Metabolomic profiling identifies complex lipid species and amino acid analogues associated with response to weight loss interventions

被引:13
作者
Bihlmeyer, Nathan A. [1 ]
Kwee, Lydia Coulter [1 ]
Clish, Clary B. [2 ]
Deik, Amy Anderson [2 ]
Gerszten, Robert E. [3 ]
Pagidipati, Neha J. [4 ,5 ]
Laferrere, Blandine [6 ]
Svetkey, Laura P. [5 ]
Newgard, Christopher B. [1 ]
Kraus, William E. [1 ]
Shah, Svati H. [1 ,4 ,5 ]
机构
[1] Duke Univ, Duke Mol Physiol Inst, Durham, NC 27708 USA
[2] Broad Inst MIT & Harvard, Metabol Platform, Cambridge, MA 02142 USA
[3] Harvard Med Sch, Beth Israel Deaconess Med Ctr, Div Cardiovasc Med, Boston, MA 02115 USA
[4] Duke Univ, Duke Clin Res Inst, Durham, NC 27708 USA
[5] Duke Univ, Sch Med, Dept Med, Durham, NC 27706 USA
[6] Columbia Univ, Irving Med Ctr, New York, NY USA
来源
PLOS ONE | 2021年 / 16卷 / 05期
关键词
DIETARY PATTERNS; GASTRIC BYPASS; BLOOD-PRESSURE; OBESITY; HMDB; PHOSPHORYLATION; MANAGEMENT; MORTALITY;
D O I
10.1371/journal.pone.0240764
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought to identify metabolic biomarkers that are associated with beneficial metabolic changes to weight loss and which distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N = 443), STRRIDE-PD (exercise intervention, N = 163), and CBD (surgical cohort, N = 125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance [%Delta HOMA-IR]) over the intervention. Overall, 92 individual metabolites were associated with %Delta HOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p = 2.3e-5) and diacylglycerols (DAGs; p = 1.6e-4), with higher baseline TAG and DAG levels associated with a greater improvement in insulin resistance with weight loss. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions.
引用
收藏
页数:17
相关论文
共 47 条
  • [21] Effect of dietary patterns on measures of lipid peroxidation - Results from a randomized clinical trial
    Miller, ER
    Appel, LJ
    Risby, TH
    [J]. CIRCULATION, 1998, 98 (22) : 2390 - 2395
  • [22] PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes
    Mootha, VK
    Lindgren, CM
    Eriksson, KF
    Subramanian, A
    Sihag, S
    Lehar, J
    Puigserver, P
    Carlsson, E
    Ridderstråle, M
    Laurila, E
    Houstis, N
    Daly, MJ
    Patterson, N
    Mesirov, JP
    Golub, TR
    Tamayo, P
    Spiegelman, B
    Lander, ES
    Hirschhorn, JN
    Altshuler, D
    Groop, LC
    [J]. NATURE GENETICS, 2003, 34 (03) : 267 - 273
  • [23] The Role of Microbial Amino Acid Metabolism in Host Metabolism
    Neis, Evelien P. J. G.
    Dejong, Cornelis H. C.
    Rensen, Sander S.
    [J]. NUTRIENTS, 2015, 7 (04): : 2930 - 2946
  • [24] Interplay between Lipids and Branched-Chain Amino Acids in Development of Insulin Resistance
    Newgard, Christopher B.
    [J]. CELL METABOLISM, 2012, 15 (05) : 606 - 614
  • [25] A Branched-Chain Amino Acid-Related Metabolic Signature that Differentiates Obese and Lean Humans and Contributes to Insulin Resistance
    Newgard, Christopher B.
    An, Jie
    Bain, James R.
    Muehlbauer, Michael J.
    Stevens, Robert D.
    Lien, Lillian F.
    Haqq, Andrea M.
    Shah, Svati H.
    Arlotto, Michelle
    Slentz, Cris A.
    Rochon, James
    Gallup, Dianne
    Ilkayeva, Olga
    Wenner, Brett R.
    Yancy, William S., Jr.
    Eisenson, Howard
    Musante, Gerald
    Surwit, Richard S.
    Millington, David S.
    Butler, Mark D.
    Svetkey, Laura P.
    [J]. CELL METABOLISM, 2009, 9 (04) : 311 - 326
  • [26] Obarzanek E, 2001, AM J CLIN NUTR, V74, P80
  • [27] Ogden Cynthia L, 2012, NCHS Data Brief, P1
  • [28] Urinary intermediates of tryptophan as indicators of the gut microbial metabolism
    Pavlova, Tereza
    Vidova, Veronika
    Bienertova-Vasku, Julie
    Janku, Petr
    Almasi, Martina
    Klanova, Jana
    Spacil, Zdenek
    [J]. ANALYTICA CHIMICA ACTA, 2017, 987 : 72 - 80
  • [29] Metabolic Predictors of Incident Coronary Heart Disease in Women
    Paynter, Nina P.
    Balasubramanian, Raji
    Giulianini, Franco
    Wang, Dong D.
    Tinker, Lesley F.
    Gopal, Shuba
    Deik, Amy A.
    Bullock, Kevin
    Pierce, Kerry A.
    Scott, Justin
    Martinez-Gonzalez, Miguel A.
    Estruch, Ramon
    Manson, JoAnn E.
    Cook, Nancy R.
    Albert, Christine M.
    Clish, Clary B.
    Rexrode, Kathryn M.
    [J]. CIRCULATION, 2018, 137 (08) : 841 - 853
  • [30] Insulin receptor Thr1160 phosphorylation mediates lipid-induced hepatic insulin resistance
    Petersen, Max C.
    Madiraju, Anila K.
    Gassaway, Brandon M.
    Marcel, Michael
    Nasiri, Ali R.
    Butrico, Gina
    Marcucci, Melissa J.
    Zhang, Dongyan
    Abulizi, Abudulcadier
    Zhang, Xian-Man
    Philbrick, William
    Hubbard, Stevan R.
    Jurczak, Michael J.
    Samuel, Varman T.
    Rinehart, Jesse
    Shulman, Gerald I.
    [J]. JOURNAL OF CLINICAL INVESTIGATION, 2016, 126 (11) : 4361 - 4371