Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
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DOI:
10.1038/nm.4246
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发表时间:
2017-01
期刊:
影响因子:
82.9
通讯作者:
Liston C
中科院分区:
文献类型:
--
作者:
Drysdale AT;Grosenick L;Downar J;Dunlop K;Mansouri F;Meng Y;Fetcho RN;Zebley B;Oathes DJ;Etkin A;Schatzberg AF;Sudheimer K;Keller J;Mayberg HS;Gunning FM;Alexopoulos GS;Fox MD;Pascual-Leone A;Voss HU;Casey BJ;Dubin MJ;Liston C
Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample (n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes (‘biotypes’) defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82–93%) sensitivity and specificity for depression subtypes in multisite validation (n = 711) and out-of-sample replication (n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy (n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.
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DOI:
10.1176/appi.ajp.2015.14091200
发表时间:
2016-04-01
期刊:
The American journal of psychiatry
影响因子:
--
作者:
Clementz BA;Sweeney JA;Hamm JP;Ivleva EI;Ethridge LE;Pearlson GD;Keshavan MS;Tamminga CA
通讯作者:
Tamminga CA
影响因子:
10.6
作者:
Greicius, Michael D.;Flores, Benjamin H.;Schatzberg, Alan F.
通讯作者:
Schatzberg, Alan F.
DOI:
10.1126/science.aac9698
发表时间:
2016-01-01
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Ferenczi EA;Zalocusky KA;Liston C;Grosenick L;Warden MR;Amatya D;Katovich K;Mehta H;Patenaude B;Ramakrishnan C;Kalanithi P;Etkin A;Knutson B;Glover GH;Deisseroth K
通讯作者:
Deisseroth K
影响因子:
1.7
作者:
GEORGE, MS;WASSERMANN, EM;POST, RM
通讯作者:
POST, RM
影响因子:
10.6
作者:
Chen, Chi-Hua;Ridler, Khanum;Bullmore, Edward T.
通讯作者:
Bullmore, Edward T.