TY - JOUR
T1 - Metabolomic approach to human brain spectroscopy identifies associations between clinical features and the frontal lobe metabolome in multiple sclerosis
AU - Vingara, Lisa K.
AU - Yu, Hui Jing
AU - Wagshul, Mark E.
AU - Serafin, Dana
AU - Christodoulou, Christopher
AU - Pelczer, István
AU - Krupp, Lauren B.
AU - Maletić-Savatić, Mirjana
N1 - Funding Information:
The authors wish to thank Y. Patel, V. Bhise, and D. Greenblatt for help with the subject recruitment. We also thank Vicky Brandt, William Rooney, and Dennis Bourdette for comments and expert revision of the paper. This work was supported by the National Library of Medicine (grant # 5-T15-LM 7088-20 ) (L.K.V), the Lourie Foundation Incorporated , National Multiple Sclerosis Society (grant # RG4030A2/1 ), National Center for Research Resources (grant # 5-MO1-RR-10710 ) (L.B.K.), and by the NIH Intellectual and Developmental Disabilities Research Grant ( P30HD024064 ), Dana Foundation , and McKnight Endowment for Science (M.M.-S.).
PY - 2013/11/15
Y1 - 2013/11/15
N2 - Proton magnetic resonance spectroscopy (1H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo 1H-MRS from frontal lobe white matter of 27 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials.
AB - Proton magnetic resonance spectroscopy (1H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo 1H-MRS from frontal lobe white matter of 27 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials.
KW - Magnetic resonance spectroscopy (MRS)
KW - Metabolomics
KW - Multivariate statistics
KW - Relapsing-remitting multiple sclerosis
UR - http://www.scopus.com/inward/record.url?scp=84880034564&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880034564&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2013.05.125
DO - 10.1016/j.neuroimage.2013.05.125
M3 - Article
C2 - 23751863
AN - SCOPUS:84880034564
SN - 1053-8119
VL - 82
SP - 586
EP - 594
JO - NeuroImage
JF - NeuroImage
ER -