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Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach

Published online by Cambridge University Press:  20 May 2015

L. Lavagnino ,
F. Amianto ,
B. Mwangi ,
F. D'Agata ,
A. Spalatro ,
G. B. Zunta-Soares ,
G. Abbate Daga ,
P. Mortara ,
S. Fassino  and
J. C. Soares
L. Lavagnino*
Affiliation:
UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
F. Amianto
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
B. Mwangi
Affiliation:
UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
F. D'Agata
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
A. Spalatro
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
G. B. Zunta-Soares
Affiliation:
UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
G. Abbate Daga
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
P. Mortara
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
S. Fassino
Affiliation:
Department of Neuroscience, AOU San Giovanni Battista, Turin, Italy
J. C. Soares
Affiliation:
UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
*
*Address for correspondence: L. Lavagnino, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, 1941 East Road, Houston, TX 77054, USA. (Email: [email protected])
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Abstract

Background

There are currently no neuroanatomical biomarkers of anorexia nervosa (AN) available to make clinical inferences at an individual subject level. We present results of a multivariate machine learning (ML) approach utilizing structural neuroanatomical scan data to differentiate AN patients from matched healthy controls at an individual subject level.

Method

Structural neuroimaging scans were acquired from 15 female patients with AN (age = 20, s.d. = 4 years) and 15 demographically matched female controls (age = 22, s.d. = 3 years). Neuroanatomical volumes were extracted using the FreeSurfer software and input into the Least Absolute Shrinkage and Selection Operator (LASSO) multivariate ML algorithm. LASSO was ‘trained’ to identify ‘novel’ individual subjects as either AN patients or healthy controls. Furthermore, the model estimated the probability that an individual subject belonged to the AN group based on an individual scan.

Results

The model correctly predicted 25 out of 30 subjects, translating into 83.3% accuracy (sensitivity 86.7%, specificity 80.0%) (p < 0.001; χ2 test). Six neuroanatomical regions (cerebellum white matter, choroid plexus, putamen, accumbens, the diencephalon and the third ventricle) were found to be relevant in distinguishing individual AN patients from healthy controls. The predicted probabilities showed a linear relationship with drive for thinness clinical scores (r = 0.52, p < 0.005) and with body mass index (BMI) (r = −0.45, p = 0.01).

Conclusions

The model achieved a good predictive accuracy and drive for thinness showed a strong neuroanatomical signature. These results indicate that neuroimaging scans coupled with ML techniques have the potential to provide information at an individual subject level that might be relevant to clinical outcomes.

Keywords

Anorexiadrive for thinnessmachine learningmagnetic resonance imaging
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 13 , October 2015 , pp. 2805 - 2812
Copyright
Copyright © Cambridge University Press 2015 

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References

Amianto, F, Caroppo, P, D'Agata, F, Spalatro, A, Lavagnino, L, Caglio, M, Righi, D, Bergui, M, Abbate Daga, G, Rigardetto, R, Mortara, P, Fassino, S (2013a). Brain volumetric abnormalities in patients with anorexia and bulimia nervosa: a voxel-based morphometry study. Psychiatry Research 213, 210–216.Google Scholar
Amianto, F, D'Agata, F, Lavagnino, L, Caroppo, P, Abbate-Daga, G, Righi, D, Scarone, S, Bergui, M, Mortara, P, Fassino, S (2013b). Intrinsic connectivity networks within cerebellum and beyond in eating disorders. Cerebellum 12, 623–631.CrossRefGoogle ScholarPubMed
Boghi, A, Sterpone, S, Sales, S, D'Agata, F, Bradac, GB, Zullo, G, Munno, D (2011). In vivo evidence of global and focal brain alterations in anorexia nervosa. Psychiatry Research 192, 154–159.Google Scholar
Bomba, M, Riva, A, Veggo, F, Grimaldi, M, Morzenti, S, Neri, F, Nacinovich, R (2013). Impact of speed and magnitude of weight loss on the development of brain trophic changes in adolescents with anorexia nervosa: a case control study. Italian Journal of Pediatrics 39, 14.CrossRefGoogle ScholarPubMed
Brooks, SJ, Barker, GJ, O'Daly, OG, Brammer, M, Williams, SC, Benedict, C, Schioth, HB, Treasure, J, Campbell, IC (2011). Restraint of appetite and reduced regional brain volumes in anorexia nervosa: a voxel-based morphometric study. BMC Psychiatry 11, 179.CrossRefGoogle ScholarPubMed
Bruch, H (1973). Eating Disorders: Obesity, Anorexia Nervosa and the Person Within. Basic Books: New York.Google Scholar
Bunea, F, She, Y, Ombao, H, Gongvatana, A, Devlin, K, Cohen, R (2011). Penalized least squares regression methods and applications to neuroimaging. NeuroImage 55, 1519–1527.Google Scholar
Cardinale, F, Chinnici, G, Bramerio, M, Mai, R, Sartori, I, Cossu, M, Lo Russo, G, Castana, L, Colombo, N, Caborni, C, De Momi, E, Ferrigno, G (2014). Validation of FreeSurfer-estimated brain cortical thickness: comparison with histologic measurements. Neuroinformatics 12, 535–542.CrossRefGoogle ScholarPubMed
Castro-Fornieles, J, Bargallo, N, Lazaro, L, Andres, S, Falcon, C, Plana, MT, Junqué, C (2009). A cross-sectional and follow-up voxel-based morphometric MRI study in adolescent anorexia nervosa. Journal of Psychiatric Research 43, 331–340.Google Scholar
Cuthbert, BN (2014). The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry 13, 28–35.Google Scholar
Desikan, RS, Ségonne, F, Fischl, B, Quinn, BT, Dickerson, BC, Blacker, D, Buckner, RL, Dale, AM, Maguire, RP, Hyman, BT, Albert, MS, Killiany, RJ (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31, 968–980.Google Scholar
Eddy, KT, Rauch, SL (2011). Neuroimaging in eating disorders: coming of age. American Journal of Psychiatry 168, 1139–1141.Google Scholar
Fairburn, CG, Harrison, PJ (2003). Eating disorders. Lancet 361, 407–416.Google Scholar
Fassino, S, Abbate Daga, G (2013). Resistance to treatment in eating disorders: a critical challenge. BMC Psychiatry 13, 282.Google Scholar
Fischl, B (2012). FreeSurfer. NeuroImage 62, 774–781.Google Scholar
Fischl, B, Stevens, AA, Rajendran, N, Yeo, BT, Greve, DN, Van Leemput, K, Polimeni, JR, Kakunoori, S, Buckner, RL, Pacheco, J, Salat, DH, Melcher, J, Frosch, MP, Hyman, BT, Grant, PE, Rosen, BR, van der Kouwe, AJ, Wiggins, GC, Wald, LL, Augustinack, JC (2009). Predicting the location of entorhinal cortex from MRI. NeuroImage 47, 8–17.Google Scholar
Fischl, B, van der Kouwe, A, Destrieux, C, Halgren, E, Ségonne, F, Salat, DH, Busa, E, Seidman, LJ, Goldstein, J, Kennedy, D, Caviness, V, Makris, N, Rosen, B, Dale, AM (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex 14, 11–22.Google Scholar
Fonville, L, Giampietro, V, Williams, SC, Simmons, A, Tchanturia, K (2014). Alterations in brain structure in adults with anorexia nervosa and the impact of illness duration. Psychological Medicine 44, 1965–1975.Google Scholar
Frank, GK (2013). Altered brain reward circuits in eating disorders: chicken or egg? Current Psychiatry Reports 15, 396.Google Scholar
Frank, GK, Shott, ME, Hagman, JO, Mittal, VA (2013). Alterations in brain structures related to taste reward circuitry in ill and recovered anorexia nervosa and in bulimia nervosa. American Journal of Psychiatry 170, 1152–1160.CrossRefGoogle ScholarPubMed
Friederich, HC, Walther, S, Bendszus, M, Biller, A, Thomann, P, Zeigermann, S, Katus, T, Brunner, R, Zastrow, A, Herzog, W (2012). Grey matter abnormalities within cortico-limbic-striatal circuits in acute and weight-restored anorexia nervosa patients. NeuroImage 59, 1106–1113.Google Scholar
Friedman, J, Hastie, T, Tibshirani, R (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software 33, 1–22.Google Scholar
Fu, CH, Costafreda, SG (2013). Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift. Canadian Journal of Psychiatry 58, 499–508.CrossRefGoogle ScholarPubMed
Fuglset, TS, Endestad, T, Landrø, NI, Rø, O (2015). Brain structure alterations associated with weight changes in young females with anorexia nervosa: a case series. Neurocase 21, 169–177.CrossRefGoogle ScholarPubMed
Garner, DM (1991). Eating Disorder Inventory-2 Professional Manual. Psychological Assessment Resources: Odessa, FL.Google Scholar
Gaudio, S, Nocchi, F, Franchin, T, Genovese, E, Cannata, V, Longo, D, Fariello, G (2011). Gray matter decrease distribution in the early stages of anorexia nervosa restrictive type in adolescents. Psychiatry Research 191, 24–30.Google Scholar
Ingalhalikar, M, Parker, D, Bloy, L, Roberts, TP, Verma, R (2011). Diffusion based abnormality markers of pathology: toward learned diagnostic prediction of ASD. NeuroImage 57, 918–927.CrossRefGoogle ScholarPubMed
Johnston, BA, Mwangi, B, Matthews, K, Coghill, D, Konrad, K, Steele, JD (2014). Brainstem abnormalities in attention deficit hyperactivity disorder support high accuracy individual diagnostic classification. Human Brain Mapping 35, 5179–5189.Google Scholar
Johnston, BA, Mwangi, B, Matthews, K, Coghill, D, Steele, JD (2013). Predictive classification of individual magnetic resonance imaging scans from children and adolescents. European Child and Adolescent Psychiatry 22, 733–744.CrossRefGoogle ScholarPubMed
Joos, A, Kloppel, S, Hartmann, A, Glauche, V, Tuscher, O, Perlov, E, Saum, B, Freyer, T, Zeek, A, Tebartz van Elst, L (2010). Voxel-based morphometry in eating disorders: correlation of psychopathology with grey matter volume. Psychiatry Research 182, 146–151.Google Scholar
Katzman, DK, Lambe, EK, Mikulis, DJ, Ridgley, JN, Goldbloom, DS, Zipursky, RB (1996). Cerebral gray matter and white matter volume deficits in adolescent girls with anorexia nervosa. Journal of Pediatrics 129, 794–803.Google Scholar
Kaye, WH, Wierenga, CE, Bailer, UF, Simmons, AN, Bischoff-Grethe, A (2013). Nothing tastes as good as skinny feels: the neurobiology of anorexia nervosa. Trends in Neuroscience 36, 110–120.Google Scholar
Kazlouski, D, Rollin, MD, Tregellas, J, Shott, ME, Jappe, LM, Hagman, JO, Pryor, T, Yang, TT, Frank, GK (2011). Altered fimbria-fornix white matter integrity in anorexia nervosa predicts harm avoidance. Psychiatry Research 192, 109–116.Google Scholar
King, JA, Geisler, D, Ritschel, F, Schober, I, Seidel, M, Roschinski, B, Soltwedel, L, Zwipp, J, Pfuhl, G, Marxen, M, Roessner, V, Ehrlich, S (2015). Global cortical thinning in acute anorexia nervosa normalizes following long-term weight restoration. Biological Psychiatry 77, 624–632.Google Scholar
Muhlau, M, Gaser, C, Ilg, R, Conrad, B, Leibl, C, Cebulla, MH, Backmund, H, Gerlinghoff, M, Lommer, P, Schnebel, A, Wohlschläger, AM, Zimmer, C, Nunnemann, S (2007). Gray matter decrease of the anterior cingulate cortex in anorexia nervosa. American Journal of Psychiatry 164, 1850–1857.Google Scholar
Murphy, R, Straebler, S, Cooper, Z, Fairburn, CG (2010). Cognitive behavioral therapy for eating disorders. Psychiatric Clinics of North America 33, 611–627.Google Scholar
Mwangi, B, Ebmeier, KP, Matthews, K, Steele, JD (2012). Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder. Brain 135, 1508–1521.Google Scholar
Mwangi, B, Spiker, D, Zunta-Soares, GB, Soares, JC (2014a). Prediction of pediatric bipolar disorder using neuroanatomical signatures of the amygdala. Bipolar Disorders 16, 713–721.Google Scholar
Mwangi, B, Tian, TS, Soares, JC (2014b). A review of feature reduction techniques in neuroimaging. Neuroinformatics 12, 229–244.Google Scholar
Nagahara, Y, Nakamae, T, Nishizawa, S, Mizuhara, Y, Moritoki, Y, Wada, Y, Sakai, Y, Yamashita, T, Narumoto, J, Miyata, J, Yamada, K, Fukui, K (2014). A tract-based spatial statistics study in anorexia nervosa: abnormality in the fornix and the cerebellum. Progress in Neuropsychopharmacology and Biological Psychiatry 51, 72–77.Google Scholar
Olatunji, BO, Broman-Fulks, JJ, Ciesielski, BG, Zawilinski, LL, Shewmaker, S, Wall, DA (2012). Taxometric investigation of the latent structure of eating disorders. Psychiatry Research 197, 97–102.Google Scholar
Roberto, CA, Mayer, LE, Brickman, AM, Barnes, A, Muraskin, J, Yeung, LK, Steffener, J, Sy, M, Hirsch, J, Stern, Y, Walsh, BT (2011). Brain tissue volume changes following weight gain in adults with anorexia nervosa. International Journal of Eating Disorders 44, 406–411.Google Scholar
Rosas, HD, Lee, SY, Bender, AC, Zaleta, AK, Vangel, M, Yu, P, Fischl, B, Pappu, V, Onorato, C, Cha, JH, Salat, DH, Hersch, SM (2010). Altered white matter microstructure in the corpus callosum in Huntington's disease: implications for cortical “disconnection”. NeuroImage 49, 2995–3004.Google Scholar
Russell, GFM (1970). Anorexia nervosa: its identity as an illness and its treatment. In Modern Trends in Psychological Medicine (ed. Price, J. H.), pp. 131–164. Butterworths: London.Google Scholar
Sathyanesan, M, Girgenti, MJ, Banasr, M, Stone, K, Bruce, C, Guilchicek, E, Wilczak-Havill, K, Nairn, A, Williams, K, Sass, S, Duman, JG, Newton, SS (2012). A molecular characterization of the choroid plexus and stress-induced gene regulation. Translational Psychiatry 2, e139.Google Scholar
Schmahmann, JD, Sherman, JC (1998). The cerebellar cognitive affective syndrome. Brain 121, 561–579.Google Scholar
Schmidt, U, Campbell, IC (2013). Treatment of eating disorders can not remain ‘brainless’: the case for brain-directed treatments. European Eating Disorders Reviews 21, 425–427.Google Scholar
Steinhausen, HC (2002). The outcome of anorexia nervosa in the 20th century. American Journal of Psychiatry 159, 1284–1293.Google Scholar
Suchan, B, Busch, M, Schulte, D, Gronemeyer, D, Herpertz, S, Vocks, S (2010). Reduction of gray matter density in the extrastriate body area in women with anorexia nervosa. Behavioural Brain Research 206, 63–67.Google Scholar
Sullivan, PF (1995). Mortality in anorexia nervosa. American Journal of Psychiatry 152, 1073–1074.Google Scholar
Swayze, VW II, Andersen, AE, Andreasen, NC, Arndt, S, Sato, Y, Ziebell, S (2003). Brain tissue volume segmentation in patients with anorexia nervosa before and after weight normalization. International Journal of Eating Disorders 33, 33–44.Google Scholar
Tibshirani, R (1996). Regression shrinkage and selection via the LASSO. Journal of the Royal Statistical Society Series B (Methodology) 58, 267–288.Google Scholar
Tibshirani, R (2011). Regression shrinkage and selection via the LASSO: a retrospective. Journal of the Royal Statistical Society 73, 273–282.Google Scholar
Titova, OE, Hjorth, OC, Schioth, HB, Brooks, SJ (2013). Anorexia nervosa is linked to reduced brain structure in reward and somatosensory regions: a meta-analysis of VBM studies. BMC Psychiatry 13, 110.Google Scholar
Trivedi, P, Jiang, M, Tamvakopoulos, CC, Shen, X, Yu, H, Mock, S, Fenyk-Melody, J, Van der Ploeg, LH, Guan, XM (2003). Exploring the site of anorectic action of peripherally administered synthetic melanocortin peptide MT-II in rats. Brain Research 977, 221–230.CrossRefGoogle ScholarPubMed
Turner, CA, Thompson, RC, Bunney, WE, Schatzberg, AF, Barchas, JD, Myers, RM, Akil, H, Watson, SJ (2014). Altered choroid plexus gene expression in major depressive disorder. Frontiers of Human Neuroscience 8, 238.Google Scholar
Vansteelandt, K, Pieters, G, Vanderlinden, J, Probst, M (2010). Body dissatisfaction moderates weight curves in the inpatient treatment of anorexia nervosa. International Journal of Eating Disorders 43, 694–700.Google Scholar
Walsh, BT (2013). The enigmatic persistence of anorexia nervosa. American Journal of Psychiatry 170, 477–484.Google Scholar
Zhu, J-N, Wang, J-J (2008). The cerebellum in feeding control: possible function and mechanism. Cellular and Molecular Neurobiology 28, 469–478.Google Scholar
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