A shared neural basis underlying psychiatric comorbidity

doi:10.1038/s41591-023-02317-4

. 2023 May;29(5):1232-1242.

doi: 10.1038/s41591-023-02317-4. Epub 2023 Apr 24.

A shared neural basis underlying psychiatric comorbidity

Chao Xie^{1

2}, Shitong Xiang^{1

2}, Chun Shen^{1

2}, Xuerui Peng³, Jujiao Kang^{1

2}, Yuzhu Li^{1

2}, Wei Cheng^{1

2}, Shiqi He^{1

4}, Marina Bobou⁵, M John Broulidakis⁶, Betteke Maria van Noort⁷, Zuo Zhang⁵, Lauren Robinson^{8

9}, Nilakshi Vaidya¹⁰, Jeanne Winterer^{10

11}, Yuning Zhang¹², Sinead King^{5

13}, Tobias Banaschewski¹⁴, Gareth J Barker¹⁵, Arun L W Bokde¹⁶, Uli Bromberg¹⁷, Christian Büchel¹⁷, Herta Flor^{18

19}, Antoine Grigis²⁰, Hugh Garavan²¹, Penny Gowland²², Andreas Heinz¹⁰, Bernd Ittermann²³, Hervé Lemaître²⁴, Jean-Luc Martinot²⁵, Marie-Laure Paillère Martinot^{25

26}, Frauke Nees^{14

18

27}, Dimitri Papadopoulos Orfanos²⁰, Tomáš Paus²⁸, Luise Poustka²⁹, Juliane H Fröhner³⁰, Ulrike Schmidt^{8

9}, Julia Sinclair⁶, Michael N Smolka³⁰, Argyris Stringaris³¹, Henrik Walter¹⁰, Robert Whelan³², Sylvane Desrivières⁵, Barbara J Sahakian^{1

33}, Trevor W Robbins^#^{1

34}, Gunter Schumann^#^{1

10

35

36}, Tianye Jia^#^{37

38

39}, Jianfeng Feng^#^{1

2

40

41

42}; IMAGEN Consortium; STRATIFY/ESTRA Consortium; ZIB Consortium

Collaborators, Affiliations

Collaborators

Betteke Maria van Noort

Affiliations

¹ Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
² Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
³ Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.
⁴ School of Health Sciences, The University of Manchester, Manchester, UK.
⁵ Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁶ Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
⁷ Department of Psychology, MSB Medical School Berlin, Berlin, Germany.
⁸ Department of Psychological Medicine, Section for Eating Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁹ South London and Maudsley NHS Foundation Trust, London, UK.
¹⁰ Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
¹¹ Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.
¹² Psychology Department, University of Southampton, Southampton, UK.
¹³ School of Medicine, Center for Neuroimaging, Cognition and Genomics, National University of Ireland (NUI) Galway, Galway, Ireland.
¹⁴ Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
¹⁵ Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
¹⁶ Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
¹⁷ University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
¹⁸ Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
¹⁹ Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany.
²⁰ NeuroSpin, C.E.A., Université Paris-Saclay, Gif-sur-Yvette, France.
²¹ Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA.
²² Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK.
²³ Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
²⁴ Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France.
²⁵ Institut National de la Santé et de la Recherche Médicale, INSERM U1299 'Trajectoires développementales en psychiatrie', Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS UMR9010, Centre Borelli, Gif-sur-Yvette, France.
²⁶ AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France.
²⁷ Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany.
²⁸ Department of Psychiatry and Neuroscience and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Quebec, Canada.
²⁹ Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany.
³⁰ Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.
³¹ Division of Psychiatry and Department of Clinical, Educational & Health Psychology, University College London, London, UK.
³² School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
³³ Department of Psychiatry and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK.
³⁴ Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK.
³⁵ Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany.
³⁶ PONS Centre, Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China.
³⁷ Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. tianyejia@fudan.edu.cn.
³⁸ Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China. tianyejia@fudan.edu.cn.
³⁹ Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. tianyejia@fudan.edu.cn.
⁴⁰ School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China.
⁴¹ Department of Computer Science, University of Warwick, Coventry, UK.
⁴² Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China.

^# Contributed equally.

PMID: 37095248
PMCID: PMC10202801
DOI: 10.1038/s41591-023-02317-4

A shared neural basis underlying psychiatric comorbidity

Chao Xie et al. Nat Med. 2023 May.

. 2023 May;29(5):1232-1242.

doi: 10.1038/s41591-023-02317-4. Epub 2023 Apr 24.

Authors

Collaborators

Betteke Maria van Noort

Affiliations

¹ Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
² Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
³ Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.
⁴ School of Health Sciences, The University of Manchester, Manchester, UK.
⁵ Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁶ Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
⁷ Department of Psychology, MSB Medical School Berlin, Berlin, Germany.
⁸ Department of Psychological Medicine, Section for Eating Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁹ South London and Maudsley NHS Foundation Trust, London, UK.
¹⁰ Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
¹¹ Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.
¹² Psychology Department, University of Southampton, Southampton, UK.
¹³ School of Medicine, Center for Neuroimaging, Cognition and Genomics, National University of Ireland (NUI) Galway, Galway, Ireland.
¹⁴ Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
¹⁵ Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
¹⁶ Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
¹⁷ University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
¹⁸ Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
¹⁹ Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany.
²⁰ NeuroSpin, C.E.A., Université Paris-Saclay, Gif-sur-Yvette, France.
²¹ Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA.
²² Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK.
²³ Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
²⁴ Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France.
²⁵ Institut National de la Santé et de la Recherche Médicale, INSERM U1299 'Trajectoires développementales en psychiatrie', Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS UMR9010, Centre Borelli, Gif-sur-Yvette, France.
²⁶ AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France.
²⁷ Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany.
²⁸ Department of Psychiatry and Neuroscience and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Quebec, Canada.
²⁹ Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany.
³⁰ Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.
³¹ Division of Psychiatry and Department of Clinical, Educational & Health Psychology, University College London, London, UK.
³² School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
³³ Department of Psychiatry and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK.
³⁴ Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK.
³⁵ Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany.
³⁶ PONS Centre, Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China.
³⁷ Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. tianyejia@fudan.edu.cn.
³⁸ Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China. tianyejia@fudan.edu.cn.
³⁹ Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. tianyejia@fudan.edu.cn.
⁴⁰ School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China.
⁴¹ Department of Computer Science, University of Warwick, Coventry, UK.
⁴² Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China.

^# Contributed equally.

PMID: 37095248
PMCID: PMC10202801
DOI: 10.1038/s41591-023-02317-4

Erratum in

Author Correction: A shared neural basis underlying psychiatric comorbidity.
Xie C, Xiang S, Shen C, Peng X, Kang J, Li Y, Cheng W, He S, Bobou M, Broulidakis MJ, van Noort BM, Zhang Z, Robinson L, Vaidya N, Winterer J, Zhang Y, King S, Banaschewski T, Barker GJ, Bokde ALW, Bromberg U, Büchel C, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Lemaître H, Martinot JL, Martinot MP, Nees F, Orfanos DP, Paus T, Poustka L, Fröhner JH, Schmidt U, Sinclair J, Smolka MN, Stringaris A, Walter H, Whelan R, Desrivières S, Sahakian BJ, Robbins TW, Schumann G, Jia T, Feng J; IMAGEN Consortium; STRATIFY/ESTRA Consortium; ZIB Consortium. Xie C, et al. Nat Med. 2023 Sep;29(9):2375. doi: 10.1038/s41591-023-02512-3. Nat Med. 2023. PMID: 37558759 Free PMC article. No abstract available.

Abstract

Recent studies proposed a general psychopathology factor underlying common comorbidities among psychiatric disorders. However, its neurobiological mechanisms and generalizability remain elusive. In this study, we used a large longitudinal neuroimaging cohort from adolescence to young adulthood (IMAGEN) to define a neuropsychopathological (NP) factor across externalizing and internalizing symptoms using multitask connectomes. We demonstrate that this NP factor might represent a unified, genetically determined, delayed development of the prefrontal cortex that further leads to poor executive function. We also show this NP factor to be reproducible in multiple developmental periods, from preadolescence to early adulthood, and generalizable to the resting-state connectome and clinical samples (the ADHD-200 Sample and the Stratify Project). In conclusion, we identify a reproducible and general neural basis underlying symptoms of multiple mental health disorders, bridging multidimensional evidence from behavioral, neuroimaging and genetic substrates. These findings may help to develop new therapeutic interventions for psychiatric comorbidities.

PubMed Disclaimer

Conflict of interest statement

T.B. served in an advisory or consultancy role for Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg GmbH and Shire. He received conference support or speaker’s fee from Lilly, Medice, Novartis and Shire. He has been involved in clinical trials conducted by Shire and Viforpharma. He received royalties from Hogrefe, Kohlhammer, CIP Medien and Oxford University Press. The present work is unrelated to the above grants and relationships. G.J.B. received honoraria from General Electric Healthcare for teaching scanner programming courses. All other authors declare no competing interests.

Figures

**Fig. 1. Overview of research questions and analyses.**
a, This study aims to answer three questions (Q1–Q3) about multiple neurobiological aspects of general psychopathology. b, We identified the NP factor in the IMAGEN dataset at ages 14 and 19 on the basis of task-based FC with a CPM (Q1; N = 1,750). c, We characterized the NP factor using multiple neurocognitive behaviors and genetic substrates (Q2). d, We checked the generalizability of the NP factor in multiple developmental periods using different fMRI states (Q3; N = 4,942). AN, anorexia nervosa; BN, bulimia nervosa; AUD, alcohol use disorder ; MDD, major depressive disorder; ADHD, attention-deficit/hyperactivity disorder; ASD, autism spectrum disorder; CD, conduct disorder; ODD, oppositional defiant disorder; GAD, general anxiety disorder; Dep., depression; ED, eating disorder; SP, specific phobia; FPN, frontoparietal network; IFG, inferior frontal gyrus; mPFC, medial prefrontal cortex; SAL, salience network; SMF, superior medial frontal network; NP factor score, the connectivity strength of the NP factor; vPCun, ventral precuneus.

**Fig. 2. Histograms of externalizing and internalizing symptoms at age 14.**
Externalizing symptoms include ASD, ADHD, CD and ODD; internalizing symptoms include GAD, depression, ED and SP. The green line in each graph marks an approximate threshold for individuals who are high risk (that is, chance with diagnoses is over 50% according to Development And Well-Being Assessment (DAWBA)).

**Fig. 3. Identification of the NP factor.**
a, The predictive performance of behavioral symptoms related to psychiatric disorders using the task-based connectivity model. Task-based connectivity was obtained from the EFT (angry and neutral conditions), the MID task (reward anticipation, positive reward feedback and negative reward feedback conditions) and the SST (go-wrong, stop-success and stop-failure conditions). Overall predictive performance was estimated using a multiple regression model with predicted symptoms of all task conditions. b, Crossdisorder edges could predict externalizing and internalizing symptoms simultaneously. Externalizing symptoms consisted of ASD, ADHD, CD and ODD. Internalizing symptoms comprised GAD, Dep., ED and SP. For each task condition, we further estimated whether the set of crossdisorder edges was significantly larger than a random discovery with permutation tests. The results showed that only conditions from the SST and MID task had significantly more crossdisorder edges than a random observation. c, Using reliability and longitudinal analyses, we identified the NP factor that was positively predictive for both externalizing and internalizing symptoms across ages 14 and 19. 14-brain, brain at age 14; 19-brain, brain at age 19; exter., externalizing; inter., internalizing; neg., negative; NP factor score, the summed FC strength of the transdiagnostic edges; NS, not significant; pos., positive.

**Fig. 4. Neurobiological characterization of the NP factor.**
a, The functional brain connections of the NP factor were mainly localized between the frontoparietal network and the superior medial frontal and limbic networks. The color bar indicates the strength of normalized inter- or intranetwork connections, where the number of connections between or within networks was divided by the largest connection number observed. b, The top 10% nodes in the NP factor ranked by the normalized node degree (that is, the number of connections with other nodes). c, The functional connection network of the NP factor containing the node with the largest degree (that is, the ventral precuneus). d, The NP factor was associated with response accuracy during the MID task and the SST. e, The NP factor was associated with most cognitive functions (13 of 20), primarily executive function-related behaviors. The significance level (that is, the dashed line) was given as a false discovery rate (fdr) of 0.05. The P values were reported as the original value and could survive the multiple correction with Benjamin–Hochberg procedure. |t| stands for the absolute value of t-statistics. AGN, Affective Go-No Go; BMI, body mass index; DD, Delay Discounting Task; MidOcci, middle occipital cortex; MidPFC, middle prefrontal cortex; NEO, NEO Personality Inventory; RVP: A, Target Sensitivity from Rapid Visual Information Processing task; PRM, Pattern Recognition Memory task; SURPS, Substance Use Risk Personality Scale; SWM, Spatial Working Memory task; TCI, Temperament and Character Inventory–Revised.

**Fig. 5. Genetic analyses of the NP factor.**
a, The NP factor correlated with the PRSs of ADHD, depression and IQ, and all were associated with most behavioral symptoms (N = 1,594 for age 14; N = 1,200 for age 19). b, The NP factor was associated with a crossdisorder SNP rs6780942, which was identified in a previous crossdisorder GWAS. This SNP is mapped to the *IGSF11* gene. The upper and lower bars represent the Q3 + 1.5 × IQR and Q1 − 1.5 × IQR, respectively. The upper and lower edges of a box represent the Q3 and Q1, and the central line represents the median. Outliers are illustrated as bold dots. c, Expression of *IGSF11* across 15 brain regions peaks at adolescence. The P values were reported as the original value and could survive the multiple correction with Benjamin–Hochberg procedure. * P < 0.05, ** P < 0.01, *** P < 0.001. Q1, first quartile; Q3, third quartile; IQR, interquartile range.

**Extended Data Fig. 1. The construction process of the NP factor.**
a. For each participant, we first constructed the brain connectome for each task condition of the three tasks with a whole-brain 268 region atlas. Specifically, the EFT contained angry and neutral conditions; the SST contained go wrong, stop success, and stop failure conditions; the MID task contained positive feedback, reward anticipation, and negative feedback conditions. We also collected eight behavioural symptoms: four externalising symptoms (ASD, ADHD, ODD, and CD) and four internalising symptoms (GAD, ED, Dep. And SP). We then estimated the brain signature for each behavioural symptom with each task-based connectome by the machine-learning method of Connectome-based predictive modeling (CPM). b. With the identified brain signature for behavioural symptoms, we next constructed the Neuropsychopathological (NP) Factor in three steps. First, for each task condition, we counted the number of cross-disorder edges that the edge was predictive of both externalising and internalising symptoms. Then we used the permutation test to identify reliable conditions where the number of cross-disorder edges was significantly higher than random discovery. These reliable cross-disorder edges were then divided into four groups regarding their simultaneous predictive effects for externalising and internalising symptoms (that is positive-positive, positive-negative, negative-positive and negative-negative), and we conducted longitudinal analyses to identify which groups of cross-disorder edges could be used to form the NP factor that is still predictive to both externalising and internalising symptoms at age 19.

**Extended Data Fig. 2. The group difference of the NP factor scores between comorbid-diagnoses, single-diagnosis and healthy control groups.**
The upper and lower bars represent the Q3 + 1.5xIQR and Q1–1.5xIQR, respectively. Abbreviation: Q1: the 1st quartile; Q3: the 3rd quartile; IQR: the interquartile range; * P < 0.05, ** P < 0.01, *** P < 0.001; ns. not significant.

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References

1. van den Akker M, Buntinx F, Knottnerus JA. Comorbidity or multimorbidity: what’s in a name? A review of literature. Eur. J. Gen. Pract. 1996;2:65–70. doi: 10.3109/13814789609162146. - DOI
1. Fusar-Poli P, et al. Transdiagnostic psychiatry: a systematic review. World Psychiatry. 2019;18:192–207. doi: 10.1002/wps.20631. - DOI - PMC - PubMed
1. Krueger RF, Eaton NR. Transdiagnostic factors of mental disorders. World Psychiatry. 2015;14:27–29. doi: 10.1002/wps.20175. - DOI - PMC - PubMed
1. Plana-Ripoll, O. et al. Exploring comorbidity within mental disorders among a Danish national population. JAMA Psychiatry76, 259–270 (2019). - PMC - PubMed
1. Kessler RC, et al. Age of onset of mental disorders: a review of recent literature. Curr. Opin. Psychiatry. 2007;20:359–364. doi: 10.1097/YCO.0b013e32816ebc8c. - DOI - PMC - PubMed

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[1] van den Akker M, Buntinx F, Knottnerus JA. Comorbidity or multimorbidity: what’s in a name? A review of literature. Eur. J. Gen. Pract. 1996;2:65–70. doi: 10.3109/13814789609162146. - DOI

[2] van den Akker M, Buntinx F, Knottnerus JA. Comorbidity or multimorbidity: what’s in a name? A review of literature. Eur. J. Gen. Pract. 1996;2:65–70. doi: 10.3109/13814789609162146. - DOI

[3] Fusar-Poli P, et al. Transdiagnostic psychiatry: a systematic review. World Psychiatry. 2019;18:192–207. doi: 10.1002/wps.20631. - DOI - PMC - PubMed

[4] Fusar-Poli P, et al. Transdiagnostic psychiatry: a systematic review. World Psychiatry. 2019;18:192–207. doi: 10.1002/wps.20631. - DOI - PMC - PubMed

[5] Krueger RF, Eaton NR. Transdiagnostic factors of mental disorders. World Psychiatry. 2015;14:27–29. doi: 10.1002/wps.20175. - DOI - PMC - PubMed

[6] Krueger RF, Eaton NR. Transdiagnostic factors of mental disorders. World Psychiatry. 2015;14:27–29. doi: 10.1002/wps.20175. - DOI - PMC - PubMed

[7] Plana-Ripoll, O. et al. Exploring comorbidity within mental disorders among a Danish national population. JAMA Psychiatry76, 259–270 (2019). - PMC - PubMed

[8] Plana-Ripoll, O. et al. Exploring comorbidity within mental disorders among a Danish national population. JAMA Psychiatry76, 259–270 (2019). - PMC - PubMed

[9] Kessler RC, et al. Age of onset of mental disorders: a review of recent literature. Curr. Opin. Psychiatry. 2007;20:359–364. doi: 10.1097/YCO.0b013e32816ebc8c. - DOI - PMC - PubMed

[10] Kessler RC, et al. Age of onset of mental disorders: a review of recent literature. Curr. Opin. Psychiatry. 2007;20:359–364. doi: 10.1097/YCO.0b013e32816ebc8c. - DOI - PMC - PubMed

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A shared neural basis underlying psychiatric comorbidity

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A shared neural basis underlying psychiatric comorbidity

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