Christopher S Thom 1,6 , Madison B Wilken 1, Stella T Chou 2, Benjamin F Voight 3,4,5,6
1 Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
2 Division of Hematology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
3 Department of Systems Pharmacology and Translational Therapeutics, Philadelphia, PA, USA
4 Department of Genetics, University of Perelman School of Medicine, Philadelphia, PA, USA
5 Institute for Translational Medicine, University of Perelman School of Medicine, Philadelphia, PA, USA
6 Correspondence:
Christopher S Thom thomc@chop.edu Children’s Hospital of Philadelphia Abramson Research Center, Room 415 3615 Civic Center Blvd Philadelphia, PA 19104
Benjamin F Voight bvoight@pennmedicine.upenn.edu Smilow Center for Translational Research, Room 10-126 3400 Civic Center Blvd Philadelphia, PA 19104
Body mass index (BMI), hyperlipidemia, and truncal adipose distribution concordantly elevate cardiovascular disease risks, but have unknown genetic effects on blood trait variation. Using Mendelian randomization, we define unexpectedly opposing roles for increased BMI and truncal adipose distribution on blood traits. Elevated genetically determined BMI and lipid levels decreased hemoglobin and hematocrit levels, consistent with clinical observations associating obesity and anemia. We found that lipid-related effects were confined to erythroid traits. In contrast, BMI affected multiple blood lineages, indicating broad effects on hematopoiesis. Increased truncal adipose distribution opposed BMI effects, increasing hemoglobin and blood cell counts across lineages. Conditional analyses indicated genes, pathways, and cell types responsible for these effects, including Leptin Receptor and other blood cell-extrinsic factors in adipocytes and endothelium that regulate hematopoietic stem and progenitor cell biology. Our findings identify novel roles for obesity on hematopoiesis, including a previously underappreciated role for genetically determined adipose distribution in determining blood cell formation and function.
Now published at eLife: 10.7554/eLife.75317
BMI, WHR, and WHRadjBMI summary statistics were obtained from: Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, Yengo L, Ferreira T, Marouli E, Ji Y, Yang J, Jones S, Beaumont R, Croteau-Chonka DC, Winkler TW, Hattersley AT, Loos RJF, Hirschhorn JN, Visscher PM, Frayling TM, Yaghootkar H, Lindgren CM. 2019. Meta-Analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet 28:166–174
Blood trait summary statistics were obtained from: Vuckovic D, Bao EL, Akbari P, Lareau CA, Mousas A, Jiang T, Chen MH, Raffield LM, Tardaguila M, Huffman JE, Ritchie SC, Megy K, Ponstingl H, Penkett CJ, Albers PK, Wigdor EM, Sakaue S, Moscati A, Manansala R, Lo KS, Qian H, Akiyama M, Bartz TM, Ben-Shlomo Y, Beswick A, Bork-Jensen J, Bottinger EP, Brody JA, van Rooij FJA, Chitrala KN, Wilson PWF, Choquet H, Danesh J, Di Angelantonio E, Dimou N, Ding J, Elliott P, Esko T, Evans MK, Felix SB, Floyd JS, Broer L, Grarup N, Guo MH, Guo Q, Greinacher A, Haessler J, Hansen T, Howson JMM, Huang W, Jorgenson E, Kacprowski T, Kähönen M, Kamatani Y, Kanai M, Karthikeyan S, Koskeridis F, Lange LA, Lehtimäki T, Linneberg A, Liu Y, Lyytikäinen LP, Manichaikul A, Matsuda K, Mohlke KL, Mononen N, Murakami Y, Nadkarni GN, Nikus K, Pankratz N, Pedersen O, Preuss M, Psaty BM, Raitakari OT, Rich SS, Rodriguez BAT, Rosen JD, Rotter JI, Schubert P, Spracklen CN, Surendran P, Tang H, Tardif JC, Ghanbari M, Völker U, Völzke H, Watkins NA, Weiss S, Cai N, Kundu K, Watt SB, Walter K, Zonderman AB, Cho K, Li Y, Loos RJF, Knight JC, Georges M, Stegle O, Evangelou E, Okada Y, Roberts DJ, Inouye M, Johnson AD, Auer PL, Astle WJ, Reiner AP, Butterworth AS, Ouwehand WH, Lettre G, Sankaran VG, Soranzo N. 2020. The Polygenic and Monogenic Basis of Blood Traits and Diseases. Cell 182:1214-1231.e11.
Lipid trait summary statistics were obtained from: Klarin D, Damrauer SM, Cho K, Sun Y V., Teslovich TM, Honerlaw J, Gagnon DR, DuVall SL, Li J, Peloso GM, Chaffin M, Small AM, Huang J, Tang H, Lynch JA, Ho YL, Liu DJ, Emdin CA, Li AH, Huffman JE, Lee JS, Natarajan P, Chowdhury R, Saleheen D, Vujkovic M, Baras A, Pyarajan S, Di Angelantonio E, Neale BM, Naheed A, Khera A V., Danesh J, Chang KM, Abecasis G, Willer C, Dewey FE, Carey DJ, Concato J, Gaziano JM, O’Donnell CJ, Tsao PS, Kathiresan S, Rader DJ, Wilson PWF, Assimes TL. 2018. Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program. Nat Genet 50:1514–1523.
Scripts utilized R, python, and linux platforms
We created instrumental variables and performed MR (univariable and multivariable) on GWAS summary statistics derived from the studies cited above
TwoSampleMR (https://mrcieu.github.io/TwoSampleMR/)
MVMR (https://github.com/WSpiller/MVMR)
Based on our MR findings, we explored conditional GWAS analyses to define novel loci, genes and related biology
GCTA (https://yanglab.westlake.edu.cn/software/gcta/#Overview), specifically the mtCOJO package (https://yanglab.westlake.edu.cn/software/gcta/#mtCOJO)
We created figures using Inkscape, BioRender (BioRender.com), GraphPad Prism, and LocusZoom (http://locuszoom.org/)