Advertisement

Putamen Structure and Function in Familial Risk for Depression: A Multimodal Imaging Study

  • Ardesheer Talati
    Correspondence
    Address correspondence to Ardesheer Talati, Ph.D.
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Milenna T. van Dijk
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Lifang Pan
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Xuejun Hao
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Zhishun Wang
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Imaging, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Marc Gameroff
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Zhengchao Dong
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Jürgen Kayser
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
    Search for articles by this author
  • Stewart Shankman
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, Illinois
    Search for articles by this author
  • Priya J. Wickramaratne
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York

    Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York
    Search for articles by this author
  • Jonathan Posner
    Affiliations
    Department of Psychiatry, Duke University, Durham, North Carolina
    Search for articles by this author
  • Myrna M. Weissman
    Affiliations
    Department of Psychiatry, Columbia University Irving Medical Center and Vagelos College of Physicians and Surgeons, Columbia University, New York, New York

    Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York

    Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
    Search for articles by this author

      Abstract

      Background

      The putamen has been implicated in depressive disorders, but how its structure and function increase depression risk is not clearly understood. Here, we examined how putamen volume, neuronal density, and mood-modulated functional activity relate to family history and prospective course of depression.

      Methods

      The study includes 115 second- and third-generation offspring at high or low risk for depression based on the presence or absence of major depressive disorder in the first generation. Offspring were followed longitudinally using semistructured clinical interviews blinded to their familial risk; putamen structure, neuronal integrity, and functional activation were indexed by structural magnetic resonance imaging (MRI), proton magnetic resonance spectroscopy (N-acetylaspartate/creatine ratio), and functional MRI activity modulated by valence and arousal components of a mood induction task, respectively.

      Results

      After adjusting for covariates, the high-risk individuals had lower putamen volume (standardized betas, β-left = −0.17, β-right = −0.15, ps = .002), N-acetylaspartate/creatine ratio (β-left= −0.40, β-right= −0.37, ps < .0001), and activation modulated by valence (β-left = −0.22, β-right = −0.27, ps < .05) than low-risk individuals. Volume differences were greater at younger ages, and N-acetylaspartate/creatine ratio differences were greater at older ages. Lower putamen volume also predicted major depressive disorder episodes up to 8 years after the scan (β-left = −0.72, p = .013; β-right = −0.83, p = .037). Magnetic resonance spectroscopy and task functional MRI measures were modestly correlated (0.27 ≤ r ≤ 0.33).

      Conclusions

      Findings demonstrate abnormalities in putamen structure and function in individuals at high risk for major depressive disorder. Future studies should focus on this region as a potential biomarker for depressive illness, noting meanwhile that differences attributable to family history may peak at different ages based on which MRI modality is being used to assay them.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Biological Psychiatry
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Bolton J.M.
        • Pagura J.
        • Enns M.W.
        • Grant B.
        • Sareen J.
        A population-based longitudinal study of risk factors for suicide attempts in major depressive disorder.
        J Psychiatr Res. 2010; 44: 817-826
        • Rhee T.G.
        • Steffens D.C.
        Major depressive disorder and impaired health-related quality of life among US older adults.
        Int J Geriatr Psychiatry. 2020; 35: 1189-1197
        • Rasic D.
        • Hajek T.
        • Alda M.
        • Uher R.
        Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: A meta-analysis of family high-risk studies.
        Schizophr Bull. 2014; 40: 28-38
        • Sullivan P.F.
        • Neale M.C.
        • Kendler K.S.
        Genetic epidemiology of major depression: Review and meta-analysis.
        Am J Psychiatry. 2000; 157: 1552-1562
        • Pizzagalli D.A.
        Depression, stress, and anhedonia: Toward a synthesis and integrated model.
        Annu Rev Clin Psychol. 2014; 10: 393-423
        • Kempton M.J.
        • Salvador Z.
        • Munafò M.R.
        • Geddes J.R.
        • Simmons A.
        • Frangou S.
        • Williams S.C.
        Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder.
        Arch Gen Psychiatry. 2011; 68: 675-690
        • Koolschijn P.C.
        • van Haren N.E.
        • Lensvelt-Mulders G.J.
        • Hulshoff Pol H.E.
        • Kahn R.S.
        Brain volume abnormalities in major depressive disorder: A meta-analysis of magnetic resonance imaging studies.
        Hum Brain Mapp. 2009; 30: 3719-3735
        • Baumann B.
        • Danos P.
        • Krell D.
        • Diekmann S.
        • Leschinger A.
        • Stauch R.
        • et al.
        Reduced volume of limbic system-affiliated basal ganglia in mood disorders: Preliminary data from a postmortem study.
        J Neuropsychiatry Clin Neurosci. 1999; 11: 71-78
        • Auerbach R.P.
        • Pisoni A.
        • Bondy E.
        • Kumar P.
        • Stewart J.G.
        • Yendiki A.
        • Pizzagalli D.A.
        Neuroanatomical prediction of anhedonia in adolescents.
        Neuropsychopharmacology. 2017; 42: 2087-2095
        • Jing B.
        • Liu C.H.
        • Ma X.
        • Yan H.G.
        • Zhuo Z.Z.
        • Zhang Y.
        • et al.
        Difference in amplitude of low-frequency fluctuation between currently depressed and remitted females with major depressive disorder.
        Brain Res. 2013; 1540: 74-83
        • Surguladze S.
        • Brammer M.J.
        • Keedwell P.
        • Giampietro V.
        • Young A.W.
        • Travis M.J.
        • et al.
        A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder.
        Biol Psychiatry. 2005; 57: 201-209
        • Pagliaccio D.
        • Alqueza K.L.
        • Marsh R.
        • Auerbach R.P.
        Brain volume abnormalities in youth at high risk for depression: Adolescent brain and cognitive development study.
        J Am Acad Child Adolesc Psychiatry. 2020; 59: 1178-1188
        • Insel T.
        • Cuthbert B.
        • Garvey M.
        • Heinssen R.
        • Pine D.S.
        • Quinn K.
        • et al.
        Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders.
        Am J Psychiatry. 2010; 167: 748-751
        • Shankman S.A.
        • Gorka S.M.
        Psychopathology research in the RDoC era: Unanswered questions and the importance of the psychophysiological unit of analysis.
        Int J Psychophysiol. 2015; 98: 330-337
        • Duyn J.H.
        • Gillen J.
        • Sobering G.
        • van Zijl P.C.
        • Moonen C.T.
        Multisection proton MR spectroscopic imaging of the brain.
        Radiology. 1993; 188: 277-282
        • Weissman M.M.
        • Berry O.O.
        • Warner V.
        • Gameroff M.J.
        • Skipper J.
        • Talati A.
        • et al.
        A 30-year study of 3 generations at high risk and low risk for depression.
        JAMA Psychiatry. 2016; 73: 970-977
        • Weissman M.M.
        • Wickramaratne P.
        • Gameroff M.J.
        • Warner V.
        • Pilowsky D.
        • Kohad R.G.
        • et al.
        Offspring of depressed parents: 30 years later.
        Am J Psychiatry. 2016; 173: 1024-1032
        • Weissman M.M.
        • Wickramaratne P.
        • Nomura Y.
        • Warner V.
        • Pilowsky D.
        • Verdeli H.
        Offspring of depressed parents: 20 years later.
        Am J Psychiatry. 2006; 163: 1001-1008
        • van Dijk M.T.
        • Murphy E.
        • Posner J.E.
        • Talati A.
        • Weissman M.M.
        Association of multigenerational family history of depression with lifetime depressive and other psychiatric disorders in children: Results from the adolescent brain cognitive development (ABCD) study.
        JAMA Psychiatry. 2021; 78: 778-787
        • Weissman M.M.
        • Wickramaratne P.
        • Nomura Y.
        • Warner V.
        • Verdeli H.
        • Pilowsky D.J.
        • et al.
        Families at high and low risk for depression: A 3-generation study.
        Arch Gen Psychiatry. 2005; 62: 29-36
        • Schuff N.
        • Meyerhoff D.J.
        • Mueller S.
        • Chao L.
        • Sacrey D.T.
        • Laxer K.
        • Weiner M.W.
        N-acetylaspartate as a marker of neuronal injury in neurodegenerative disease.
        Adv Exp Med Biol. 2006; 576 (discussion 361–363): 241-262
        • Mannuzza S.
        • Fyer A.J.
        • Klein D.F.
        • Endicott J.
        Schedule for Affective Disorders and Schizophrenia—Lifetime Version modified for the study of anxiety disorders (SADS-LA): Rationale and conceptual development.
        J Psychiatr Res. 1986; 20: 317-325
        • Kaufman J.
        • Birmaher B.
        • Brent D.
        • Rao U.
        • Flynn C.
        • Moreci P.
        • et al.
        Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): Initial reliability and validity data.
        J Am Acad Child Adolesc Psychiatry. 1997; 36: 980-988
        • Leckman J.F.
        • Sholomskas D.
        • Thompson W.D.
        • Belanger A.
        • Weissman M.M.
        Best estimate of lifetime psychiatric diagnosis: A methodological study.
        Arch Gen Psychiatry. 1982; 39: 879-883
        • Weissman M.M.
        • Talati A.
        • Gameroff M.J.
        • Pan L.
        • Skipper J.
        • Posner J.E.
        • Wickramaratne P.J.
        Enduring problems in the offspring of depressed parents followed up to 38 years.
        EClinicalmedicine. 2021; 38101000
        • Tottenham N.
        • Weissman M.M.
        • Wang Z.
        • Warner V.
        • Gameroff M.J.
        • Semanek D.P.
        • et al.
        Depression risk is associated with weakened synchrony between the amygdala and experienced emotion.
        Biol Psychiatry Cogn Neurosci Neuroimaging. 2021; 6: 343-351
        • Dong Z.
        • Peterson B.
        The rapid and automatic combination of proton MRSI data using multi-channel coils without water suppression.
        Magn Reson Imaging. 2007; 25: 1148-1154
        • Hao X.
        • Xu D.
        • Bansal R.
        • Dong Z.
        • Liu J.
        • Wang Z.
        • et al.
        Multimodal magnetic resonance imaging: The coordinated use of multiple, mutually informative probes to understand brain structure and function.
        Hum Brain Mapp. 2013; 34: 253-271
        • Abedelahi A.
        • Hasanzadeh H.
        • Hadizadeh H.
        • Joghataie M.T.
        Morphometric and volumetric study of caudate and putamen nuclei in normal individuals by MRI: Effect of normal aging, gender and hemispheric differences.
        Pol J Radiol. 2013; 78: 7-14
        • McDonald W.M.
        • Husain M.
        • Doraiswamy P.M.
        • Figiel G.
        • Boyko O.
        • Krishnan K.R.
        A magnetic resonance image study of age-related changes in human putamen nuclei.
        NeuroReport. 1991; 2: 57-60
        • Holmans P.
        • Weissman M.M.
        • Zubenko G.S.
        • Scheftner W.A.
        • Crowe R.R.
        • Depaulo J.R.
        • et al.
        Genetics of recurrent early-onset major depression (GenRED): Final genome scan report.
        Am J Psychiatry. 2007; 164: 248-258
        • Auerbach R.P.
        • Pagliaccio D.
        • Pizzagalli D.A.
        Toward an improved understanding of anhedonia.
        JAMA Psychiatry. 2019; 76: 571-573
        • Schaub A.C.
        • Kirschner M.
        • Schweinfurth N.
        • Mählmann L.
        • Kettelhack C.
        • Engeli E.E.
        • et al.
        Neural mapping of anhedonia across psychiatric diagnoses: A transdiagnostic neuroimaging analysis.
        NeuroImage Clin. 2021; 32102825
        • Colibazzi T.
        • Posner J.
        • Wang Z.
        • Gorman D.
        • Gerber A.
        • Yu S.
        • et al.
        Neural systems subserving valence and arousal during the experience of induced emotions.
        Emotion. 2010; 10: 377-389
        • Lane R.D.
        • Chua P.M.
        • Dolan R.J.
        Common effects of emotional valence, arousal and attention on neural activation during visual processing of pictures.
        Neuropsychologia. 1999; 37: 989-997
        • Lewis P.A.
        • Critchley H.D.
        • Rotshtein P.
        • Dolan R.J.
        Neural correlates of processing valence and arousal in affective words.
        Cereb Cortex. 2007; 17: 742-748
        • Duckworth A.L.
        • Kern M.L.
        A meta-analysis of the convergent validity of self-control measures.
        J Res Pers. 2011; 45: 259-268
        • Eisenberg I.W.
        • Bissett P.G.
        • Zeynep Enkavi A.
        • Li J.
        • MacKinnon D.P.
        • Marsch L.A.
        • Poldrack R.A.
        Uncovering the structure of self-regulation through data-driven ontology discovery.
        Nat Commun. 2019; 10: 2319
        • Peng Y.
        • Knotts J.D.
        • Taylor C.T.
        • Craske M.G.
        • Stein M.B.
        • Bookheimer S.
        • et al.
        Failure to identify robust latent variables of positive or negative valence processing across units of analysis.
        Biol Psychiatry Cogn Neurosci Neuroimaging. 2021; 6: 518-526
        • Shengli C.
        • Yingli Z.
        • Zheng G.
        • Shiwei L.
        • Ziyun X.
        • Han F.
        • et al.
        An aberrant hippocampal subregional network, rather than structure, characterizes major depressive disorder.
        J Affect Disord. 2022; 302: 123-130
        • Dima D.
        • Modabbernia A.
        • Papachristou E.
        • Doucet G.E.
        • Agartz I.
        • Aghajani M.
        • et al.
        Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years.
        Hum Brain Mapp. 2022; 43: 452-469
        • Harvey P.O.
        • Pruessner J.
        • Czechowska Y.
        • Lepage M.
        Individual differences in trait anhedonia: A structural and functional magnetic resonance imaging study in non-clinical subjects.
        Mol Psychiatry. 2007; (12:12(8):703, 67–75)
        • Pizzagalli D.A.
        • Holmes A.J.
        • Dillon D.G.
        • Goetz E.L.
        • Birk J.L.
        • Bogdan R.
        • et al.
        Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder.
        Am J Psychiatry. 2009; 166: 702-710

      Linked Article

      • Risk Markers Are Not One Size Fits All
        Biological PsychiatryVol. 92Issue 12
        • Preview
          Identifying risk markers for depression has long been an elusive goal in psychiatric research. These efforts have been undertaken using a variety of methods investigating environmental, genetic, physiological, and neural candidate markers (1–4). The search for useful and valid risk markers for depression has been plagued by small sample sizes, inconsistent effects, and likely overestimated effect sizes. Even large consortia formed to overcome issues of low statistical power in this endeavor have yet to identify large and replicable effects when seeking neural markers of depression.
        • Full-Text
        • PDF