1
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Abi-Dargham A, Moeller SJ, Ali F, DeLorenzo C, Domschke K, Horga G, Jutla A, Kotov R, Paulus MP, Rubio JM, Sanacora G, Veenstra-VanderWeele J, Krystal JH. Candidate biomarkers in psychiatric disorders: state of the field. World Psychiatry 2023; 22:236-262. [PMID: 37159365 PMCID: PMC10168176 DOI: 10.1002/wps.21078] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2023] [Indexed: 05/11/2023] Open
Abstract
The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.
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Affiliation(s)
- Anissa Abi-Dargham
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Scott J Moeller
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Farzana Ali
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Christine DeLorenzo
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Centre for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Guillermo Horga
- Department of Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Amandeep Jutla
- Department of Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Roman Kotov
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | | | - Jose M Rubio
- Zucker School of Medicine at Hofstra-Northwell, Hempstead, NY, USA
- Feinstein Institute for Medical Research - Northwell, Manhasset, NY, USA
- Zucker Hillside Hospital - Northwell Health, Glen Oaks, NY, USA
| | - Gerard Sanacora
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Jeremy Veenstra-VanderWeele
- Department of Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
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2
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Breen MS, Fan X, Levy T, Pollak RM, Collins B, Osman A, Tocheva AS, Sahin M, Berry-Kravis E, Soorya L, Thurm A, Powell CM, Bernstein JA, Kolevzon A, Buxbaum JD. Large 22q13.3 deletions perturb peripheral transcriptomic and metabolomic profiles in Phelan-McDermid syndrome. HGG ADVANCES 2023; 4:100145. [PMID: 36276299 PMCID: PMC9579712 DOI: 10.1016/j.xhgg.2022.100145] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 09/23/2022] [Indexed: 11/25/2022] Open
Abstract
Phelan-McDermid syndrome (PMS) is a rare neurodevelopmental disorder caused at least in part by haploinsufficiency of the SHANK3 gene, due to sequence variants in SHANK3 or subtelomeric 22q13.3 deletions. Phenotypic differences have been reported between PMS participants carrying small "class I" mutations and large "class II" mutations; however, the molecular perturbations underlying these divergent phenotypes remain obscure. Using peripheral blood transcriptome and serum metabolome profiling, we examined the molecular perturbations in the peripheral circulation associated with a full spectrum of PMS genotypes spanning class I (n = 37) and class II mutations (n = 39). Transcriptomic data revealed 52 genes with blood expression profiles that tightly scale with 22q.13.3 deletion size. Furthermore, we uncover 208 underexpressed genes in PMS participants with class II mutations, which were unchanged in class I mutations. These genes were not linked to 22q13.3 and were strongly enriched for glycosphingolipid metabolism, NCAM1 interactions, and cytotoxic natural killer (NK) immune cell signatures. In silico predictions estimated a reduction in CD56+ CD16- NK cell proportions in class II mutations, which was validated by mass cytometry time of flight. Global metabolomics profiling identified 24 metabolites that were significantly altered in PMS participants with class II mutations and confirmed a general reduction in sphingolipid metabolism. Collectively, these results provide new evidence linking PMS participants carrying class II mutations with decreased expression of cytotoxic cell signatures, reduced relative proportions of NK cells, and lower sphingolipid metabolism. These findings highlight alternative avenues for therapeutic development and offer new mechanistic insights supporting genotype-to-phenotype associations in PMS.
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Affiliation(s)
- Michael S Breen
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xuanjia Fan
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tess Levy
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca M Pollak
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brett Collins
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aya Osman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anna S Tocheva
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Rosamund Stone Zander Translational Neuroscience Center and F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth Berry-Kravis
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Latha Soorya
- Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA
| | - Audrey Thurm
- Neurodevelopmental and Behavioral Phenotyping Service, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Craig M Powell
- Department of Neurobiology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA.,Civitan International Research Center, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Jonathan A Bernstein
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexander Kolevzon
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph D Buxbaum
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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3
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A Comprehensive Exploration of the Transcriptomic Landscape in Multiple Sclerosis: A Systematic Review. Int J Mol Sci 2023; 24:ijms24021448. [PMID: 36674968 PMCID: PMC9862618 DOI: 10.3390/ijms24021448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/29/2022] [Accepted: 01/09/2023] [Indexed: 01/15/2023] Open
Abstract
Multiple Sclerosis (MS) is, to date, an incurable disease of the nervous system characterized by demyelination. Several genetic mutations are associated with the disease but they are not able to explain all the diagnosticated cases. Thus, it is suggested that altered gene expression may play a role in human pathologies. In this review, we explored the role of the transcriptomic profile in MS to investigate the main altered biological processes and pathways involved in the disease. Herein, we focused our attention on RNA-seq methods that in recent years are producing a huge amount of data rapidly replacing microarrays, both with bulk and single-cells. The studies evidenced that different MS stages have specific molecular signatures and non-coding RNAs may play a key role in the disease. Sex-dependence was observed before and after treatments used to alleviate symptomatology activating different biological processes in a drug-dependent manner. New pathways, such as neddylation, were found deregulated in MS and inflammation was linked to neuron degeneration areas through spatial transcriptomics. It is evident that the use of RNA-seq in the study of complex pathologies, such as MS, is a valid strategy to shed light on new involved mechanisms.
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Yamagata H, Kobayashi A, Tsunedomi R, Seki T, Kobayashi M, Hagiwara K, Chen C, Uchida S, Okada G, Fuchikami M, Kamishikiryo T, Iga JI, Numata S, Kinoshita M, Kato TA, Hashimoto R, Nagano H, Okamoto Y, Ueno S, Ohmori T, Nakagawa S. Optimized protocol for the extraction of RNA and DNA from frozen whole blood sample stored in a single EDTA tube. Sci Rep 2021; 11:17075. [PMID: 34426633 PMCID: PMC8382694 DOI: 10.1038/s41598-021-96567-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 08/11/2021] [Indexed: 01/27/2023] Open
Abstract
Cryopreservation of whole blood is useful for DNA collection, and clinical and basic research. Blood samples in ethylenediaminetetraacetic acid disodium salt (EDTA) tubes stored at − 80 °C are suitable for DNA extraction, but not for high-quality RNA extraction. Herein, a new methodology for high-quality RNA extraction from human blood samples is described. Quickly thawing frozen whole blood on aluminum blocks at room temperature could minimize RNA degradation, and improve RNA yield and quality compared with thawing the samples in a 37 °C water bath. Furthermore, the use of the NucleoSpin RNA kit increased RNA yield by fivefold compared with the PAXgene Blood RNA Kit. Thawing blood samples on aluminum blocks significantly increased the DNA yield by ~ 20% compared with thawing in a 37 °C water bath or on ice. Moreover, by thawing on aluminum blocks and using the NucleoSpin RNA and QIAamp DNA Blood kits, the extraction of RNA and DNA of sufficient quality and quantity was achieved from frozen EDTA whole blood samples that were stored for up to 8.5 years. Thus, extracting RNA from frozen whole blood in EDTA tubes after long-term storage is feasible. These findings may help advance gene expression analysis, as well as biomarker research for various diseases.
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Affiliation(s)
- Hirotaka Yamagata
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan. .,Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan.
| | - Ayumi Kobayashi
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Ryouichi Tsunedomi
- Department of Gastroenterological, Breast and Endocrine Surgery, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Tomoe Seki
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan.,Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan
| | - Masaaki Kobayashi
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Kosuke Hagiwara
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Chong Chen
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Shusaku Uchida
- Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan.,SK Project, Medical Innovation Center, Kyoto University Graduate School of Medicine, 53 Shogoin‑Kawahara‑cho, Sakyo‑ku, Kyoto, 606‑8507, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Manabu Fuchikami
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Toshiharu Kamishikiryo
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Jun-Ichi Iga
- Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Shusuke Numata
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, 3-18-5 Kuramoto-cho, Tokushima, 770-8503, Japan
| | - Makoto Kinoshita
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, 3-18-5 Kuramoto-cho, Tokushima, 770-8503, Japan
| | - Takahiro A Kato
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi Higashi-Ku, Fukuoka, 812-8582, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo, 187-8553, Japan
| | - Hiroaki Nagano
- Department of Gastroenterological, Breast and Endocrine Surgery, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Shuichi Ueno
- Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Tetsuro Ohmori
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, 3-18-5 Kuramoto-cho, Tokushima, 770-8503, Japan
| | - Shin Nakagawa
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-kogushi, Ube, Yamaguchi, 755-8505, Japan
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5
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Rhee SJ, Han D, Lee Y, Kim H, Lee J, Lee K, Shin H, Kim H, Lee TY, Kim M, Kim SH, Ahn YM, Kwon JS, Ha K. Comparison of serum protein profiles between major depressive disorder and bipolar disorder. BMC Psychiatry 2020; 20:145. [PMID: 32245436 PMCID: PMC7118970 DOI: 10.1186/s12888-020-02540-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 03/10/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders. METHODS Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted. RESULTS Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10- 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10- 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p = 1.5 × 10- 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different. CONCLUSIONS Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.
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Affiliation(s)
- Sang Jin Rhee
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dohyun Han
- grid.412484.f0000 0001 0302 820XProteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yunna Lee
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeyoung Kim
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea ,grid.411605.70000 0004 0648 0025Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea
| | - Junhee Lee
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kangeun Lee
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyunsuk Shin
- grid.412484.f0000 0001 0302 820XProteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeyoon Kim
- grid.412484.f0000 0001 0302 820XProteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tae Young Lee
- grid.412484.f0000 0001 0302 820XInstitute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea ,grid.412591.a0000 0004 0442 9883Department of Neuropsychiatry, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Minah Kim
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Se Hyun Kim
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yong Min Ahn
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea ,grid.412484.f0000 0001 0302 820XInstitute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Jun Soo Kwon
- grid.412484.f0000 0001 0302 820XDepartment of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea ,grid.412484.f0000 0001 0302 820XInstitute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Kyooseob Ha
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea. .,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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6
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Wang Y, Cheng C, Zhang Z, Wang J, Wang Y, Li X, Gao R, Wang Z, Fang Y, Wang J, Wang M, Fan Q, Periya S, Zhang H, Tsuang MT, Liew CC. Blood-based dynamic genomic signature for obsessive-compulsive disorder. Am J Med Genet B Neuropsychiatr Genet 2018; 177:709-716. [PMID: 30350918 DOI: 10.1002/ajmg.b.32675] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 07/03/2018] [Accepted: 07/05/2018] [Indexed: 12/29/2022]
Abstract
No biologically based diagnostic criteria are in clinical use today for obsessive-compulsive disorder (OCD), schizophrenia, and major depressive disorder (MDD), which are defined with reference to Diagnostic and Statistical Manual clinical symptoms alone. However, these disorders cannot always be well distinguished on clinical grounds and may also be comorbid. A biological blood-based dynamic genomic signature that can differentiate among OCD, MDD, and schizophrenia would therefore be of great utility. This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD-specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six-gene panel (COPS7A, FKBP1A, FIBP, TP73-AS1, SDF4, and GOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver-operating-characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood-based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.
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Affiliation(s)
- Yuan Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Changming Cheng
- Research and Development Department, Shanghai Biomedical Laboratory, Shanghai, People's Republic of China.,Research and Development Department, Bionexus Gene Laboratory, Penang, Malaysia
| | - Zongfeng Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jianyu Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yao Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Xiaoping Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Rui Gao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zhen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yiru Fang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Min Wang
- Research and Development Department, Shanghai Biomedical Laboratory, Shanghai, People's Republic of China
| | - Qing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Sanggetha Periya
- Research and Development Department, Bionexus Gene Laboratory, Penang, Malaysia
| | - Haiyin Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, San Diego, California
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7
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Breen MS, Tylee DS, Maihofer AX, Neylan TC, Mehta D, Binder EB, Chandler SD, Hess JL, Kremen WS, Risbrough VB, Woelk CH, Baker DG, Nievergelt CM, Tsuang MT, Buxbaum JD, Glatt SJ. PTSD Blood Transcriptome Mega-Analysis: Shared Inflammatory Pathways across Biological Sex and Modes of Trauma. Neuropsychopharmacology 2018; 43:469-481. [PMID: 28925389 PMCID: PMC5770765 DOI: 10.1038/npp.2017.220] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Revised: 07/29/2017] [Accepted: 08/29/2017] [Indexed: 01/30/2023]
Abstract
Transcriptome-wide screens of peripheral blood during the onset and development of posttraumatic stress disorder (PTSD) indicate widespread immune dysregulation. However, little is known as to whether biological sex and the type of traumatic event influence shared or distinct biological pathways in PTSD. We performed a combined analysis of five independent PTSD blood transcriptome studies covering seven types of trauma in 229 PTSD and 311 comparison individuals to synthesize the extant data. Analyses by trauma type revealed a clear pattern of PTSD gene expression signatures distinguishing interpersonal (IP)-related traumas from combat-related traumas. Co-expression network analyses integrated all data and identified distinct gene expression perturbations across sex and modes of trauma in PTSD, including one wound-healing module downregulated in men exposed to combat traumas, one IL-12-mediated signaling module upregulated in men exposed to IP-related traumas, and two modules associated with lipid metabolism and mitogen-activated protein kinase activity upregulated in women exposed to IP-related traumas. Remarkably, a high degree of sharing of transcriptional dysregulation across sex and modes of trauma in PTSD was also observed converging on common signaling cascades, including cytokine, innate immune, and type I interferon pathways. Collectively, these findings provide a broad view of immune dysregulation in PTSD and demonstrate inflammatory pathways of molecular convergence and specificity, which may inform mechanisms and diagnostic biomarkers for the disorder.
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Affiliation(s)
- Michael S Breen
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1668, New York, NY 10029, USA, Tel: +1 212 241 0242, Fax: 212 828 4221, E-mail:
| | - Daniel S Tylee
- Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology, Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), SUNY Upstate Medical University, Syracuse, NY, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Thomas C Neylan
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA,San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Divya Mehta
- School of Psychology and Counseling, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Elisabeth B Binder
- Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, Munich, Germany,Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Sharon D Chandler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Jonathan L Hess
- Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology, Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), SUNY Upstate Medical University, Syracuse, NY, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA,Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Victoria B Risbrough
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA,Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Christopher H Woelk
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK,Merck Exploratory Science Center, Merck Research Laboratories, Cambridge, MA, USA
| | - Dewleen G Baker
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA,Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA,Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA,Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen J Glatt
- Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology, Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), SUNY Upstate Medical University, Syracuse, NY, USA
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8
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Belzeaux R, Lalanne L, Kieffer BL, Lutz PE. Focusing on the Opioid System for Addiction Biomarker Discovery. Trends Mol Med 2018; 24:206-220. [PMID: 29396147 DOI: 10.1016/j.molmed.2017.12.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 12/06/2017] [Accepted: 12/09/2017] [Indexed: 12/26/2022]
Abstract
Substance use disorders (SUD) and behavioral addictions are devastating conditions that impose a severe burden on all societies, and represent difficult challenges for clinicians. Therefore, biomarkers are urgently needed to help predict vulnerability, clinical course, and response to treatment. Here, we elaborate on the potential for addiction biomarker discovery of the opioid system, particularly within the emerging framework aiming to probe opioid function in peripheral tissues. Mu, delta, and kappa opioid receptors all critically regulate neurobiological and behavioral processes that define addiction, and are also targeted by major pharmacotherapies used in the management of patients with SUD. We propose that opioid biomarkers may have the potential to improve and guide diagnosis and therapeutic decisions in the addiction field.
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Affiliation(s)
- Raoul Belzeaux
- McGill Group for Suicide Studies, Douglas Hospital Research Center, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Pôle de Psychiatrie, Assistance Publique Hôpitaux de Marseille, Marseille, France; INT-UMR7289,CNRS Aix-Marseille Université, Marseille, France; These authors contributed equally to this article
| | - Laurence Lalanne
- Department of Psychiatry and Addictology, University Hospital of Strasbourg and Medical School of Strasbourg, Strasbourg, France; Fédération de Médecine Translationnelle de Strasbourg, University Hospital of Strasbourg and Medical School of Strasbourg, Strasbourg, France; INSERM 1114, Department of Psychiatry and Addictology, University Hospital of Strasbourg, Strasbourg, France; These authors contributed equally to this article
| | - Brigitte L Kieffer
- Douglas Hospital Research Center, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Pierre-Eric Lutz
- McGill Group for Suicide Studies, Douglas Hospital Research Center, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Current address: Institut des Neurosciences Cellulaires et Intégratives, CNRS UPR 3212, Strasbourg, France.
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9
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Hervé M, Bergon A, Le Guisquet AM, Leman S, Consoloni JL, Fernandez-Nunez N, Lefebvre MN, El-Hage W, Belzeaux R, Belzung C, Ibrahim EC. Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response. Front Mol Neurosci 2017; 10:248. [PMID: 28848385 PMCID: PMC5550836 DOI: 10.3389/fnmol.2017.00248] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 07/24/2017] [Indexed: 12/12/2022] Open
Abstract
Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.
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Affiliation(s)
- Mylène Hervé
- Aix Marseille Univ, CNRS, CRN2M UMR 7286Marseille, France.,FondaMental, Fondation de Recherche et de Soins en Santé MentaleCréteil, France
| | - Aurélie Bergon
- Aix Marseille Univ, INSERM, TAGC UMR_S 1090Marseille, France
| | | | - Samuel Leman
- INSERM U930 Eq 4, UFR Sciences et Techniques, Université François RabelaisTours, France
| | - Julia-Lou Consoloni
- Aix Marseille Univ, CNRS, CRN2M UMR 7286Marseille, France.,FondaMental, Fondation de Recherche et de Soins en Santé MentaleCréteil, France.,AP-HM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire SolarisMarseille, France
| | | | | | - Wissam El-Hage
- INSERM U930 Eq 4, UFR Sciences et Techniques, Université François RabelaisTours, France.,CHRU de Tours, Clinique Psychiatrique UniversitaireTours, France.,INSERM CIC 1415, Centre d'Investigation Clinique, CHRU de ToursTours, France
| | - Raoul Belzeaux
- Aix Marseille Univ, CNRS, CRN2M UMR 7286Marseille, France.,FondaMental, Fondation de Recherche et de Soins en Santé MentaleCréteil, France.,AP-HM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire SolarisMarseille, France.,McGill Group for Suicide Studies, Douglas Mental Health University Institute, Department of Psychiatry, McGill UniversityMontreal, QC, Canada
| | - Catherine Belzung
- INSERM U930 Eq 4, UFR Sciences et Techniques, Université François RabelaisTours, France
| | - El Chérif Ibrahim
- Aix Marseille Univ, CNRS, CRN2M UMR 7286Marseille, France.,FondaMental, Fondation de Recherche et de Soins en Santé MentaleCréteil, France.,Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone UMR 7289Marseille, France
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10
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Parallel changes in serum proteins and diffusion tensor imaging in methamphetamine-associated psychosis. Sci Rep 2017; 7:43777. [PMID: 28252112 PMCID: PMC5333148 DOI: 10.1038/srep43777] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 01/30/2017] [Indexed: 11/09/2022] Open
Abstract
Methamphetamine-associated psychosis (MAP) involves widespread neurocognitive and molecular deficits, however accurate diagnosis remains challenging. Integrating relationships between biological markers, brain imaging and clinical parameters may provide an improved mechanistic understanding of MAP, that could in turn drive the development of better diagnostics and treatment approaches. We applied selected reaction monitoring (SRM)-based proteomics, profiling 43 proteins in serum previously implicated in the etiology of major psychiatric disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurements from patients diagnosed with MAP (N = 12), methamphetamine dependence without psychosis (MA; N = 14) and healthy controls (N = 16). Protein analysis identified changes in APOC2 and APOH, which differed significantly in MAP compared to MA and controls. DTI analysis indicated widespread increases in mean diffusivity and radial diffusivity delineating extensive loss of white matter integrity and axon demyelination in MAP. Upon integration, several co-linear relationships between serum proteins and DTI measures reported in healthy controls were disrupted in MA and MAP groups; these involved areas of the brain critical for memory and social emotional processing. These findings suggest that serum proteomics and DTI are sensitive measures for detecting pathophysiological changes in MAP and describe a potential diagnostic fingerprint of the disorder.
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