Hippocampal Development Deviation and Its Relationship With Cognition in Major Psychiatric Disorders

QIAO Chun-xia, WEI Wei, DENG Li-hong, TAO Shi-wan, LI Tao

Abstract

To investigate hippocampal development deviation and its association with cognition in patients with major psychiatric disorders (MPDs), including schizophrenia, bipolar disorder and major depressive disorder.   Methods  The T1-weighted MRI data of 174 first-episode drug-naïve schizophrenia (FES) atients, 169 bipolar disorder (BD) patients, 184 major depressive disorder (MDD) patients, and 321 healthy controls were collected and their hippocampal volume was extracted after preprocessing with Freesurfer 5.3. A normative neurodevelopment model was applied to calculate the hippocampal deviation scores. Data on cognitive functions, including visual memory, attention, spatial working memory, were collected. Comparison by different sexes was made to identify difference between the hippocampal development deviation scores of the control group and those of the disease groups. We also investigated the moderating effect of age on the deviation score and explored the association between the deviation score and cognitive function.   Results  The hippocampal development deviation scores of patients with MPDs were significantly lower than those of the healthy controls (false discovery rate [FDR]-P<0.05). Analysis of the moderating effect of age revealed lower deviation scores in young patients (<[25.83-28.56] yr.) and higher deviation scores in old patients (>[35.87-54.35] yr.) in comparison with those of the healthy controls. The right hippocampal deviation scores in male FES patients were positively correlated with the number of errors for tasks concerning spatial working memory (r=0.32, FDR-P=0.04).   Conclusion  Our findings suggest abnormal hippocampal development in MPDs patients and its different distribution in MPDs patients of different age groups. The hippocampal development deviation score may provide a new perspective for further understanding of etiology in MPDs.

 

Keywords: Hippocampus, Normative neurodevelopment model, Deviation score, Cognition, Major psychiatric disorders

 

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References


ANAND K S， DHIKAV V. Hippocampus in health and disease: an overview. Ann Indian Acad Neurol，2012，15(4): 239–246. doi: 10.4103/ 0972-2327.104323.

GOMES F V， ZHU X， GRACE A A. Stress during critical periods of development and risk for schizophrenia. Schizophr Res，2019，2013: 107–113. doi: 10.1016/j.schres.2019.01.030.

DU PLESSIS S， SCHEFFLER F， LUCKHOFF H， et al. Childhood trauma and hippocampal subfield volumes in first-episode schizophrenia and healthy controls. Schizophr Res，2020，215: 308–313. doi: 10.1016/j. schres.2019.10.009.

TANTI A， WESTPHAL W P， GIRAULT V， et al. Region-dependent and stage-specific effects of stress, environmental enrichment, and antidepressant treatment on hippocampal neurogenesis. Hippocampus， 2013，23(9): 797–811. doi: 10.1002/hipo.22134.

MARTÍNEZ A L， BREA J， RICO S， et al. Cognitive deficit in schizophrenia: from etiology to novel treatments. Int J Mol Sci，2021， 22(18): 9905. doi: 10.3390/ijms22189905.

XU N， HUGGON B， SAUNDERS K E A. Cognitive impairment in patients with bipolar disorder: impact of pharmacological treatment. CNS Drugs，2020，34(1): 29–46. doi: 10.1007/s40263-019-00688-2.

ROCK P L， ROISER J P， RIEDEL W J， et al. Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med，2014， 44(10): 2029–2040. doi: 10.1017/S0033291713002535.

Van ERP T G， HIBAR D P， RASMUSSEN J M， et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol Psychiatry，2016， 21(4): 547–553. doi: 10.1038/mp.2015.63.

HIBAR D P， WESTLYE L T， Van ERP T G， et al. Subcortical volumetric abnormalities in bipolar disorder. Mol Psychiatry，2016，21(12): 1710–1716. doi: 10.1038/mp.2015.227.

SCHMAAL L， VELTMAN D J， Van ERP T G， et al. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry，2016，21(6): 806–812. doi: 10.1038/mp.2015.69.

KHALIL M， HOLLANDER P， RAUCHER-CHENE D， et al. Structural brain correlates of cognitive function in schizophrenia: a meta-analysis. Neurosci Biobehav Rev，2022，132: 37–49. doi: 10.1016/j.neubiorev.2021. 11.034.

SHI J， GUO H， LIU S， et al. Subcortical brain volumes relate to neurocognition in first-episode schizophrenia, bipolar disorder, major depression disorder, and healthy controls. Front Psychiatry，2021，12: 747386. doi: 10.3389/fpsyt.2021.747386.

PATEL V， DAN C， PARIKH R， et al. Addressing the burden of mental, neurological, and substance use disorders: key messages from Disease Control Priorities, 3rd edition. Lancet，2016，387(10028): 1672–1685. doi: 10.1016/S0140-6736(15)00390-6.

OWEN M J， O'DONOVAN M C， THAPAR A， et al. Neurodevelop-mental hypothesis of schizophrenia. Br J Psychiatry，2011，198(3): 173–175. doi: 10.1192/bjp.bp.110.084384.

RUTHERFORD S， FRAZA C， DINGA R， et al. Charting brain growth and aging at high spatial precision. eLife，2022，11: e72904. doi: 10.7554/eLife.72904.

COLE T J. The development of growth references and growth charts. Ann Hum Biol，2012，39(5): 382–394. doi: 10.3109/03014460.2012.694475.

BETHLEHEM R A I， SEIDLITZ J， WHITE S R， et al. Brain charts for the human lifespan. Nature，2022，604(7906): 525–533. doi: 10.1038/s41586-022-04554-y.

PINAYA W H L， MECHELLI A， SATO J R. Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: a large-scale multi-sample study. Hum Brain Mapp，2019，40(3): 944–954. doi: 10.1002/hbm.24423.

ZABIHI M， OLDEHINKEL M， WOLFERS T， et al. Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models. Biol Psychiatry Cogn Neurosci Neuroimaging，2019， 4(6): 567–578. doi: 10.1016/j.bpsc.2018.11.013.

FRAZA C J， DINGA R， BECKMANN C F， et al. Warped Bayesian linear regression for normative modelling of big data. Neuroimage，2021，245: 118715. doi: 10.1016/j.neuroimage.2021.118715.

DIMA D， MODABBERNIA A， PAPACHRISTOU E， et al. Subcortical volumes across the lifespan: data from 18, 605 healthy individuals aged 3-90 years. Hum Brain Mapp，2022，43(1): 452–469. doi: 10.1002/hbm. 25320.

ANNETT M. Hand preference observed in large healthy samples: classification, norms and interpretations of increased non-right-handedness by the right shift theory. Br J Psychol，2004，95(Pt 3): 339–353. doi: 10.1348/0007126041528130.

KAY S R， FISZBEIN A， OPLER L A. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull，1987，13(2): 261–276. doi: 10.1093/schbul/13.2.261.

HAMILTON M. A rating scale for depression. J Neurol Neurosurg Psychiatry，1960，23(1): 56–62. doi: 10.1136/jnnp.23.1.56.

YOUNG R C， BIGGS J T， ZIEGLER V E， et al. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry，1978，133(5): 429–435. doi: 10.1192/bjp.133.5.429.

SEGONNE F， DALE A M， BUSA E， et al. A hybrid approach to the Skull Stripping problem in MRI. Neuroimage，2004，22(3): 1060–1075. doi: 10.1016/j.neuroimage.2004.03.032.

FISCHL B， SALAT D H， BUSA E， et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron，2002，33(3): 341–355. doi: 10.1016/s0896-6273(02)00569-x.

DINGA R， FRAZA C J， BAYER J M， et al. Normative modeling of neuroimaging data using generalized additive models of location scale and shape. bioRxiv，2021. doi: 10.1101/2021.06.14.448106.

De LANGE A M G， COLE J H. Commentary: correction procedures in brain-age prediction. Neuroimage Clin，2020，26: 102229. doi: 10.1016/j. nicl.2020.102229.

KAUFMANN T， Van Der MEER D， DOAN N T， et al. Common brain disorders are associated with heritable patterns of apparent aging of the brain. Nat Neurosci，2019，22(10): 1617–1623. doi: 10.1038/s41593-019-0471-7.


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