Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults

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Official Journal of the European Paediatric Neurology Society

Original article

Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults Knut J. Bjuland a,*, Lars M. Rimol a, Gro C.C. Løhaugen a,b, Jon Skranes a,b a

Department of Laboratory Medicine, Children’s and Women’s Health, Norwegian University of Science and Technology, Olav Kyrres gt. 11, N-7489 Trondheim, Norway b Department of Pediatrics, Sørlandet Hospital, 4809 Arendal, Norway

article info

abstract

Article history:

Background: Preterm born very-low-birth-weight (VLBW: birth weight
1500 g) survivors

Received 5 October 2013

have increased risk of perinatal brain injury that may cause deviant brain development

Received in revised form

and later neuroimpairments, including reduced cognitive functioning.

12 February 2014

Aims: In this long-term follow up study of three year-cohorts (birth years 1986e88) of VLBW

Accepted 4 April 2014

subjects and term born controls with normal birth weight, the aim was to examine differences in brain volumes at age 20 years. In addition, the relationships between brain

Keywords:

volumes and cognitive abilities and perinatal variables were explored.

Very-low-birth-weight (VLBW)

Methods: Forty-four VLBW subjects and 60 controls were assessed with cognitive testing

Cerebral MRI

(Wechsler Adult Intelligence Scale e WAIS-III) and structural MRI at 1.5 T, using the

Cognition

FreeSurfer 5.1 software for volumetric analysis. A subpopulation had MRI performed also at

Brain volumes

age 15, and for this group changes in brain volumes with age were examined.

Young adulthood

Results: The VLBW subjects had smaller brain volumes, especially of thalamus, globus

Preterm birth

pallidus and parts of the corpus callosum, and larger lateral ventricles than controls at age 20. However, no significant group differences in longitudinal change from age 15 to 20 were observed. The most immature and smallest VLBW subjects at birth, and those with the highest perinatal morbidity, showed most pronounced volume deviations. Positive associations between several brain volumes and full IQ, as well as three of four IQ indices in the VLBW group, were observed. Conclusion: Reduced volumes of grey and white matter and ventricular dilatation in VLBW young adults may indicate permanent effects on brain development from perinatal brain injury with influence on later cognitive function. ª 2014 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

1.

Introduction

Children born preterm with very low birth weight (VLBW: birth weight
1500 g) are prone to perinatal brain injuries that

affect normal brain development, resulting in gray and white matter abnormalities.1,2 These perinatal brain injuries may be caused by periventricular leukomalacia (PVL), either as focal, periventricular lesions or in a diffuse form with widespread white matter involvement, including diffuse gliosis and

* Corresponding author. Tel.: þ47 928 35 718. E-mail addresses: [email protected], [email protected] (K.J. Bjuland). http://dx.doi.org/10.1016/j.ejpn.2014.04.004 1090-3798/ª 2014 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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axonal damage, which may affect the microstructural integrity of white matter and tract connectivity.3 Cerebral cortical and deep gray matter and cerebellum may also be involved in preterm perinatal brain injury either directly or secondary to white matter injury.4e7 Several studies have investigated perinatal brain injuries in VLBW survivors using quantitative MRI, reporting reduced volumes of the cerebral cortex, myelinated white matter and deep nuclear structures in VLBW/very preterm born (VPT: gestational age <32 week) infants related to the degree of immaturity at birth and to concomitant white matter injury.8 In addition, smaller hippocampal volume in VLBW/VPT children,9,10 and increased volumes of the lateral ventricles in VPT children10 compared to term born controls have been reported. A recent meta-analysis summarized such findings in preterm born VLBW/VPT survivors as smaller total brain volume, and reduced volumes of cerebral gray and white matter, hippocampus, cerebellum and corpus callosum compared to term born controls.11 Reported findings in VLBW/VPT young adults include enlarged ventricles12e14 and total gray matter and white matter reduction,14,15 and reduced volumes of thalamus and right putamen.16 Widespread deviations in white matter microstructure and organization14,17 have been found, also in areas that appeared normal on conventional MRI. These deviations were related to birth weight and number of days on mechanical ventilator.17 Longitudinal age-related change in brain volume has been studied from childhood to young adulthood in healthy individuals with reported increase in white matter and preadolescent increase followed by post-adolescent decrease in gray matter volume.18 Cerebral white matter volume seems to increase more rapidly than cerebral gray matter volume in healthy subjects from childhood to pre-adolescence.19 These findings have been extended in a meta-study, which summarized 56 longitudinal MRI studies with an age range from five to 88 years and found that total brain volume seems to peak at age 13 follow by a decline in volume from age 35 years, while white matter volume increases until 45 years of age in healthy subjects.20 Brain volume changes from childhood to adolescence have also been described in VLBW subjects but results have been conflicting as to whether these changes differ from or are equal to what is found in age-matched controls.11,21 Few studies have investigated the change in volumes from adolescence to young adulthood in preterm born survivors, but similar decrease in gray matter and increase in white matter within this age group has been reported for those born very preterm (VPT) and term born controls.15 However, Parker et al. reported decreased cerebellum volume and Allin et al. found increased corpus callosum volume in VPT compared to term born controls from adolescents to young adulthood.15,22 The perinatal brain injuries observed in VLBW survivors may influence cognitive development and performance.1,11 In a meta-analysis of neurobehavioral outcomes in very preterm (VPT) and/or VLBW children deficits in academic achievement, attention and executive function problems, and behavioral problems were reported, and the adverse outcomes were strongly correlated to degree of immaturity at birth.23 The authors claimed that these children continue to lag behind term-born peers when entering into young adulthood. Reduced academic performance, attention/executive

problems, and more internalizing behavior have also been reported for VPT/VLBW young adults.23 Already in 2000, Ajayi-Obe et al. reported reduced cortical development with less cortical surface area and in extremely preterm infants at term-equivalent age and suggested that this could explain later neurocognitive impairments.24 Increasing prematurity has been associated with reduced cortical surface area in relation to cerebral volume,24 and even modest decreases in the duration of gestation seem to exert profound and lasting effects on neurodevelopment for both term and preterm infants.25,26 In a recent study, abnormal early brain maturation in preterm born neonates was associated with adverse developmental outcomes at 18 months’ corrected age,27 while Clark et al. found that reduced brain volumes, especially of white matter structures persisted into late adolescence in ELBW and VLBW subjects, and were related to reduced academic achievement, probably caused by disturbed connectivity.28 We have followed a three-year cohort of VLBW children and age-matched controls from birth into adulthood, including follow-up at age 14e15 years. We found areas with thinner cerebral cortex, smaller cortical and subcortical structure volumes, and disturbed white matter microstructure, which were related to cognitive and behavioral impairments.3,29e33 Moreover, when we reassessed the VLBW cohorts as young adults, we found that deviations in cortical thickness, surface area reduction, and the lower fractional anisotropy values seen in white matter tracts were related to reduced IQ scores.17,34,35 The aim of present study was to investigate the long-term effects of perinatal brain injuries on brain volumes in VLBW young adults. We also wanted to study the longitudinal change in brain volumes from age 15e20 years in the same study population. Finally, we wanted to relate brain volumes at age 20 to cognitive functioning and perinatal risk factors. We hypothesized that the VLBW subjects would have deviations in brain volumes compared to term born controls, but that developmental trajectories for brain volumes from adolescence to young adulthood would be similar in both groups. We hypothesized that the deviations in brain volumes would relate to cognitive deficits and perinatal risk factors within the VLBW group.

2.

Materials and methods

We performed a hospital based follow-up study of three year cohorts (birth years 1986e88) of subjects born preterm with VLBW (birth weight
1500 g) and a term born control group with normal birth weight (birth weight >10th percentile) at 15 and 20 years of age. Inclusion criteria and results from the multidisciplinary assessments and cerebral MRI at age 15 have been published before.3,29e33,36,37

2.1.

VLBW group

In 1986e88, 121 children with very low birth weight (VLBW: Birth weight
1500 g) were admitted to the Neonatal Intensive Care Unit at the University Hospital in Trondheim. Of these, 33 children died, six were lost to follow up, and one child with

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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Down’s syndrome was excluded for follow-up (Fig. 1). Of 81 eligible subjects for follow-up, 21 did not consent, three had moved and two with severe cerebral palsy (CP) were excluded due to inability to perform the neuropsychological tests. Fifty of 55 young adults born preterm with VLBW agreed to cerebral MRI at age 20. We had to reject the MRI scan of four subject due to motion artifacts, and two other subjects were excluded from the study due to lack of cognitive assessment. This resulted in 44 VLBW subjects for inclusion in the analysis. Thirty-one of the 44 VLBW young adults (70%) also had acceptable MRI scans performed at age 15 years (Fig. 1). Birth weight, gestational age and perinatal risk factors like Apgar scores, number of days on mechanical ventilator and total days of stay in the NICU were registered. There were two VLBW young adults with cerebral palsy classified as grade IeII according to Gross Motor Function Classification System (GMFC) participating in the study.

2.2.

Controls

The term born controls were born at the St. Olav University hospital in Trondheim, Norway to mothers living in the Trondheim region, who were enrolled before week 20 of

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pregnancy in a multicenter study between January 1986 and March 1988. A 10% random sample of women (para 1 and 2) was selected for follow-up during pregnancy. At birth, 122 children with birth weight 10th centile for gestational age from the random sample were included for follow-up as controls. At 19e20 years follow up, ten had moved and two were excluded due to severe medical conditions. Of the remaining 110 young adults, 66 met for cognitive testing and cerebral MRI at age 20. Six participants had to be rejected from analysis due to MRI artifacts caused by dental braces and motion or lack of concomitant cognitive assessment. This resulted in 60 participating controls with both cognitive assessment and MRI examination, of these 37 controls (62%) had successful MRI at age 15 years.

2.3.

Non-participants

There were no significant differences in maternal age at birth, birth weight and gestational age between participants and non-participants within each group.38

2.4.

Socio-economic status

We used the Hollingshead’s Two Factor index of Social position to calculate Socio-economic status (SES) based on education and occupation of one parent or the mean index of both parents.39 Missing SES was dealt with by imputation of mean SES value from each group, respectively.

2.5.

Cognitive assessment

A full Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III) was administered to all participants at age 19e20 years.40 The Full IQ score is based upon the results of eleven subtests that constitute four IQ indices: Verbal Comprehension, Perceptual Organization, Working Memory and Processing Speed. We used age appropriate norms from the US standardization to calculate IQ and index scores. Low IQ was defined as scores more than minus one standard deviation (sd) from the mean score in the control group. We defined cognitive disability as scores more than minus two sd from the term born controls’ mean score.

2.6.

MR imaging

2.6.1.

Image acquisition

MRI was performed on a 1.5 T Siemens Magnetom Symphony with Quantum gradients (30 mT/m) and a quadrature head coil. A structural T1-weighted magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence was acquired with the following specifications: TR ¼ 7.1 ms, TE ¼ 3.45 ms, TI ¼ 1000 ms, flip angle 7 , FOV 256  256, slab thickness 170 mm, slice thickness 1.33 mm, acquisition matrix 256  192  128, reconstructed to 256  256  128, giving a reconstructed voxel resolution of 1  1  1.33 mm, and acquisition duration of 8.5 min.

2.6.2. Fig. 1 e Consort chart that illustrates the composition of the VLBW group at the two measurement points.

Image analysis

Two MPRAGE sequences acquired at each time point (14e15 and 19e20 years) were registered to correct for head motion

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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and averaged into a single image. Volumetric segmentation and cortical reconstruction were performed with FreeSurfer image analysis suite version 5.3.0, which is documented and freely available for download online (https://surfer.nmr.mgh. harvard.edu/), on the Abel Cluster, owned by the University of Oslo and the Norwegian metacenter for High Performance Computing (NOTUR), and operated by the Research Computing Services group at USIT, the University of Oslo ITdepartment (http://www.hpc.uio.no). The technical details of the FreeSurfer processing procedures are described in prior publications.41e51 Briefly, this processing includes motion correction and averaging52 of multiple volumetric T1 weighted images, removal of non-brain tissue using a hybrid watershed/surface deformation procedures,50 automated Talairach transformation, intensity normalization,53 segmentation of subcortical white matter and deep gray matter volume (including hippocampus, amygdala, caudate, putamen, ventricles),45,46 and parcellation of the cerebral cortex based on structural information.47,54 For each subject at each time point, subcortical brain structure volumes, as well as cerebral cortical gray matter, cerebral white matter estimated intracranial volume (eICV), were obtained from the automated procedures for volumetric measures of brain structure implemented in FreeSurfer. The volumes of specific subcortical structures in each hemisphere were added together, resulting in the following dependent variables: hippocampus, amygdala, thalamus, lateral ventricle, caudate nucleus, putamen, globus pallidus, and nucleus accumbens. In addition, corpus callosum and cerebellar gray and white matter volumes were used as dependent variables. In order to investigate longitudinal research questions, all images where processed with the longitudinal stream in FreeSurfer.55 Specifically, an unbiased within-subject template space and image56 are created using robust, inverse consistent registration.52 Several processing step such as skull striping, Talairach transformations, atlas registration as well as spherical surface maps and parcellations are then initialized with common information from the within-subject template, significantly increasing reliability and statistical power.55 This approach allows for unbalanced time points.57,58 In the present study, 36 subjects had scans only at 19e20 years, in most case either because the subject moved too much or had braces at age 14e15 years, and only one subject had scans only at 14e15 years.

2.7.

analysis, as implemented in FreeSurfer 5.3.0.57 The following model was fitted y ¼ intercept þ centered age þ group þ group  centered age þ gender; where centered age ¼ ¼ [age for each unique scanning session e mean age]. Intercept was the random factor. In a separate model, centered age was used as random factor. The two models were compared for goodness of fit with the maximum likelihood test described in Ref. 57, and the model with intercept as random factor showed the best fit (data not shown). The following research questions were investigated with lme: 1. Is the change in brain morphology between tp1 and tp2 different in healthy controls and the very-low-birthweight group? This was done by testing for an interaction between centered age and group (Contrast vector: 0 0 0 1 0). 2. Is there an effect of time in each group? If the interaction test in 1) were non-significant, the trajectories over time of the control group and the VLBW group would tend toward being parallel. Under these circumstances, it would be sufficient to test for the effect of centered age i.e. change over time in the control group: (Contrast vector: 0 1 0 0 0). If, however, there were a significant interaction between centered age/time and group, it would also be appropriate to conduct a separate test for change over time in the VLBW group: (Contrast vector: 0 1 0 1 0). All analyses were performed both with and without ICV as a (time-invariant) covariate, with the ICV regressor scaled down by a factor of one million. In addition, simple GLMs were performed to test for group differences ICV. To look at the associations between IQ measurements and brain volumes, we used partial correlations controlling for gender and SES, and these analyses were repeated controlling also for total intracranial volume. The two VLBW subjects with cerebral palsy were excluded from the correlation analysis of IQ measurements and brain volumes. The relationships between brain volumes and perinatal variables were also explored with partial correlations. We controlled for gender and age at MRI for all perinatal risk factors, and controlled for gestational age at birth when looking at the relationship between brain volumes and days in NICU and days on mechanical ventilator, respectively. To compensate for multiple comparisons in the volumetric analyses, Bonferroni corrections were applied within each analysis. This changed the significance threshold from p < 0.05 to p < 0.0025.

Statistics 2.8.

The software package IBM SPSS 20 and Matlab 2011b were used for statistical analysis. We used Student’s t-test to compare clinical characteristics between groups and Chisquare test to compare the gender distribution within each group. We used a general linear model (GLM) to compare group differences in brain volumes between the VLBW participants and term born controls, adjusted for gender and age at MRI. In addition, group differences were examined with GLM, controlling for gender, age at MRI and total intracranial volume. All subcortical brain structure volumes and cortical gray and white matter volumes, from time point 1 (tp1: 14e15 years) and time point 2 (tp2: 19e20 years), were analyzed with Linear Mixed Effects Models (lme) for longitudinal data

Ethics

The Regional Committee for Medical Research Ethics (Norwegian Health Region IV) approved the study protocol (project number: 4.2005.2605), and each subject gave a written informed consent to participate.

3.

Results

As expected, birth weight and gestational age were significantly lower in the VLBW group than in controls (Table 1). There were no differences in gender distribution, age at MRI or socio-economic status between groups. The VLBW young

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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Table 1 e Clinical characteristics of 104 young adults aged 20 years born preterm with very-low-birth-weight (VLBW) (n [ 44) and term born controls (n [ 60).

Birth weight (g) Gestational age (weeks) Gender (males/females) Days in NICU (n ¼ 43) Days on mechanical ventilator (n ¼ 42) Full Scale IQ Verbal comprehension index Working memory index Perceptional organization index Processing speed index Age at MRI (years) Socio-economic status

VLBW (n ¼ 44) mean (95 ci)

Control (n ¼ 60) mean (95 ci)

p Value

1213 (1141e1284) 29.3 (28.5e30) 18/26 76.4 (23e386)a 4.8 (0e63)a 89 (85e93) 91 (88e95) 83 (79e87) 97 (92e102) 91 (87e96) 20.1 (19.9e20.4) 3.4 (3e3.8)

3698 (3569e3828) 39.7 (39.4e40) 25/35 e e 100 (97e103) 98 (95e101) 92 (89e95) 108 (105e111) 100 (96e103) 20.3 (20.2e20.5) 3.7 (3.5e4)

<0.001 <0.001 0.938

<0.001 0.004 0.001 <0.001 0.003 0.132 0.133

Student’s t-test, Chi-square test, Significant p-values < 0.05 in bold. Abbreviations: ci: confidence interval; MRI: magnetic resonance imaging; IQ: Intelligence Quotient; NICU: neonatal intensive care. a Range.

adults had lower IQ scores than controls at age 20 years. We found a significantly higher IQ in males compared to females within the control group, with no gender difference in the VLBW group (data not shown). The clinical characteristics for the subpopulation that had MRI both at 15 and 20 years of age are presented in Supplemental Table 1S. There were no differences in gender distribution, age at MRI or socio-economic status between these groups, and there was no group difference in time interval between MRI at 15 and 20 years of age (data not shown).

3.1.

only larger brain structure in the VLBW group was the lateral ventricle (Table 2). When we compared the volumes between groups after also controlling for total intracranial volume, we found significant reduction of thalamus, caudate nucleus, globus pallidus, cerebellar white matter volume, central and mid posterior parts of the corpus callosum, and enlargement of lateral ventricle in the VLBW young adults (Table 3 and Fig. 2). Males had larger brain volumes than females in both groups, with the most pronounced gender differences found in the control group (Supplemental Tables 2S and 3S).

Brain volumes at age 20 years

Most brain structures had significantly reduced volumes at 20 years in the VLBW subjects compared to controls except for putamen and anterior corpus callosum (Table 2). The

3.1.1. Changes in brain volumes from age 15e20 years in the two study groups There was no significant interaction between time and group. In other words, the change in brain morphology from age 15 to

Table 2 e Absolute brain volumes for VLBW (n [ 44) and term born control (n [ 60) young adults at age 20 years. Brain volumes (in cm3)

Total intracranial volume Cerebral cortical gray matter Cerebral white matter Hippocampus Amygdala Thalamus Lateral ventricle Caudate nucleus Putamen Globus pallidus Nucleus accumbens Cerebellar gray matter Cerebellar white matter Corpus callosum anterior Corpus callosum mid anterior Corpus callosum central Corpus callosum mid posterior Corpus callosum posterior

VLBW

Controls

Mean

(95% ci)

Mean

(95% ci)

1525.99 483.18 439.12 7.09 3.13 13.17 26.15 7.35 12.23 3.42 1.36 98.44 26.23 0.83 0.41 0.36 0.33 0.79

(1486.98e1564.99) (470.14e496.21) (424.1e454.14) (6.87e7.31) (3.02e3.23) (12.76e13.58) (23e29.3) (7.06e7.63) (11.84e12.63) (3.28e3.56) (1.29e1.42) (95.84e101.04) (25.21e27.24) (0.78e0.88) (0.38e0.43) (0.34e0.38) (0.3e0.35) (0.74e0.84)

1617.52 515.74 473.21 7.71 3.37 15.19 14.37 8.28 12.96 3.84 1.54 105.41 29.67 0.92 0.47 0.43 0.42 0.92

(1584.19e1650.86) (504.6e526.88) (460.38e486.05) (7.52e7.9) (3.28e3.46) (14.84e15.54) (11.68e17.06) (8.04e8.52) (12.63e13.3) (3.72e3.95) (1.49e1.59) (103.19e107.63) (28.8e30.54) (0.88e0.96) (0.45e0.49) (0.41e0.45) (0.4e0.44) (0.88e0.97)

p Value 0.001 <0.001 0.001 <0.001 0.001 <0.001 <0.001 <0.001 0.007 <0.001 <0.001 <0.001 <0.001 0.006 <0.001 <0.001 <0.001 <0.001

General linear model with group as fixed factor, gender and age at MRI scan as covariates. Significant p-values (Bonferroni-adjusted threshold: 0.0025) are shown in bold font. Abbreviations: VLBW: very-low-birth-weight; ci: confidential interval; MRI: magnetic resonance imaging.

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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Table 3 e Comparison of brain volumes controlled for ICV in VLBW (n [ 44) and term born control (n [ 60) young adults at age 20 years. Brain volumes (in cm3)

Cerebral cortical gray matter Cerebral white matter Hippocampus Amygdala Thalamus Lateral ventricle Caudate nucleus Putamen Globus pallidus Nucleus accumbens Cerebellar gray matter Cerebellar white matter Corpus callosum anterior Corpus callosum mid anterior Corpus callosum central Corpus callosum mid posterior Corpus callosum posterior

VLBW

Controls

Mean

(95% ci)

Mean

(95% ci)

497.84 456.31 7.28 3.19 13.55 27.43 7.59 12.55 3.52 1.39 100.49 27.04 0.86 0.42 0.37 0.34 0.82

(490.28e505.4) (447.95e464.67) (7.1e7.46) (3.1e3.29) (13.25e13.86) (24.3e30.56) (7.36e7.82) (12.22e12.88) (3.4e3.64) (1.33e1.45) (98.29e102.69) (26.19e27.9) (0.82e0.9) (0.4e0.45) (0.35e0.39) (0.31e0.36) (0.77e0.87)

504.99 460.61 7.58 3.32 14.91 13.43 8.1 12.73 3.76 1.51 103.9 29.07 0.89 0.46 0.43 0.41 0.9

(498.59e511.39) (453.53e467.69) (7.42e7.73) (3.24e3.41) (14.65e15.16) (10.78e16.08) (7.91e8.29) (12.45e13.01) (3.66e3.87) (1.46e1.56) (102.04e105.77) (28.34e29.79) (0.86e0.93) (0.44e0.48) (0.41e0.44) (0.39e0.44) (0.86e0.94)

p Value

0.169 0.453 0.017 0.065 <0.001 <0.001 0.002 0.430 0.004 0.003 0.025 0.001 0.294 0.035 0.001 0.000 0.027

General linear model with group as fixed factor, gender, age at MRI, and total intracranial volume as covariates. Significant p-values (Bonferroni-adjusted threshold: 0.0025) are shown in bold font. Abbreviations: ICV: total intracranial volume; VLBW: very-low-birth-weight; ci: confidential interval.

20 was not different in healthy controls compared to the very low birth weight group. However, there was a nominally significant trend in the lateral ventricle (F ¼ 7.4575, effect size ¼ 121.66, DF¼(1.00,65.21) p ¼ 0.008), which did not survive Bonferroni correction. The effect of time was significant in several subcortical structures as well as cortical gray and white matter in both groups (see Table 4). There were significant decreases in the volumes of cerebral cortical gray matter, basal ganglia, and cerebellar gray matter from age 15e20 years in both groups. We also found increased volumes of cerebral white matter, the lateral ventricle (VLBW group only),

and most parts of the corpus callosum, while hippocampal, amygdala and thalamic volumes did not change over time. Including estimated intracranial volume as a covariate did not significantly change the outcome of any analysis (data not shown).

3.2. Relationship between brain volumes and IQ for the VLBW young adults We found positive associations between several brain volumes and Full IQ in the VLBW young adults when controlling

Fig. 2 e Segmented color-coded subcortical grey matter nuclei and hippocampus in a VLBW young adult.

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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Table 4 e Longitudinal change in brain volumes from age 15e20 years within each study group. Brain volumes

VLBW group

Cerebral cortical gray matter Cerebral white matter Hippocampus Amygdala Thalamus Lateral ventricle Caudate nucleus Putamen Globus pallidus Nucleus accumbens Cerebellar gray matter Cerebellar white matter Corpus callosum anterior Corpus callosum mid anterior Corpus callosum central Corpus callosum mid posterior Corpus callosum posterior

Controls

F

Effect sizea

df

p

F

Effect sizea

df

p

39.278 31.39 0.294 6.548 4.813 36.476 34.8 50.182 2.269 8.336 25.596 28.945 13.914 42.782 31.115 1.828 54.968

5413.8 1376.21 5.51 16.431 35.829 194.826 38.422 95.823 11.372 9.203 427.35 215.601 4.747 4.306 4.027 1.353 8.87

(1.00,67.22) (1.00,65.12) (1.00,66.23) (1.00,67.35) (1.00,65.98) (1.00,65.24) (1.00,65.32) (1.00,65.68) (1.00,66.64) (1.00,66.56) (1.00,65.66) (1.00,65.97) (1.00,65.42) (1.00,65.40) (1.00,65.57) (1.00,65.80) (1.00,65.31)

<0.001 <0.001 0.589 0.013 0.032 <0.001 <0.001 <0.001 0.137 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 0.181 <0.001

63.374 46.86 2.09 9.277 1.666 5.698 38.76 71.843 4.047 18.906 14.718 22.043 4.443 33.872 31.434 2.892 41.046

6504.5 1598.2 13.925 18.493 19.993 73.166 38.523 108.83 14.386 13.129 307.62 178.47 2.547 3.64 3.843 1.614 7.282

(1.00,68.71) (1.00,65.21) (1.00,67.07) (1.00,68.94) (1.00,66.66) (1.00,65.40) (1.00,65.54) (1.00,66.16) (1.00,67.75) (1.00,67.62) (1.00,66.11) (1.00,66.64) (1.00,65.71) (1.00,65.68) (1.00,65.96) (1.00,66.35) (1.00,65.53)

<0.001 <0.001 0.153 0.003 0.201 0.020 <0.001 <0.001 0.048 <0.001 <0.001 <0.001 0.039 <0.001 <0.001 0.094 <0.001

FreeSurfer 5.3.0 longitudinal stream. Linear mixed effects models. Abbreviations: VLBW: very-low-birth-weight; DF: degrees of freedom. Significant correlations (Bonferroni-adjusted threshold: 0.0025) are shown in bold font. a Effect size is calculated by multiplying the contrast vector with the vector of beta values.

for SES and gender, even after correction for multiple comparisons (Table 5). These included cerebral cortical grey and white matter, hippocampus, amygdala, thalamus, basal ganglia, cerebellar white matter and posterior corpus

Table 5 e Partial correlations between absolute brain volumes and Full scale IQ and IQ indices for the non-CP VLBW young adults at age 20 years (n [ 43). Brain volumes

Full IQ

VCI

WMI

POI

PSI

Total intracranial volume Cerebral cortical gray matter Cerebral white matter Hippocampus Amygdala Thalamus Caudate Putamen Globus pallidus Cerebellar gray matter Cerebellar white matter Corpus callosum anterior Corpus callosum posterior

0.555***

0.437**

0.543***

0.478***

0.480***

0.541***

0.362*

0.545***

0.524***

0.492***

0.534***

0.331*

0.489***

0.548***

0.506***

0.558*** 0.470*** 0.619*** 0.460*** 0.552*** 0.479*** 0.394*

0.279 0.246 0.440** 0.367* 0.388* 0.267 0.316*

0.407** 0.355* 0.500*** 0.503*** 0.421** 0.465*** 0.273

0.662*** 0.541*** 0.619*** 0.369* 0.565*** 0.481*** 0.365*

0.519*** 0.358* 0.548*** 0.361* 0.557*** 0.565*** 0.488***

0.497***

0.302

0.391*

0.542***

0.507***

0.441**

0.320*

0.391*

0.464***

0.310*

0.476***

0.293

0.477***

0.468***

0.395*

*p
0.05, **p
0.01, ***p
0.0025. Significant correlations (Bonferroni-adjusted threshold: 0.0025) are shown in bold font. Partial correlations controlled for SES and gender (IQ score is already corrected for age). Abbreviations: VLBW: very-low-birth-weight; IQ: Intelligence Quotient; CP: cerebral palsy; VCI: Verbal comprehension index; WMI: Working memory index; POI: Perceptual organization index; PSI: Processing speed index.

callosum. When looking at IQ indices in the non-disabled VLBW group, there were no significant associations between the verbal comprehensive index and brain volumes. We found significant associations between the working memory index and volumes of cerebral cortical gray and white matter, thalamus, parts of basal ganglia and posterior corpus callosum. Positive correlations were found between the perceptual organization index and several brain volumes, including volumes of cerebral cortical gray matter, cerebral and cerebellar white matter, hippocampus, amygdala, thalamus, putamen, globus pallidus and corpus callosum. At last, the processing speed index correlated with volumes of cerebral cortical gray and white matter, hippocampus, thalamus, putamen, globus pallidus and cerebellar gray and white matter (Table 5). In controls, there were no significant associations between brain volumes and Full IQ when controlling for gender and SES (data not shown). Associations between Full IQ and total intra cranial, cerebral cortical gray and white matter volumes in the non-CP VLBW group and for controls are shown as scatter plots in Fig. 3.

3.3. Relationship between brain volumes and perinatal risk factors in the VLBW group Table 6 presents the associations between selected brain volumes and perinatal risk factors in the VLBW group. There were positive associations between birth weight and volumes of cerebral white matter, thalamus, parts of basal ganglia and corpus callosum. Gestational age correlated with volume of corpus callosum, but this correlation did not survive Bonferroni correction. After adjusting for degree of immaturity, i.e. gestational age at birth, negative associations were found between days in NICU and volumes of globus pallidus, nucleus accumbens and posterior parts of corpus callosum. However,

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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Fig. 3 e Scatter plots showing the associations between different brain volumes and Full Scale IQ for non-CP VLBW and term born controls at 20 years of age.

no significant correlations were seen between days on mechanical ventilator and brain volumes (Table 6).

4.

Discussion

In this study, we found reduction in absolute volumes of several brain structures in VLBW young adults compared to term born controls. The VLBW subjects had significant enlargement of the lateral ventricle. We also found decreased volumes of thalamus, caudate nucleus, cerebellar white matter, central and mid posterior corpus callosum, and increased volume of the lateral ventricle in the VLBW young adults when controlling for total intracranial volume. We did not find any group  time interaction apart from a near significant interaction in the lateral ventricle. Cerebral cortical

Table 6 e Partial correlations between absolute brain volumes and perinatal risk factors: birth weight (bw), gestational age (ga), days in NICU, and days on mechanical ventilator (ventilator) for the VLBW young adults at age 20 (n [ 44). Brain volumes Cerebral white matter Thalamus Nucleus caudate Globus pallidus Nucleus Accumbens Corpus callosum mid anterior Corpus callosum mid posterior Corpus callosum posterior

bw

ga

Days in NICUa

Days on ventilatora

0.535*** 0.139

0.370*

0.269

0.556*** 0.479*** 0.558*** 0.468***

0.433** 0.404** L0.563*** L0.505***

0.119 0.132 0.305 0.005

0.478*** 0.225

0.357

0.363*

0.574*** 0.332**

L0.481***

0.226

0.588*** 0.338**

L0.519***

0.439**

0.265 0.069 0.130 0.030

*p
0.05, **p
0.01, ***p
0.0025. Significant correlations (Bonferroni-adjusted threshold: 0.0025) are shown in bold font. Partial correlations controlled for gender and age at MRI. Abbreviations: VLBW: very low birth weight; NICU: neonatal intensive care unit. a Correlations also controlled for degree of immaturity (gestational age at birth).

and deep nuclei grey matter decreased and white matter increased with time in both groups. Significant associations were demonstrated between brain volumes and IQ measurements in non-CP VLBW young adults, but not in controls. There were also some associations between perinatal risk factors and brain volumes, especially of corpus callosum in the VLBW young adults.

4.1.

Strength and limitations

The brain volume measurements were calculated with FreeSurfer version 5.3.0 using an automated algorithm for cortical and subcortical segmentation.45,46 This algorithm has demonstrated satisfactory test-retest reproducibility across different MRI scanners and field strengths.48,55 However, the subcortical segmentation algorithm has been shown to have high reliability for thalamic measurements, low reliability for amygdala and intermediate reliability for hippocampus,59 especially when hippocampal atrophy was present.60 To avoid segmentation errors, we checked each subject’s images manually as earlier described. Structures with obvious segmentation errors were rejected and no manual corrections were made to avoid introducing bias and increasing variances into the data set of MRI images. The moderate sample size limits the statistical power to detect minor group differences and differences in less reliable brain structures like the amygdala.59 Negative findings should therefore be interpreted with caution. However, the absolute volume differences between the VLBW and the control group were generally large as indicated by the low p-values, and therefore unlikely to be due to chance. The longitudinal study sample was smaller than the cross-sectional study at age 19e20, which reduces the statistical power and generalizability of this subanalysis. We have to be cautious about the generalization of our results, and larger studies are needed to confirm or reject our findings. Since our study population was born in the late 1980s, the dramatic improvement in neonatology, but also the increased survival of the most immature babies during the last decades may have changed the scenario of permanent brain injuries, and thereby the developmental trajectories and volume deviations that this study demonstrates. An experienced neuropsychologist blinded to group adherence performed all the cognitive assessments, which was strength of this study. Strength was also the fact that there was no significant group difference in socio-economic

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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status, which could have confounded the results. The rather moderate attrition rate may also limit the generalization of the results, and may have created a selection bias. However, the attrition rate was comparable to other follow-up studies of young adults,61 and we did not find significant differences in available background variables (gestational age, birth weight, maternal age at birth) between participants and nonparticipants, which make selection bias less likely. This study used US norms of the WAIS-III instead of Norwegian norms, which could be a limitation of study. However, studies have shown that US norms are valid for Norwegian (and other Western Europe) samples with minor differences in mean subtask scores.62 We would also argue that such differences would influence both study groups in the same way.

4.2.

Group differences

The reduction in cerebral gray matter volumes in the VLBW young adults compared to controls has also been reported in very preterm (VPT) born young adults,14,15 in VPT adolescents,15 in VLBW adolescents29,63 and in VLBW/VPT infants.8 Grey matter reduction has been shown to be associated with periventricular leukomalacia (PVL) in preterm born infants,5,64 and is probably a consequence of a combination of axonal damage due to white matter injury and disturbance of normal cortical development.1,65 Volpe describes this encephalopathy of prematurity as “a complex amalgam of primary destructive injuries causing secondary trophic and maturational disturbances of the immature brain”.1 Our finding of decreased white matter volume and increased lateral ventricles in the VLBW group, has previously been reported in VPT young adults14,15 as well as increased size of lateral ventricles in VLBW and VPT young adults.12e14 The reduced white matter volume with compensatory ventricular dilatation is most likely a direct consequence of perinatal white matter injury. Such injury may be caused by a complex interaction between hypoxia, infection/inflammation along with microglia activation, which could result in both focal and diffuse white matter damage, including neuronal axonal loss and disturbed myelination.1,65,66 In the same study population, we have previously reported widespread deviations in white matter microstructure evaluated with diffusion tensor imaging also in areas that looked normal on conventional MRI.3,17 This may indicate aberrant myelination in addition to white matter volume loss. Studies have shown that such hypomyelination in preterm born subjects is likely caused by a combination of loss of developing oligodendrocytes and impaired or arrested maturation of pre-oligodendrocytes to myelin-producing oligodendrocytes.65,67 We also found reduced volume of thalamus in the VLBW group, and this has been reported in. VPT young adults16 and VPT and VLBW adolescents.31,68 We speculate that this finding also reflects perinatal injury, and thalamic involvement has been reported in 60% of cases with periventricular leukomalacia (PVL) in infants born preterm,4 and the thalamic volume deficit is thought to be caused by neuronal loss.64 Reduced thalamic volume in preterm born infants has also been shown to predict lower cortical and hippocampal volumes at term-equivalent age,69 and reduced thalamo-cortical connectivity following preterm birth has been recently reported.70

9

Our finding of reduced volume of hippocampus in VLBW young adults is in accordance with the findings of Fearon et al. who reported non-significant hippocampal reduction in VLBW young adults.13 Our finding is also in agreement with a metaanalysis of VPT and VLBW children and adolescents, which found decreased hippocampal volume in these groups compared with age-matched controls.11 The smaller hippocampus may imply a specific vulnerability of this structure to perinatal white matter injury and postnatal steroid exposure.71 Our findings of reduced volumes of cerebellum and corpus callosum are similar to results of other studies with VLBW adolescents72 and children.73 The exact pathophysiological mechanism behind cerebellar volume deficits in preterm born subjects is still unknown,6 although preterm birth has been reported to cause disturbances to normal cerebellar development in the third trimester74 Shah et al. found that preterm born infants with the most reduced cerebellar volume also had the largest degree of white matter damage, which may indicate a pathophysiological relationship between such findings.75 Reduced volume of globus pallidus has been reported in a study of VLBW children,76 and in another study of VLBW adolescents that found reduced subcortical volume that included globus pallidus.72

4.2.1. Changes in brain volumes from adolescence to young adulthood The reduction in gray matter and increase in white matter volumes from adolescence to young adulthood were similar for VLBW and term born controls in our study. This is in agreement with other studies, which report equivalent development in cerebral gray and white matter in VPT subjects and controls from adolescence to young adulthood,15 and in VLBW/VPT children from childhood to adolescents.11 However, some studies have reported increased growth of corpus callosum in VPT subjects compared with term born controls from adolescents to young adulthood,22 while others have found decreasing cerebellar volume in VPT subject, but not in controls in the same period.15 We did not detect such group differences in change with time, which may be explained by different study samples and segmentation methods. Larger longitudinal studies are needed to investigate further trajectories of brain volume change with time in VLBW survivors.

4.3. Associations between brain volumes and general cognitive ability in VLBW young adults We found associations between volume deviations and full IQ in the VLBW group that are in accordance with several other studies.15,31,72,76e78 These studies found significant correlations between IQ and relative gray matter volume in preterm born girls aged 4.5e8 years,77 between IQ and regional cerebral grey matter volume in VLBW children,76 and between IQ and cerebral white matter volume in VLBW adolescents.72 In addition, positive associations have been found between IQ and cerebellar volume in VPT young adults15 and in VPT teenagers.15,78 However, in our study no significant associations between IQ and specific brain volumes within the VLBW group remained when controlling for total intracranial volume (data not shown). The smaller total intracranial volume in the VLBW group may be due to diffuse widespread perinatal

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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brain injury causing volume loss or influenced early growth, which may have an impact on later cognitive functioning. In addition, we may have had too low statistical power to detect any relationship between specific brain volumes and IQ when we controlled for intracranial volume. Perinatal white matter injury, causing damage to white matter microstructure with reduced functional connectivity may be more important as a cause of functional deficits than any change in volume of specific cortical or subcortical structures in VLBW survivors. For white matter, volume reduction may actually interfere with connectivity. This seems to be the case for corpus callosum where we found an association between IQ and volume of corpus callosum, while using DTI in a previous report IQ also correlated with the fractional anisotropy (FA) values of corpus callosum within the same study population.17 In contrast to the other IQ indices, we found no associations between the verbal comprehension index (VCI) and brain volumes. This is in accordance with our previous reports showing no correlation between VCI and cortical thickness and surface area,34,35 and with the work of Allin et al., who found no association between FA values and verbal IQ in VPT young adults.14 We did find correlations between several structural brain volumes and the working memory, perceptual organization and processing speed indices. Reduced processing speed and working memory deficits are related to poor academic attainment,79 inattentive behavior80 and poor executive functions81 in preterm born children. Perceptual problems are also common in VLBW subjects.30,38 As we found positive correlations between several brain volumes and the scores on these indices, this may indicate structureefunction relationships. Normal processing speed and perceptual organization probably demand intact networks and optimal connectivity of white matter, which reflect that these indices also correlated with white matter volumes. This is partly in an agreement with another study that reported correlations between areas with reduced FA values in VPT young adults and performance IQ, which included the perceptual organization and processing speed indices.14 Furthermore, we have previously reported that the same three IQ indices also correlated with cortical surface area and to a lesser degree with cortical thickness in this VLBW young adult population.34,35

4.4. data

Associations between brain volumes and perinatal

We found that lower birth weight was related to volume reduction of cerebral white matter, thalamus, parts of basal ganglia and corpus callosum. This is in agreement with a study reporting that preterm born adolescents with the lowest birth weight had the most reduced volumes of cerebral white matter and corpus callosum.72 In our study, we found that lower gestational age correlated with reduced volume of corpus callosum, but this correlation did not survive Bonferroni correction. Others have reported relationships between gestational age and cerebral white matter volume in VPT adolescents,82 between gestational age and thalamus in VPT infants69 and between gestational age and combined thalamic and basal ganglia volumes in VLBW infants.83 We speculate that the relationship between brain volumes and birth weight

and gestational age respectively, reflects the increased risk of perinatal injury for the smallest and most immature babies. When controlling for the degree of immaturity, increasing days in NICU still correlated with volume reduction of globus pallidus, nucleus accumbens and posterior parts of corpus callosum, indicating that perinatal morbidity also influences brain structure and development in VLBW survivors. However, we did not find a similar relationship between days on mechanical ventilator and brain volumes when controlling for immaturity. This may be explained by the fact that the mean time on mechanical ventilator was only 4.5 days in the VLBW group. The associations between brain structure volumes and perinatal variables are in accordance with our previous DTI study of the same VLBW young adults, where we found fractional anisotropy of white matter to correlate positively with birth weight and to a lesser degree with gestational age, and negatively with number of days in intensive care, particularly in the corpus callosum.17 Overall, our study suggests that low birth weight and gestational age at birth and increasing days in NICU reflecting both immaturity and increased perinatal morbidity, correlate with specific volume deviations in VLBW young adults. The smaller total intracranial volume per se in VLBW subjects could not fully explain some of these relationships between specific brain structures with perinatal variables, and we speculate that this indicates that some brain structures are more prone to permanent morphometric changes after perinatal brain injury in VLBW survivors.

5.

Conclusion

This study found reduced brain volumes of grey and white matter and ventricular dilatation in VLBW young adults. The findings may indicate permanent effects from preterm birth on brain development due to perinatal brain injury, with influence on later cognitive function. Furthermore, volume reductions of thalamus, caudate nucleus, cerebellar white matter and corpus callosum could not be explained by smaller total intracranial volume in the VLBW young adults, indicating that these brain structures seem especially vulnerable to early brain injury and permanent maldevelopment. Positive associations between several brain volumes and IQ indices in the VLBW group may indicate a structureefunction relationship. However, there is a need for further longitudinal studies with larger samples starting in early childhood to evaluate if volume deviations in VLBW subjects can act as early biomarkers for later cognitive impairments that may be treated or ameliorated with early intervention programs.

Acknowledgments We thank the participants for their co-operation and interest in this study. We also thank the Notur e The Norwegian metacenter for computational science e funded by the Research Council of Norway (RCN) and the University partners NTNU, UiB, UiO and UiT for using the Abel cluster at UiO for the processing of the subjects with FreeSurfer longitudinal

Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004

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stream (project NN9208K). The study was founded by The Research Council of Norway, Norwegian University of Science and Technology (NTNU), Trondheim and Liaison Committee between the Central Norway Regional Health Authority and NTNU.

17.

18.

Appendix A. Supplementary data

19.

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.ejpn.2014.04.004. 20.

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Please cite this article in press as: Bjuland KJ, et al., Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults, European Journal of Paediatric Neurology (2014), http://dx.doi.org/10.1016/j.ejpn.2014.04.004