Maternal Pre-pregnancy BMI Associates With Neonate Brain Local Synchrony in the Left Superior Frontal Gyrus: a Pilot Study

Olli Paul Einari Rajasilta (  operaj@utu. ) University of Turku Suvi Häkkinen University of Turku Malin Björnsdotter Karolinska Institute Noora Scheinin University of Turku Satu Lehtola University of Turku Jani Saunavaara Turku University Hospital Riitta Parkkola Turku University Hospital Tuire Lähdesmäki Turku University Hospital Linnea Karlsson University of Turku Hasse Karlsson University of Turku Jetro Tuulari University of Turku


Introduction
Maternal obesity (BMI ≥ 30 kg/m2) and overweight (BMI ≥ 25-30 kg/m2) during pregnancy have become prevalent worldwide within the last few decades 1 . While the risks of obesity and overweight pregnancies have been extensively studied from obstetric point of view, and is identi ed as a risk factor for delivery and congenital structural abnormalities 1 , less is known about its association to child neurodevelopment. Studies focusing on neurobehavioral and neurodevelopmental aspects have linked maternal obesity and overweight during pregnancy to impaired offspring cognitive development 2,3 , emotional/behavioural problems and consecutive increased risk in obtaining a diagnosis for neuropsychiatric disorders, including anxiety and depressive disorders, autism spectrum disorder, attention de cit hyperactivity disorder and even psychotic disorders 2,3 .
Obesity and overweight are related to complex alterations in metabolism, e.g. insulin resistance, increased circulating levels of lipids, dysfunction of adipose tissue and skeletal muscle, hepatic and pancreatic tissue as well as low grade oxidative stress and in ammation [4][5][6] . During pregnancy, these adverse processes may cause placental dysfunction 7 , likely increasing fetal vulnerability to endo-and exogenous exposures through altered placental vascular permeability. Obesity and overweight are also accompanied by humoral dysregulation with increased levels of estrogen and adipokines, e.g. leptin 8 , which may further contribute to placental dysfunction 6 . These metabolic, humoral and in ammatory alterations coupled with possible placental dysfunction are highly plausible factors to exert a programming effect on the developing fetal brain. Animal model investigations into maternal obesity and offspring brain development have provided some insight on the mechanisms, including dysregulation within serotonergic and dopaminergic systems 9,10 , altered hypothalamic-pituitary-adrenal axis (HPA-axis) responses 11 , fetal neuronal damage 12 and changes in offspring brain gene expression patterns 12 .
Recent advances in brain imaging techniques, such as diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI), have provided the opportunity to probe gestational effects of various states and factors on human fetal and neonate brain development 13 , including maternal obesity and overweight. In adults, functional resting-state networks (RSNs) have been shown to remain stable over time with little variability over imaging sessions, revealing the distributed intrinsic functional organization of the brain where long-range connections dominate 14 . During the rst year of life, there is a formidable gradual shift from local, intra-hemispheric network connectivity seen already in utero and in the neonatal stage to more distributed network connectivity in older children and adults [15][16][17] . These macro-scale network changes are described with prominent alterations to functional hub localization, proliferation of connector hubs and progression of functional segregation of networks, likely indicating more e cient information processing within and between networks over the rst postnatal years in normal development 16,18,19 . Further, alterations in network topology temporally coincide with increased white matter myelination 20 and synaptic pruning 21 . The delicate developmental and recon guration processes in brain functional networks during gestation and the rst years, respectively, present a time window in brain development, that has been shown to be particularly vulnerable for disruption by endogenous and exogenous factors 13 . Prior human MRI neonate studies focusing on obese and overweight pregnancies have revealed that maternal adiposity is associated with widespread alterations in the anterior brain white matter tract integrity 22 and in functional networks 23,24 with emphasis on sensory cue and reward processing, cognitive and motor control in the neonate brain 25 .
Regional homogeneity (ReHo) is an e cient, reliable and widely used index of local fMRI connectivity 26,27 . Based on the assumption that hemodynamic characteristics of every voxel in a functional cluster should be similar to the neighbour voxels, ReHo is commonly interpreted as an index of ongoing brain activity 26 . ReHo measured at rest is altered in adolescents with autism 28 and in adults, shows promising sensitivity to functional changes in schizophrenia 29 , cognitive impairment 30 and even presymptomatic stages of genetic dementia 31 . To the best of our knowledge, there have been no investigations into maternal adiposity induced alterations in local connectivity of the neonate brain. In the present study, we hypothesized that correlations between maternal pre-pregnancy BMI and ReHo may reveal functional abnormalities associated with altered neurodevelopment. For future reference we also provide the average ReHo maps of the neonate brain at 26.14 ± 6.28 days after birth in the supplementary materials.

Materials And Methods
This study was conducted in accordance with the Declaration of Helsinki, and it was approved by the Ethics Committee of the Hospital District of Southwest Finland (15.03.2011) § 95, ETMK: 31/180/2011. Informed written consents were obtained from parents before MRI scans were conducted.

Participants
This study was performed as a part of FinnBrain Birth Cohort Study (www. nnbrain. ) 32 . 28 dyads of full-term born healthy infants and mothers (Table 1) were randomly recruited from the cohort and participated to fMRI scans (performed during year 2015). Exclusion criteria for infants included complications of neurological involvement, less than 5 points in the 5 min Apgar, previously diagnosed central nervous system anomaly, gestational age at delivery less than 32 weeks and birth weight less than 1500 g. Seven dyads were excluded from the study due to excessive neonate motion during the MRI scanning session. All mothers reported having stopped ingesting alcohol and possible use of illicit substances after being informed of being pregnant, although three participants with minor exposure to alcohol or illicit substances (cannabis) during early gestation were included. The sample likely re ects the general Finnish population. None of the included mothers suffered from hypertension, hypercholesterolemia or any form of diabetes mellitus. All scans were carried out during natural sleep at the gestation corrected age of 26.14 ± 6.28 days. To facilitate natural sleep, infants were fed with (breast) milk prior to the scanning session. Image acquisition 28 infants underwent an MRI brain scanning session, including a 6 minute resting-state fMRI sequence.

Image preprocessing
Data were slice timing corrected and motion corrected in FMRIB Software Library (FSL) 35 v6.0 relative to a manually chosen reference volume, free of major artefacts. Motion outliers were estimated by ART (http://www.nitrc.org/projects/artifact_detect; Composite motion threshold (CMT) < 2 mm, DVARS < 9). As neonates commonly exhibit more jerk-like and rigid body movements in the scanner than older infants and adults, more stringent CMT values would have resulted in considerable increase in rejection rate of available data. At this initial step, rs-fMRI data of seven subjects were rejected from further analyses based on major artefacts (with most having ca. 4 / 6 min of data outliers), yielding an included sample size to 21. Anatomical masks for white matter and CSF were de ned by the UNC neonate segmentation model 36 and registered to functional data with a ne transformation. Average signal in white matter average and CSF as well as 24 motion covariates 37 were included as nuisance covariates. Thus, denoising consisted of nuisance regression followed by outlier rejection, detrending, and high-pass ltering (0.008 Hz).
The main outcome metric for functional organization of the neonate brain was ReHo, which is estimated in a data-driven manner and provides a voxel-wise, local connectivity measure 26,38 . ReHo is based on calculating the Kendall's coe cient of concordance over a target voxel and neighboring voxels.

Statistical analysis
All statistical analyses were performed with SPM12 (https://www. l.ion.ucl.ac.uk/spm/software/spm12/) software with multiple regression design for ReHo maps. Maternal pre-pregnancy BMI was set as the main explanatory variable (EV), and gestation corrected age and neonate sex were set as primary independent variables (IV). Statistical threshold was set to p < 0.005 and corrected with FWE/FDR at the cluster level. Images were inclusively masked after cluster correction with averaged UNC template GM mask to limit the statistics to the grey matter. We ran separate sensitivity analyses with identical design except for the added fourth regressor of no interest for the following: Apgar points at 1 and 5 minutes, neonate birth weight, maternal age in years and EPDS questionnaire score lled out by mothers at the 24th gestational week. Models with Apgar points at 1 and 5 minutes were performed with Statistical nonparametric mapping due to non-normal distribution of the clusters. The cluster size for left SFG and right SFG were 487 and 645 voxels, respectively, at p < 0.001 level. The observed additive effects of included two IVs (EPDS sum score, gestational weight) likely stem from collinearity or from inclusion of too many IVs for a model with relatively small sample size.

Discussion
In this study we explored whether maternal pre-pregnancy BMI affects neonate brain local functional connectivity. Multiple regression analysis revealed that maternal pre-pregnancy BMI and neonate ReHo values were positively associated (FDR/FWE -corrected p < 0.005, cluster size of 869 voxels) within the left SFG, suggesting that higher maternal BMI during pre-pregnancy or early pregnancy in uences neonatal local brain connectivity.
In neonates soon after birth, high ReHo values are encountered symmetrically in primary somatosensory and visual networks (mean ReHo map shown in Supplementary materials, Figs. 1 and 39 ). Notably, previous developmental fMRI connectivity studies have estimated that these networks achieve adult-like network topology and function earlier than e.g. frontoparietal, executive control and default-mode networks 16,18,19 . In line with this idea, prior modelling studies have suggested an inverse relationship between distal connectivity and ReHo regarding a given voxel 38 , suggesting that as functional segregation of networks ensues, ReHo values decrease. In this framework, our observation that ReHo in the left SFG was higher in neonates born to mothers with higher BMIs likely relates to ampli ed local, and conversely, decreased distal connectivity in this region.
The left SFG has been identi ed as a key hub in the left frontoparietal network (FPN), which holds a central role in executive control, working memory and uid intelligence in adults 40 . Furthermore, SFGs have been recognized as crucial areas for global networks in terms of network centrality in adults 41 and identi ed as a possible connector hub between executive control network and default-mode-network 42 . However, in their immature state, brain networks in neonates likely have divergent functions as compared to corresponding networks in older infants and adults, complicating network-related change interpretation and comparison between populations of different age. For the left FPN, increase in within-network and in inter-network connectivity between lateral visual, auditory/language and right FP networks with simultaneous decreases in inter-network connectivity between medial visual and salience networks take place during the rst year of life 18 . In light of previous studies into functional resting-state-network development and ReHo interpretation, the observed positive association between maternal pre-pregnancy BMI and neonate left SFG ReHo values in this study may suggest accelerated within-network development. Whether this is re ected as altered inter-network connectivity regarding lateral visual, auditory/language and right FP or other networks, remains unclear. If inter-network and distal connectivity are altered, it might explain some of the observed cognitive performance differences seen in older children born from obese and overweight pregnancies 2,3 .
Prior investigations into maternal obesity and overweight during pregnancy related infant neurodevelopment have revealed widespread functional connectivity and white matter tract alterations in the neonate brain [22][23][24][25] . Similarly, a recent study found that higher pre-pregnancy maternal BMI during gestation associated with variations in functional connectivity in fetal prefrontal, frontal and insular brain regions 43 . These results suggest that at least some group differences observed in obese/overweight and normal-weight populations could begin during the gestational period and may be attributed to metabolic, humoral and in ammatory processes in obese mothers. Indeed, obesity/overweight related changes in brain network organization have been well documented in adult populations with alterations emphasizing to four distinct domains concerned with feeding behavior: Sensory cue processing 44 , reward processing 45 , cognitive 44 and motor control 46 . A recent seed-based connectivity study hypothesized that these network abnormalities could be inherited through genetic or environmental effects and observed similar functional connectivity differences in neonates exposed to maternal obesity during gestation 25 . To the best of our knowledge, no structural MRI studies have been performed on neonates born from pregnancies with maternal obesity, but studies focusing on older obese/overweight children have found grey matter abnormalities within the frontal, prefrontal and limbic areas 47 . Moreover, the observed GM reduction were partly associated with impaired executive function 47 . These abnormalities mainly spatially overlap with functional changes seen in neonates born from pregnancies with maternal obesity/overweight and likely precede structural abnormalities seen in older children and may begin as early as gestation.
Despite the observable widespread connectivity differences between neonates born from normal-weight and pregnancies with maternal obesity, it is unclear whether these changes are driven by systemic effects of insults or caused by localized impairment of key regions, e.g. connector hubs, followed by plasticity induced changes within plural functional networks, causing global differences in connectivity. It is likely that divergent detrimental factors have a heavier impact on speci c regions and those most vulnerable are presumably areas crucial for networks that take years to reach maturity and obtain coherent function 13 .

Limitations
We acknowledge that a larger sample size would have increased statistical power and possibly revealed more subtle local connectivity variations as well as allowed studying e.g. sex-differences. Similarly, due to sample size, we were unable to perform statistically reliable group difference tests for normal versus elevated BMI exposed subjects. Further, while BMI is a sound indicator for obesity and overweight, it does not take into account the variability in body composition, e.g. fat and muscle ratios. This study unfortunately lacks background information on the types of maternal food intake, which is likely a contributing factor in obesity induced effects. Finally, no data vas available for maternal BMI variability during the course of pregnancies and such data would be valuable in future studies (ideally coupled to other metabolic biomarkers).

Conclusions
In this study, we showed that maternal pre-pregnancy BMI is positively associated with ReHo values within the neonate left SFG, suggesting an increase in local functional connectivity and ampli ed withinnetwork connectivity. Our ndings provide further evidence for maternal BMI in uenced changes in functional brain development seen in neonates born from obese/overweight pregnancies. The observed alterations in local connectivity within the left SFG are unlikely to be independently detrimental but may contribute to unfavorable neurodevelopmental outcomes if negative exposures on the developing brain are encountered.

Declarations Con ict of interest
None.
Author contributions JJT, MB, NMS, HK, MB planned and/or funded the MR measurements. JS planned and implemented the image acquisition parameters. JJT and SL collected the imaging data. OR and JJT planned the analytical approach and performed the data analyses. SH aided in the data preprocessing and interpretation. RP provided neuroradiological expertise for screening the acquired MRI images for incidental ndings. HK and LK established the cohort and built infrastructure for carrying out the study.
All authors participated in writing the manuscript and accepted the nal version.