Literature DB >> 31153774

The Heterogeneity Problem: Approaches to Identify Psychiatric Subtypes.

Eric Feczko1, Oscar Miranda-Dominguez2, Mollie Marr2, Alice M Graham3, Joel T Nigg3, Damien A Fair4.   

Abstract

The imprecise nature of psychiatric nosology restricts progress towards characterizing and treating mental health disorders. One issue is the 'heterogeneity problem': different causal mechanisms may relate to the same disorder, and multiple outcomes of interest can occur within one individual. Our review tackles this heterogeneity problem, providing considerations, concepts, and approaches for investigators examining human cognition and mental health. We highlight the difficulty of pure dimensional approaches due to 'the curse of dimensionality'. Computationally, we consider supervised and unsupervised statistical approaches to identify putative subtypes within a population. However, we emphasize that subtype identification should be linked to a particular outcome or question. We conclude with novel hybrid approaches that can identify subtypes tied to outcomes, and may help advance precision diagnostic and treatment tools.
Copyright © 2019. Published by Elsevier Ltd.

Entities:  

Keywords:  functional random forest; heterogeneity; machine learning; mental health; surrogate variable analysis

Year:  2019        PMID: 31153774      PMCID: PMC6821457          DOI: 10.1016/j.tics.2019.03.009

Source DB:  PubMed          Journal:  Trends Cogn Sci        ISSN: 1364-6613            Impact factor:   20.229


  100 in total

1.  The sva package for removing batch effects and other unwanted variation in high-throughput experiments.

Authors:  Jeffrey T Leek; W Evan Johnson; Hilary S Parker; Andrew E Jaffe; John D Storey
Journal:  Bioinformatics       Date:  2012-01-17       Impact factor: 6.937

Review 2.  Attention deficit hyperactivity disorder.

Authors:  Marguerite Matthews; Joel T Nigg; Damien A Fair
Journal:  Curr Top Behav Neurosci       Date:  2014

3.  Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism.

Authors:  Zening Fu; Yiheng Tu; Xin Di; Yuhui Du; Jing Sui; Bharat B Biswal; Zhiguo Zhang; N de Lacy; V D Calhoun
Journal:  Neuroimage       Date:  2018-06-06       Impact factor: 6.556

4.  Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

Authors:  Raquel Iniesta; Karim Malki; Wolfgang Maier; Marcella Rietschel; Ole Mors; Joanna Hauser; Neven Henigsberg; Mojca Zvezdana Dernovsek; Daniel Souery; Daniel Stahl; Richard Dobson; Katherine J Aitchison; Anne Farmer; Cathryn M Lewis; Peter McGuffin; Rudolf Uher
Journal:  J Psychiatr Res       Date:  2016-04-01       Impact factor: 4.791

5.  Use of Machine Learning to Identify Children with Autism and Their Motor Abnormalities.

Authors:  Alessandro Crippa; Christian Salvatore; Paolo Perego; Sara Forti; Maria Nobile; Massimo Molteni; Isabella Castiglioni
Journal:  J Autism Dev Disord       Date:  2015-07

Review 6.  Diagnosis of autism spectrum disorder: reconciling the syndrome, its diverse origins, and variation in expression.

Authors:  John N Constantino; Tony Charman
Journal:  Lancet Neurol       Date:  2015-10-20       Impact factor: 44.182

7.  Association of Genetic Risk Variants With Attention-Deficit/Hyperactivity Disorder Trajectories in the General Population.

Authors:  Lucy Riglin; Stephan Collishaw; Ajay K Thapar; Søren Dalsgaard; Kate Langley; George Davey Smith; Evie Stergiakouli; Barbara Maughan; Michael C O'Donovan; Anita Thapar
Journal:  JAMA Psychiatry       Date:  2016-12-01       Impact factor: 21.596

8.  Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism.

Authors:  Colleen P Chen; Christopher L Keown; Afrooz Jahedi; Aarti Nair; Mark E Pflieger; Barbara A Bailey; Ralph-Axel Müller
Journal:  Neuroimage Clin       Date:  2015-04-09       Impact factor: 4.881

9.  Most genetic risk for autism resides with common variation.

Authors:  Trent Gaugler; Lambertus Klei; Stephan J Sanders; Corneliu A Bodea; Arthur P Goldberg; Ann B Lee; Milind Mahajan; Dina Manaa; Yudi Pawitan; Jennifer Reichert; Stephan Ripke; Sven Sandin; Pamela Sklar; Oscar Svantesson; Abraham Reichenberg; Christina M Hultman; Bernie Devlin; Kathryn Roeder; Joseph D Buxbaum
Journal:  Nat Genet       Date:  2014-07-20       Impact factor: 38.330

Review 10.  The conception of the ABCD study: From substance use to a broad NIH collaboration.

Authors:  Nora D Volkow; George F Koob; Robert T Croyle; Diana W Bianchi; Joshua A Gordon; Walter J Koroshetz; Eliseo J Pérez-Stable; William T Riley; Michele H Bloch; Kevin Conway; Bethany G Deeds; Gayathri J Dowling; Steven Grant; Katia D Howlett; John A Matochik; Glen D Morgan; Margaret M Murray; Antonio Noronha; Catherine Y Spong; Eric M Wargo; Kenneth R Warren; Susan R B Weiss
Journal:  Dev Cogn Neurosci       Date:  2017-10-10       Impact factor: 6.464

View more
  57 in total

1.  Which 'Working' Components of Working Memory aren't Working in Youth with ADHD?

Authors:  Whitney D Fosco; Michael J Kofler; Nicole B Groves; Elizabeth S M Chan; Joseph S Raiker
Journal:  J Abnorm Child Psychol       Date:  2020-05

Review 2.  Heterogeneity and Subtyping in Attention-Deficit/Hyperactivity Disorder-Considerations for Emerging Research Using Person-Centered Computational Approaches.

Authors:  Sarah L Karalunas; Joel T Nigg
Journal:  Biol Psychiatry       Date:  2019-11-09       Impact factor: 13.382

3.  Probing the overarching continuum theory: data-driven phenotypic clustering of children with ASD or ADHD.

Authors:  M K Deserno; J Bathelt; A P Groenman; H M Geurts
Journal:  Eur Child Adolesc Psychiatry       Date:  2022-06-10       Impact factor: 4.785

Review 4.  Beyond diagnoses and total symptom scores: Diversifying the level of analysis in psychoneuroimmunology research.

Authors:  Daniel P Moriarity; Lauren B Alloy
Journal:  Brain Behav Immun       Date:  2020-07-18       Impact factor: 7.217

Review 5.  Disentangling Heterogeneity in Alzheimer's Disease and Related Dementias Using Data-Driven Methods.

Authors:  Mohamad Habes; Michel J Grothe; Birkan Tunc; Corey McMillan; David A Wolk; Christos Davatzikos
Journal:  Biol Psychiatry       Date:  2020-01-31       Impact factor: 13.382

Review 6.  Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth.

Authors:  Antonia N Kaczkurkin; Tyler M Moore; Aristeidis Sotiras; Cedric Huchuan Xia; Russell T Shinohara; Theodore D Satterthwaite
Journal:  Biol Psychiatry       Date:  2019-12-23       Impact factor: 13.382

7.  Integration of brain and behavior measures for identification of data-driven groups cutting across children with ASD, ADHD, or OCD.

Authors:  Grace R Jacobs; Aristotle N Voineskos; Colin Hawco; Laura Stefanik; Natalie J Forde; Erin W Dickie; Meng-Chuan Lai; Peter Szatmari; Russell Schachar; Jennifer Crosbie; Paul D Arnold; Anna Goldenberg; Lauren Erdman; Stephanie H Ameis
Journal:  Neuropsychopharmacology       Date:  2020-11-09       Impact factor: 7.853

8.  Inflammatory phenotype of depression symptom structure: A network perspective.

Authors:  Daniel P Moriarity; Claudia van Borkulo; Lauren B Alloy
Journal:  Brain Behav Immun       Date:  2020-12-09       Impact factor: 7.217

Review 9.  A review of decreased sound tolerance in autism: Definitions, phenomenology, and potential mechanisms.

Authors:  Zachary J Williams; Jason L He; Carissa J Cascio; Tiffany G Woynaroski
Journal:  Neurosci Biobehav Rev       Date:  2020-12-04       Impact factor: 8.989

10.  Advancing preventive interventions for pregnant women who are opioid using via the integration of addiction and mental health research.

Authors:  Kristen L Mackiewicz Seghete; Alice M Graham; Taylor M Shank; Shelby L Alsup; Philip A Fisher; Anna C Wilson; Sarah W Feldstein Ewing
Journal:  Curr Addict Rep       Date:  2020-01-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.