Genomic Analysis Yields Eight Distinct Types of Schizophrenia
The American Journal of Psychiatry
Abstract
Objective
The authors sought to demonstrate that schizophrenia is a heterogeneous group of heritable disorders caused by different genotypic networks that cause distinct clinical syndromes.
Method
In a large genome-wide association study of cases with schizophrenia and controls, the authors first identified sets of interacting single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (SNP sets) regardless of clinical status. Second, they examined the risk of schizophrenia for each SNP set and tested replicability in two independent samples. Third, they identified genotypic networks composed of SNP sets sharing SNPs or subjects. Fourth, they identified sets of distinct clinical features that cluster in particular cases (phenotypic sets or clinical syndromes) without regard for their genetic background. Fifth, they tested whether SNP sets were associated with distinct phenotypic sets in a replicable manner across the three studies.
Results
The authors identified 42 SNP sets associated with a 70% or greater risk of schizophrenia, and confirmed 34 (81%) or more with similar high risk of schizophrenia in two independent samples. Seventeen networks of SNP sets did not share any SNP or subject. These disjoint genotypic networks were associated with distinct gene products and clinical syndromes (i.e., the schizophrenias) varying in symptoms and severity. Associations between genotypic networks and clinical syndromes were complex, showing multifinality and equifinality. The interactive networks explained the risk of schizophrenia more than the average effects of all SNPs (24%).
Conclusions
Schizophrenia is a group of heritable disorders caused by a moderate number of separate genotypic networks associated with several distinct clinical syndromes.
Link: http://ajp.psychiatryonline.org/
Method
In a large genome-wide association study of cases with schizophrenia and controls, the authors first identified sets of interacting single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (SNP sets) regardless of clinical status. Second, they examined the risk of schizophrenia for each SNP set and tested replicability in two independent samples. Third, they identified genotypic networks composed of SNP sets sharing SNPs or subjects. Fourth, they identified sets of distinct clinical features that cluster in particular cases (phenotypic sets or clinical syndromes) without regard for their genetic background. Fifth, they tested whether SNP sets were associated with distinct phenotypic sets in a replicable manner across the three studies.
Results
The authors identified 42 SNP sets associated with a 70% or greater risk of schizophrenia, and confirmed 34 (81%) or more with similar high risk of schizophrenia in two independent samples. Seventeen networks of SNP sets did not share any SNP or subject. These disjoint genotypic networks were associated with distinct gene products and clinical syndromes (i.e., the schizophrenias) varying in symptoms and severity. Associations between genotypic networks and clinical syndromes were complex, showing multifinality and equifinality. The interactive networks explained the risk of schizophrenia more than the average effects of all SNPs (24%).
Conclusions
Schizophrenia is a group of heritable disorders caused by a moderate number of separate genotypic networks associated with several distinct clinical syndromes.
One Antidepressant Dose Causes Rapid Brain Changes
Journal of Current BiologySummary
Serotonin functions as an essential neuromodulator that serves a multitude of roles, most prominently balancing mood. Serotonergic challenge has been observed to reduce intrinsic functional connectivity in brain regions implicated in mood regulation. However, the full scope of serotonergic action on functional connectivity in the human brain has not been explored. Here, we show evidence that a single dose of a serotonin reuptake inhibitor dramatically alters functional connectivity throughout the whole brain in healthy subjects (n = 22). Our network-centrality analysis reveals a widespread decrease in connectivity in most cortical and subcortical areas. In the cerebellum and thalamus, however, we find localized increases. These rapid and brain-encompassing connectivity changes linked to acute serotonin transporter blockade suggest a key role for the serotonin transporter in the modulation of the functional macroscale connectome.
Link: http://www.cell.com/current-biology/
Blood Test for Depression?
Translational PsychiatryAbstract
An objective, laboratory-based diagnostic tool could increase the diagnostic accuracy of major depressive disorders (MDDs), identify factors that characterize patients and promote individualized therapy. The goal of this study was to assess a blood-based biomarker panel, which showed promise in adolescents with MDD, in adult primary care patients with MDD and age-, gender- and race-matched nondepressed (ND) controls. Patients with MDD received cognitive behavioral therapy (CBT) and clinical assessment using self-reported depression with the Patient Health Questionnaire–9 (PHQ-9). The measures, including blood RNA collection, were obtained before and after 18 weeks of CBT. Blood transcript levels of nine markers of ADCY3, DGKA, FAM46A, IGSF4A/CADM1, KIAA1539, MARCKS, PSME1, RAPH1 and TLR7, differed significantly between participants with MDD (N=32) and ND controls (N=32) at baseline (q< 0.05). Abundance of the DGKA, KIAA1539 and RAPH1 transcripts remained significantly different between subjects with MDD and ND controls even after post-CBT remission (defined as PHQ-9 <5). The ROC area under the curve for these transcripts demonstrated high discriminative ability between MDD and ND participants, regardless of their current clinical status. Before CBT, significant co-expression network of specific transcripts existed in MDD subjects who subsequently remitted in response to CBT, but not in those who remained depressed. Thus, blood levels of different transcript panels may identify the depressed from the nondepressed among primary care patients, during a depressive episode or in remission, or follow and predict response to CBT in depressed individuals.
Link: http://www.nature.com/tp/journal/v4/
An Inflammatory Biomarker as a Differential Predictor of Outcome of Depression Treatment
The American Journal of PsychiatryAbstract
Objective
Major depressive disorder has been linked with inflammatory processes, but it is unclear whether individual differences in levels of inflammatory biomarkers could help match patients to treatments that are most likely to be beneficial. The authors tested the hypothesis that C-reactive protein (CRP), a commonly available marker of systemic inflammation, predicts differential response to escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor).
Method
The hypothesis was tested in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, a multicenter open-label randomized clinical trial. CRP was measured with a high-sensitivity method in serum samples from 241 adult men and women with major depressive disorder randomly allocated to 12-week treatment with escitalopram (N=115) or nortriptyline (N=126). The primary outcome measure was the score on the Montgomery-Åsberg Depression Rating Scale (MADRS), administered weekly.
Results
CRP level at baseline differentially predicted treatment outcome with the two antidepressants (CRP-drug interaction: β=3.27, 95% CI=1.65, 4.89). For patients with low levels of CRP (<1 mg/L), improvement on the MADRS score was 3 points higher with escitalopram than with nortriptyline. For patients with higher CRP levels, improvement on the MADRS score was 3 points higher with nortriptyline than with escitalopram. CRP and its interaction with medication explained more than 10% of individual-level variance in treatment outcome.
Conclusions
An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.
Link: http://ajp.psychiatryonline.org/
Rapid Mood-Elevating Effects of Low Field Magnetic Stimulation in Depression
Journal: Biological PsychiatryAbstract
Background
We previously reported rapid mood elevation following an experimental magnetic resonance imaging procedure in depressed patients with bipolar disorder (BPD). This prompted the design, construction, and testing of a portable electromagnetic device that reproduces only the rapidly oscillating (1 kHz, <1 V/m) electromagnetic field of the experimental procedure, called low field magnetic stimulation (LFMS).
Methods
We used a randomized, double blind, sham controlled treatment protocol to study the effects of LFMS in a large group of stably medicated, depressed patients with either BPD (n = 41) or major depressive disorder (n = 22). Subjects received a single, 20-minute treatment. Change in mood was assessed immediately afterward using a visual analog scale (VAS), the 17-item Hamilton Depression Rating Scale (HDRS-17), and the Positive and Negative Affect Schedule scales.
Results
Substantial improvement (>10% of baseline) in mood was observed following LFMS treatment relative to sham treatment for both diagnostic subgroups for our primary outcomes, the VAS and the HDRS-17. These differences were not statistically significant in primary analyses stratifying by diagnosis but were significant in secondary analyses combining data across the two diagnostic groups (p = .01 VAS, p = .02 HDRS-17). Rapid improvement in mood was also observed using the Positive and Negative Affect Schedule scales as secondary measures (positive affect scale p = .02 BPD, p = .002 combined group). A finite element method calculation indicates a broad penetration of the LFMS electric field throughout the cerebral cortex.
Conclusions
Low field magnetic stimulation may produce rapid changes in mood using a previously unexplored range of electromagnetic fields.
Link: http://www.biologicalpsychiatryjournal.com/
Reversal of cognitive decline: A novel therapeutic program
Aging JournalAbstract
This report describes a novel, comprehensive, and personalized therapeutic program that is based on the underlying pathogenesis of Alzheimer's disease, and which involves multiple modalities designed to achieve metabolic enhancement for neurodegeneration (MEND). The first 10 patients who have utilized this program include patients with memory loss associated with Alzheimer's disease (AD), amnestic mild cognitive impairment (aMCI), or subjective cognitive impairment (SCI). Nine of the 10 displayed subjective or objective improvement in cognition beginning within 3-6 months, with the one failure being a patient with very late stage AD. Six of the patients had had to discontinue working or were struggling with their jobs at the time of presentation, and all were able to return to work or continue working with improved performance. Improvements have been sustained, and at this time the longest patient follow-up is two and one-half years from initial treatment, with sustained and marked improvement. These results suggest that a larger, more extensive trial of this therapeutic program is warranted. The results also suggest that, at least early in the course, cognitive decline may be driven in large part by metabolic processes. Furthermore, given the failure of monotherapeutics in AD to date, the results raise the possibility that such a therapeutic system may be useful as a platform on which drugs that would fail as monotherapeutics may succeed as key components of a therapeutic system.
Link: http://www.impactaging.com/papers/v6/
