View Item 

Show simple item record

Strategies to Understand the Weight‐Reduced State: Genetics and Brain Imaging
dc.contributor.authorLoos, Ruth J. F.
dc.contributor.authorBurant, Charles
dc.contributor.authorSchur, Ellen A.
dc.date.accessioned2021-04-06T02:12:33Z
dc.date.available2022-05-05 22:12:31en
dc.date.available2021-04-06T02:12:33Z
dc.date.issued2021-04
dc.identifier.citationLoos, Ruth J. F.; Burant, Charles; Schur, Ellen A. (2021). "Strategies to Understand the Weight‐Reduced State: Genetics and Brain Imaging." Obesity : S39-S50.
dc.identifier.issn1930-7381
dc.identifier.issn1930-739X
dc.identifier.urihttps://hdl.handle.net/2027.42/167080
dc.publisherSpringer
dc.publisherWiley Periodicals, Inc.
dc.titleStrategies to Understand the Weight‐Reduced State: Genetics and Brain Imaging
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelEndocrinology
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167080/1/oby23101.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167080/2/oby23101_am.pdf
dc.identifier.doi10.1002/oby.23101
dc.identifier.sourceObesity
dc.identifier.citedreferenceThomas K, Beyer F, Lewe G, et al. Higher body mass index is linked to altered hypothalamic microstructure. Sci Rep 2019; 9: 17373. doi: 10.1038/s41598‐019‐53578‐4
dc.identifier.citedreferenceMcCaffery JM, Papandonatos GD, Huggins GS, et al. FTO predicts weight regain in the Look AHEAD clinical trial. Int J Obes (Lond) 2013; 37: 1545 ‐ 1552.
dc.identifier.citedreferenceMcCaffery JM, Papandonatos GD, Huggins GS, et al. Human cardiovascular disease IBC chip‐wide association with weight loss and weight regain in the Look AHEAD trial. Hum Hered 2013; 75: 160 ‐ 174.
dc.identifier.citedreferenceNettleton JA, Follis JL, Ngwa JS, et al. Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. Hum Mol Genet 2015; 24: 4728 ‐ 4738.
dc.identifier.citedreferenceRasmussen‐Torvik LJ, Baldridge AS, Pacheco JA, et al. rs4771122 predicts multiple measures of long‐term weight loss after bariatric surgery. Obes Surg 2015; 25: 2225 ‐ 2229.
dc.identifier.citedreferenceGTEx Consortium. Human genomics. The Genotype–Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 2015; 348: 648 ‐ 660.
dc.identifier.citedreferenceSharma MR, Koc EC, Datta PP, Booth TM, Spremulli LL, Agrawal RK. Structure of the mammalian mitochondrial ribosome reveals an expanded functional role for its component proteins. Cell 2003; 115: 97 ‐ 108.
dc.identifier.citedreferenceRoth CL, Melhorn SJ, Elfers CT, et al. Central nervous system and peripheral hormone responses to a meal in children. J Clin Endocrinol Metab 2019; 104: 1471 ‐ 1483.
dc.identifier.citedreferenceMelhorn SJ, Askren MK, Chung WK, et al. FTO genotype impacts food intake and corticolimbic activation. Am J Clin Nutr 2018; 107: 145 ‐ 154.
dc.identifier.citedreferenceBruce AS, Holsen LM, Chambers RJ, et al. Obese children show hyperactivation to food pictures in brain networks linked to motivation, reward and cognitive control. Int J Obes 2010; 34: 1494 ‐ 1500.
dc.identifier.citedreferenceSchur EA, Melhorn SJ, Scholz K, et al. Child neurobiology impacts success in family‐based behavioral treatment for children with obesity. Int J Obes 2020; 44: 2011 ‐ 2022.
dc.identifier.citedreferenceGolden NH, Ashtari M, Kohn MR, et al. Reversibility of cerebral ventricular enlargement in anorexia nervosa, demonstrated by quantitative magnetic resonance imaging. J Pediatr 1996; 128: 296 ‐ 301.
dc.identifier.citedreferencedel Parigi A, Schur E. Eating disorders. In: Cohen R, Sweet LH, eds. Brain Imaging in Behavioral Medicine and Clinical Neuroscience. New York: Springer; 2011: 179 ‐ 191.
dc.identifier.citedreferenceSein P, Searson S, Nicol AR, Hall K. Anorexia nervosa and pseudo‐atrophy of the brain. Br J Psychiatry 1981; 139: 257 ‐ 258.
dc.identifier.citedreferenceMukherjee P, Berman JI, Chung SW, Hess CP, Henry RG. Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. AJNR Am J Neuroradiol 2008; 29: 632 ‐ 641.
dc.identifier.citedreferenceDouglass JD, Dorfman MD, Fasnacht R, Shaffer LD, Thaler JP. Astrocyte IKKbeta/NF‐kappaB signaling is required for diet‐induced obesity and hypothalamic inflammation. Molecular Metabolism 2017; 6: 366 ‐ 373.
dc.identifier.citedreferenceValdearcos M, Douglass JD, Robblee MM, et al. Microglial inflammatory signaling orchestrates the hypothalamic immune response to dietary excess and mediates obesity susceptibility. Cell Metab 2018; 27: 1356. doi: 10.1016/j.cmet.2018.04.019
dc.identifier.citedreferenceDouglass JD, Dorfman MD, Thaler JP. Glia: silent partners in energy homeostasis and obesity pathogenesis. Diabetologia 2017; 60: 226 ‐ 236.
dc.identifier.citedreferenceSofroniew MV. Molecular dissection of reactive astrogliosis and glial scar formation. Trends Neurosci 2009; 32: 638 ‐ 647.
dc.identifier.citedreferenceKarimi‐Abdolrezaee S, Billakanti R. Reactive astrogliosis after spinal cord injury‐beneficial and detrimental effects. Mol Neurobiol 2012; 46: 251 ‐ 264.
dc.identifier.citedreferenceBriellmann RS, Kalnins RM, Berkovic SF, Jackson GD. Hippocampal pathology in refractory temporal lobe epilepsy: T2‐weighted signal change reflects dentate gliosis. Neurology 2002; 58: 265 ‐ 271.
dc.identifier.citedreferenceChung YL, Williams A, Ritchie D, et al. Conflicting MRI signals from gliosis and neuronal vacuolation in prion diseases. Neuroreport 1999; 10: 3471 ‐ 3477.
dc.identifier.citedreferenceJackson GD, Williams SR, Weller RO, et al. Vigabatrin‐induced lesions in the rat brain demonstrated by quantitative magnetic resonance imaging. Epilepsy Res 1994; 18: 57 ‐ 66.
dc.identifier.citedreferenceBerkseth KE, Guyenet SJ, Melhorn SJ, et al. Hypothalamic gliosis associated with high‐fat diet feeding is reversible in mice: a combined immunohistochemical and magnetic resonance imaging study. Endocrinology 2014; 155: 2858 ‐ 2867.
dc.identifier.citedreferenceSchur EA, Melhorn SJ, Oh SK, et al. Radiologic evidence that hypothalamic gliosis is associated with obesity and insulin resistance in humans. Obesity (Silver Spring) 2015; 23: 2142 ‐ 2148.
dc.identifier.citedreferenceKreutzer C, Peters S, Schulte DM, et al. Hypothalamic inflammation in human obesity is mediated by environmental and genetic factors. Diabetes 2017; 66: 2407 ‐ 2415.
dc.identifier.citedreferenceSewaybricker LE, Schur EA, Melhorn SJ, et al. Initial evidence for hypothalamic gliosis in children with obesity by quantitative T2 MRI and implications for blood oxygen‐level dependent response to glucose ingestion. Pediatr Obes 2019; 14: e12486. doi: 10.1111/ijpo.12486
dc.identifier.citedreferenceBerkseth KE, Rubinow KB, Melhorn SJ, et al. Hypothalamic gliosis by MRI and visceral fat mass negatively correlate with plasma testosterone concentrations in healthy men. Obesity (Silver Spring) 2018; 26: 1898 ‐ 1904.
dc.identifier.citedreferenceAlkan A, Sahin I, Keskin L, et al. Diffusion‐weighted imaging features of brain in obesity. Magn Reson Imaging 2008; 26: 446 ‐ 450.
dc.identifier.citedreferencePuig J, Blasco G, Daunis IEJ, et al. Hypothalamic damage is associated with inflammatory markers and worse cognitive performance in obese subjects. J Clin Endocrinol Metab 2015; 100: E276 ‐ E281.
dc.identifier.citedreferenceCazettes F, Cohen JI, Yau PL, Talbot H, Convit A. Obesity‐mediated inflammation may damage the brain circuit that regulates food intake. Brain Res 2011; 1373: 101 ‐ 109.
dc.identifier.citedreferenceGreenway FL. Physiological adaptations to weight loss and factors favouring weight regain. Int J Obes (Lond) 2015; 39: 1188 ‐ 1196.
dc.identifier.citedreferenceSpeakman JR. Obesity: the integrated roles of environment and genetics. J Nutr 2004; 134: 2090S ‐ 2105S.
dc.identifier.citedreferenceGoldsmith R, Joanisse DR, Gallagher D, et al. Effects of experimental weight perturbation on skeletal muscle work efficiency, fuel utilization, and biochemistry in human subjects. Am J Physiol Regul Integr Comp Physiol 2010; 298: R79 ‐ R88.
dc.identifier.citedreferenceRosenbaum M, Goldsmith RL, Haddad F, et al. Triiodothyronine and leptin repletion in humans similarly reverse weight‐loss‐induced changes in skeletal muscle. Am J Physiol Endocrinol Metab 2018; 315: E771 ‐ E779.
dc.identifier.citedreferenceFisher‐Wellman KH, Davidson MT, Narowski TM, Lin CT, Koves TR, Muoio DM. Mitochondrial diagnostics: a multiplexed assay platform for comprehensive assessment of mitochondrial energy fluxes. Cell Rep 2018; 24: 3593 ‐ 3606.e10.
dc.identifier.citedreferenceSoftic S, Meyer JG, Wang GX, et al. Dietary sugars alter hepatic fatty acid oxidation via transcriptional and post‐translational modifications of mitochondrial proteins. Cell Metab 2019; 30: 735 ‐ 753.e4.
dc.identifier.citedreferenceCarrer A, Parris JL, Trefely S, et al. Impact of a high‐fat diet on tissue Acyl‐CoA and histone acetylation levels. J Biol Chem 2017; 292: 3312 ‐ 3322.
dc.identifier.citedreferenceLantier L, Williams AS, Williams IM, et al. SIRT3 is crucial for maintaining skeletal muscle insulin action and protects against severe insulin resistance in high‐fat‐fed mice. Diabetes 2015; 64: 3081 ‐ 3092.
dc.identifier.citedreferenceFisher‐Wellman KH, Draper JA, Davidson MT, et al. Respiratory phenomics across multiple models of protein hyperacylation in cardiac mitochondria reveals a marginal impact on bioenergetics. Cell Rep 2019; 26: 1557 ‐ 1572.e8.
dc.identifier.citedreferenceLocke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 2015; 518: 197 ‐ 206.
dc.identifier.citedreferenceYengo L, Sidorenko J, Kemper KE, et al. Meta‐analysis of genome‐wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum Mol Genet 2018; 27: 3641 ‐ 3649.
dc.identifier.citedreferenceAkiyama M, Okada Y, Kanai M, et al. Genome‐wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet 2017; 49: 1458 ‐ 1467.
dc.identifier.citedreferenceRiveros‐McKay F, Mistry V, Bounds R, et al. Genetic architecture of human thinness compared to severe obesity. PLoS Genet 2019; 15: e1007603. doi: 10.1371/journal.pgen.1007603
dc.identifier.citedreferenceBulik CM, Allison DB. The genetic epidemiology of thinness. Obes Rev 2001; 2: 107 ‐ 115.
dc.identifier.citedreferenceOrthofer M, Valsesia A, Mägi R, et al. Identification of ALK in thinness. Cell 2020; 181: 1246 ‐ 1262.e22.
dc.identifier.citedreferenceElks CE, den Hoed M, Hua Zhao J, et al. Variability in the heritability of body mass index: a systematic review and meta‐regression. Front Endocrinol (Lausanne) 2012; 3: 29.
dc.identifier.citedreferenceWhitaker KL, Jarvis MJ, Boniface D, Wardle J. The intergenerational transmission of thinness. Arch Pediatr Adolesc Med 2011; 165: 900 ‐ 905.
dc.identifier.citedreferenceBouchard C, Tremblay A, Després J‐P, et al. The response to exercise with constant energy intake in identical twins. Obes Res 1994; 2: 400 ‐ 410.
dc.identifier.citedreferenceHainer V, Stunkard AJ, Kunešová M, Parízková J, Štich V, Allison DB. Intrapair resemblance in very low calorie diet‐induced weight loss in female obese identical twins. Int J Obes Relat Metab Disord 2000; 24: 1051 ‐ 1057.
dc.identifier.citedreferenceHatoum IJ, Greenawalt DM, Cotsapas C, Reitman ML, Daly MJ, Kaplan LM. Heritability of the weight loss response to gastric bypass surgery. J Clin Endocrinol Metab 2011; 96: E1630 ‐ E1633.
dc.identifier.citedreferenceFinucane HK, Reshef YA, Anttila V, et al. Heritability enrichment of specifically expressed genes identifies disease‐relevant tissues and cell types. Nat Genet 2018; 50: 621 ‐ 629.
dc.identifier.citedreferenceNdiaye FK, Huyvaert M, Ortalli A, et al. The expression of genes in top obesity‐associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward. Int J Obes (Lond) 2020; 44: 539 ‐ 543.
dc.identifier.citedreferenceTimshel PN, Thompson JJ, Pers TH. Genetic mapping of etiologic brain cell types for obesity. Elife 2020; 9: e55851. doi: 10.7554/eLife.55851
dc.identifier.citedreferenceBerndt SI, Gustafsson S, Mägi R, et al. Genome‐wide meta‐analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet 2013; 45: 501 ‐ 512.
dc.identifier.citedreferenceRobinson MR, English G, Moser G, et al. Genotype‐covariate interaction effects and the heritability of adult body mass index. Nat Genet 2017; 49: 1174 ‐ 1181.
dc.identifier.citedreferenceBiederer T, Sara Y, Mozhayeva M, et al. SynCAM, a synaptic adhesion molecule that drives synapse assembly. Science 2002; 297: 1525 ‐ 1531.
dc.identifier.citedreferenceYan X, Wang Z, Schmidt V, et al. Cadm2 regulates body weight and energy homeostasis in mice. Mol Metab 2018; 8: 180 ‐ 188.
dc.identifier.citedreferenceDelahanty LM, Pan Q, Jablonski KA, et al. Genetic predictors of weight loss and weight regain after intensive lifestyle modification, metformin treatment, or standard care in the Diabetes Prevention Program. Diabetes Care 2012; 35: 363 ‐ 366.
dc.identifier.citedreferencePapandonatos GD, Pan Q, Pajewski NM, et al. Genetic predisposition to weight loss and regain with lifestyle intervention: analyses from the Diabetes Prevention Program and the Look AHEAD randomized controlled trials. Diabetes 2015; 64: 4312 ‐ 4321.
dc.identifier.citedreferenceBray GA, Krauss RM, Sacks FM, Qi L. Lessons learned from the POUNDS Lost study: genetic, metabolic, and behavioral factors affecting changes in body weight, body composition, and cardiometabolic risk. Curr Obes Rep 2019; 8: 262 ‐ 283.
dc.identifier.citedreferenceLarsen LH, Ängquist L, Vimaleswaran KS, et al. Analyses of single nucleotide polymorphisms in selected nutrient‐sensitive genes in weight‐regain prevention: the DIOGENES study. Am J Clin Nutr 2012; 95: 1254 ‐ 1260.
dc.identifier.citedreferenceSarzynski MA, Jacobson P, Rankinen T, et al. Associations of markers in 11 obesity candidate genes with maximal weight loss and weight regain in the SOS bariatric surgery cases. Int J Obes (Lond) 2011; 35: 676 ‐ 683.
dc.identifier.citedreferenceHinney A, Wolters B, Pütter C, et al. No impact of obesity susceptibility loci on weight regain after a lifestyle intervention in overweight children. J Pediatr Endocrinol Metab 2013; 26: 1209 ‐ 1213.
dc.identifier.citedreferenceMcCaffery JM. Precision behavioral medicine: implications of genetic and genomic discoveries for behavioral weight loss treatment. Am Psychol 2018; 73: 1045 ‐ 1055.
dc.identifier.citedreferenceZimmer L, Luxen A. PET radiotracers for molecular imaging in the brain: past, present and future. Neuroimage 2012; 61: 363 ‐ 370.
dc.identifier.citedreferenceBuonocore MH, Maddock RJ. Magnetic resonance spectroscopy of the brain: a review of physical principles and technical methods. Rev Neurosci 2015; 26: 609 ‐ 632.
dc.identifier.citedreferenceLaBar KS, Gitelman DR, Parrish TB, Kim YH, Nobre AC, Mesulam MM. Hunger selectively modulates corticolimbic activation to food stimuli in humans. Behav Neurosci 2001; 115: 493 ‐ 500.
dc.identifier.citedreferenceGautier JF, Del Parigi A, Chen K, et al. Effect of satiation on brain activity in obese and lean women. Obes Res 2001; 9: 676 ‐ 684.
dc.identifier.citedreferencePoldrack RA, Baker CI, Durnez J, et al. Scanning the horizon: towards transparent and reproducible neuroimaging research. Nat Rev Neurosci 2017; 18: 115 ‐ 126.
dc.identifier.citedreferenceBotvinik‐Nezer R, Holzmeister F, Camerer CF, et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020; 582: 84 ‐ 88.
dc.identifier.citedreferenceGorgolewski KJ, Poldrack RA. A practical guide for improving transparency and reproducibility in neuroimaging research. PLoS Biol 2016; 14: e1002506. doi: 10.1371/journal.pbio.1002506
dc.identifier.citedreferenceNichols TE, Das S, Eickhoff SB, et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat Neurosci 2017; 20: 299 ‐ 303.
dc.identifier.citedreferenceKillgore WD, Young AD, Femia LA, Bogorodzki P, Rogowska J, Yurgelun‐Todd DA. Cortical and limbic activation during viewing of high‐ versus low‐calorie foods. Neuroimage 2003; 19: 1381 ‐ 1394.
dc.identifier.citedreferenceSchur EA, Kleinhans NM, Goldberg J, Buchwald D, Schwartz MW, Maravilla K. Activation in brain energy regulation and reward centers by food cues varies with choice of visual stimulus. Int J Obes Relat Metab Disord 2009; 33: 653 ‐ 661.
dc.identifier.citedreferencevan der Laan LN, de Ridder DT, Viergever MA, Smeets PA. The first taste is always with the eyes: a meta‐analysis on the neural correlates of processing visual food cues. Neuroimage 2011; 55: 296 ‐ 303.
dc.identifier.citedreferencePursey KM, Stanwell P, Callister RJ, Brain K, Collins CE, Burrows TL. Neural responses to visual food cues according to weight status: a systematic review of functional magnetic resonance imaging studies. Front Nutr 2014; 1: 7.
dc.identifier.citedreferenceHan JE, Boachie N, Garcia‐Garcia I, Michaud A, Dagher A. Neural correlates of dietary self‐control in healthy adults: a meta‐analysis of functional brain imaging studies. Physiol Behav 2018; 192: 98 ‐ 108.
dc.identifier.citedreferenceGoldstone AP, de Hernandez CGP, Beaver JD, et al. Fasting biases brain reward systems towards high‐calorie foods. Eur J Neurosci 2009; 30: 1625 ‐ 1635.
dc.identifier.citedreferenceMehta S, Melhorn SJ, Smeraglio A, et al. Regional brain response to visual food cues is a marker of satiety that predicts food choice. Am J Clin Nutr 2012; 96: 989 ‐ 999.
dc.identifier.citedreferencePetrovich GD, Setlow B, Holland PC, Gallagher M. Amygdalo‐hypothalamic circuit allows learned cues to override satiety and promote eating. J Neurosci 2002; 22: 8748 ‐ 8753.
dc.identifier.citedreferenceMalik S, McGlone F, Bedrossian D, Dagher A. Ghrelin modulates brain activity in areas that control appetitive behavior. Cell Metab 2008; 7: 400 ‐ 409.
dc.identifier.citedreferenceFarooqi IS, Bullmore E, Keogh J, Gillard J, O’Rahilly S, Fletcher PC. Leptin regulates striatal regions and human eating behavior. Science 2007; 317: 1355. doi: 10.1126/science.1144599
dc.identifier.citedreferenceBaicy K, London ED, Monterosso J, et al. Leptin replacement alters brain response to food cues in genetically leptin‐deficient adults. Proc Natl Acad Sci USA 2007; 104: 18276 ‐ 18279.
dc.identifier.citedreferenceDe Silva A, Salem V, Long CJ, et al. The gut hormones PYY 3–36 and GLP‐1 7–36 amide reduce food intake and modulate brain activity in appetite centers in humans. Cell Metab 2011; 14: 700 ‐ 706.
dc.identifier.citedreferenceTen Kulve JS, Veltman DJ, van Bloemendaal L, et al. Liraglutide reduces CNS activation in response to visual food cues only after short‐term treatment in patients with type 2 diabetes. Diabetes Care 2016; 39: 214 ‐ 221.
dc.identifier.citedreferenceGuthoff M, Grichisch Y, Canova C, et al. Insulin modulates food‐related activity in the central nervous system. J Clin Endocrinol Metab 2010; 95: 748 ‐ 755.
dc.identifier.citedreferenceLe DS, Pannacciulli N, Chen K, et al. Less activation in the left dorsolateral prefrontal cortex in the reanalysis of the response to a meal in obese than in lean women and its association with successful weight loss. Am J Clin Nutr 2007; 86: 573 ‐ 579.
dc.identifier.citedreferenceDelParigi A, Chen K, Salbe AD, et al. Successful dieters have increased neural activity in cortical areas involved in the control of behavior. Int J Obes 2007; 31: 440 ‐ 448.
dc.identifier.citedreferenceMcCaffery JM, Haley AP, Sweet LH, et al. Differential functional magnetic resonance imaging response to food pictures in successful weight‐loss maintainers relative to normal‐weight and obese controls. Am J Clin Nutr 2009; 90: 928 ‐ 934.
dc.identifier.citedreferenceHolsen LM, Davidson P, Cerit H, et al. Neural predictors of 12‐month weight loss outcomes following bariatric surgery. Int J Obes 2018; 42: 785 ‐ 793.
dc.identifier.citedreferenceOchner CN, Stice E, Hutchins E, et al. Relation between changes in neural responsivity and reductions in desire to eat high‐calorie foods following gastric bypass surgery. Neuroscience 2012; 209: 128 ‐ 135.
dc.identifier.citedreferenceScholtz S, Miras AD, Chhina N, et al. Obese patients after gastric bypass surgery have lower brain‐hedonic responses to food than after gastric banding. Gut 2014; 63: 891 ‐ 902.
dc.identifier.citedreferenceFaulconbridge LF, Ruparel K, Loughead J, et al. Changes in neural responsivity to highly palatable foods following Roux‐en‐Y gastric bypass, sleeve gastrectomy, or weight stability: an fMRI study. Obesity (Silver Spring) 2016; 24: 1054 ‐ 1060.
dc.identifier.citedreferenceTen Kulve JS, Veltman DJ, Gerdes VEA, et al. Elevated postoperative endogenous GLP‐1 levels mediate effects of Roux‐en‐Y gastric bypass on neural responsivity to food cues. Diabetes Care 2017; 40: 1522 ‐ 1529.
dc.identifier.citedreferenceOchner CN, Kwok Y, Conceicao E, et al. Selective reduction in neural responses to high calorie foods following gastric bypass surgery. Ann Surg 2011; 253: 502 ‐ 507.
dc.identifier.citedreferenceZoon HFA, de Bruijn SEM, Jager G, et al. Altered neural inhibition responses to food cues after Roux‐en‐Y gastric bypass. Biol Psychol 2018; 137: 34 ‐ 41.
dc.identifier.citedreferenceRosenbaum M, Sy M, Pavlovich K, Leibel RL, Hirsch J. Leptin reverses weight loss‐induced changes in regional neural activity responses to visual food stimuli. J Clin Invest 2008; 118: 2583 ‐ 2591.
dc.identifier.citedreferenceNeseliler S, Hu W, Larcher K, et al. Neurocognitive and hormonal correlates of voluntary weight loss in humans. Cell Metab 2019; 29: 39 ‐ 49.e34.
dc.identifier.citedreferenceMurdaugh DL, Cox JE, Cook EW 3rd, Weller RE. fMRI reactivity to high‐calorie food pictures predicts short‐ and long‐term outcome in a weight‐loss program. Neuroimage 2012; 59: 2709 ‐ 2721.
dc.identifier.citedreferenceDrummen M, Dorenbos E, Vreugdenhil ACE, et al. Associations of brain reactivity to food cues with weight loss, protein intake and dietary restraint during the PREVIEW intervention. Nutrients 2018; 10: 1771. doi: 10.3390/nu10111771
dc.identifier.citedreferenceGlover GH, Mueller BA, Turner JA, et al. Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies. J Magn Reson Imaging 2012; 36: 39 ‐ 54.
dc.identifier.citedreferenceCharbonnier L, van Meer F, van der Laan LN, Viergever MA, Smeets PAM. Standardized food images: a photographing protocol and image database. Appetite 2016; 96: 166 ‐ 173.
dc.identifier.citedreferenceFrank TC, Kim GL, Krzemien A, Van Vugt DA. Effect of menstrual cycle phase on corticolimbic brain activation by visual food cues. Brain Res 2010; 1363: 81 ‐ 92.
dc.identifier.citedreferenceMelhorn SJ, Mehta S, Kratz M, et al. Brain regulation of appetite in twins. Am J Clin Nutr 2016; 103: 314 ‐ 322.
dc.identifier.citedreferenceSchur E, Carnell S. What twin studies tell us about brain responses to food cues. Curr Obes Rep 2017; 6: 371 ‐ 379.
dc.identifier.citedreferenceDamoiseaux JS, Rombouts SA, Barkhof F, et al. Consistent resting‐state networks across healthy subjects. Proc Natl Acad Sci USA 2006; 103: 13848 ‐ 13853.
dc.identifier.citedreferencePower JD, Cohen AL, Nelson SM, et al. Functional network organization of the human brain. Neuron 2011; 72: 665 ‐ 678.
dc.identifier.citedreferenceShulman GL, Fiez JA, Corbetta M, et al. Common blood flow changes across visual tasks: II. Decreases in cerebral cortex. J Cogn Neurosci 1997; 9: 648 ‐ 663.
dc.identifier.citedreferenceRaichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage 2007; 37: 1083 ‐ 1090. Discussion 1097‐1089.
dc.identifier.citedreferenceSeeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large‐scale human brain networks. Neuron 2009; 62: 42 ‐ 52.
dc.identifier.citedreferenceSewaybricker LE, Melhorn SJ, Askren MK, et al. Salience network connectivity is reduced by a meal and influenced by genetic background and hypothalamic gliosis. Int J Obes (Lond) 2020; 44: 167 ‐ 177.
dc.identifier.citedreferenceSeeley WW, Menon V, Schatzberg AF, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 2007; 27: 2349 ‐ 2356.
dc.identifier.citedreferenceMenon V, Uddin LQ. Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct 2010; 214: 655 ‐ 667.
dc.identifier.citedreferenceLips MA, Wijngaarden MA, van der Grond J, et al. Resting‐state functional connectivity of brain regions involved in cognitive control, motivation, and reward is enhanced in obese females. Am J Clin Nutr 2014; 100: 524 ‐ 531.
dc.identifier.citedreferenceRyan JP, Karim HT, Aizenstein HJ, Helbling NL, Toledo FGS. Insulin sensitivity predicts brain network connectivity following a meal. Neuroimage 2018; 171: 268 ‐ 276.
dc.identifier.citedreferencePaolini BM, Laurienti PJ, Norris J, Rejeski WJ. Meal replacement: calming the hot‐state brain network of appetite. Front Psychol 2014; 5: 249.
dc.identifier.citedreferenceSmith SM, Beckmann CF, Andersson J, et al. Resting‐state fMRI in the human connectome project. Neuroimage 2013; 80: 144 ‐ 168.
dc.identifier.citedreferenceBirn RM, Molloy EK, Patriat R, et al. The effect of scan length on the reliability of resting‐state fMRI connectivity estimates. Neuroimage 2013; 83: 550 ‐ 558.
dc.identifier.citedreferenceBohon C, Geliebter A. Change in brain volume and cortical thickness after behavioral and surgical weight loss intervention. Neuroimage Clin 2019; 21: 101640. doi: 10.1016/j.nicl.2018.101640
dc.identifier.citedreferenceHaltia LT, Viljanen A, Parkkola R, et al. Brain white matter expansion in human obesity and the recovering effect of dieting. J Clin Endocrinol Metab 2007; 92: 3278 ‐ 3284.
dc.identifier.citedreferenceHonea RA, Szabo‐Reed AN, Lepping RJ, et al. Voxel‐based morphometry reveals brain gray matter volume changes in successful dieters. Obesity (Silver Spring) 2016; 24: 1842 ‐ 1848.
dc.identifier.citedreferencevan de Sande‐Lee S, Melhorn SJ, Rachid B, et al. Radiologic evidence that hypothalamic gliosis is improved after bariatric surgery in obese women with type 2 diabetes. Int J Obes (Lond) 2020; 44: 178 ‐ 185.
dc.identifier.citedreferenceThaler JP, Yi CX, Schur EA, et al. Obesity is associated with hypothalamic injury in rodents and humans. J Clin Invest 2012; 122: 153 ‐ 162.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
oby23101.pdf
Size:
477.9KB
Format:
PDF
View/Open
Name:
oby23101_am.pdf
Size:
511.0KB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.