528 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Bradfield Jonathan P JP Kember Rachel L RL Ulrich Anna A Balkhiyarova Zhanna Z Alyass Akram A Aris Izzuddin M IM Bell Joshua A JA Broadaway K Alaine KA Chen Zhanghua Z Chai Jin-Fang JF Davies Neil M NM Fernandez-Orth Dietmar D Bustamante Mariona M Fore Ruby R Ganguli Amitavo A Heiskala Anni A Hottenga Jouke-Jan JJ Íñiguez Carmen C Kobes Sayuko S Leinonen Jaakko J Lowry Estelle E Lyytikainen Leo-Pekka LP Mahajan Anubha A Pitkänen Niina N Schnurr Theresia M TM Have Christian Theil CT Strachan David P DP Thiering Elisabeth E Vogelezang Suzanne S Wade Kaitlin H KH Wang Carol A CA Wong Andrew A Holm Louise Aas LA Chesi Alessandra A Choong Catherine C Cruz Miguel M Elliott Paul P Franks Steve S Frithioff-Bøjsøe Christine C Gauderman W James WJ Glessner Joseph T JT Gilsanz Vicente V Griesman Kendra K Hanson Robert L RL Kaakinen Marika M Kalkwarf Heidi H Kelly Andrea A Kindler Joseph J Kähönen Mika M Lanca Carla C Lappe Joan J Lee Nanette R NR McCormack Shana S Mentch Frank D FD Mitchell Jonathan A JA Mononen Nina N Niinikoski Harri H Oken Emily E Pahkala Katja K Sim Xueling X Teo Yik-Ying YY Baier Leslie J LJ van Beijsterveldt Toos T Adair Linda S LS Boomsma Dorret I DI de Geus Eco E Guxens Mònica M Eriksson Johan G JG Felix Janine F JF Gilliland Frank D FD Biobank Penn Medicine PM Hansen Torben T Hardy Rebecca R Hivert Marie-France MF Holm Jens-Christian JC Jaddoe Vincent W V VWV Järvelin Marjo-Riitta MR Lehtimäki Terho T Mackey David A DA Meyre David D Mohlke Karen L KL Mykkänen Juha J Oberfield Sharon S Pennell Craig E CE Perry John R B JRB Raitakari Olli O Rivadeneira Fernando F Saw Seang-Mei SM Sebert Sylvain S Shepherd John A JA Standl Marie M Sørensen Thorkild I A TIA Timpson Nicholas J NJ Torrent Maties M Willemsen Gonneke G Hypponen Elina E Power Chris C McCarthy Mark I MI Freathy Rachel M RM Widén Elisabeth E Hakonarson Hakon H Prokopenko Inga I Voight Benjamin F BF Zemel Babette S BS Grant Struan F A SFA Cousminer Diana L DL
Genome biology 20240116 1
<h4>Background</h4>Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pu ...[more]