Research reportHippocampal subfield volume changes in subtypes of attention deficit hyperactivity disorder
Introduction
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects millions of people worldwide. The prevalence of ADHD lies between 5.4% (Canals et al., 2016) and 6% (Bachmann et al., 2017) in children and adolescents, and at 3.4% in adults (Fayyad et al., 2007). For instance, in Germany 6% of children and adolescents (up to 17 years old) are diagnosed with ADHD (with a maximum of 13.9% in 9-year-old boys; (Bachmann et al., 2017). Up to two-thirds of younger ADHD patients continue experiencing symptoms in adulthood (Faraone et al., 2006). ADHD is characterized by age-inappropriate symptoms of inattention and/or hyperactivity-impulsivity that interfere with cognitive functioning and development. The ADHD is classified into three distinct subtypes: inattentive, hyperactive-impulsive and combined types (Association and Association, 2013). Each type has distinct symptoms and corresponding treatments. For instance, inattentive type is predominantly characterized by difficulty in paying attention to details and concentrating on a task. The predominantly hyperactive-impulsive type is described by fidgeting, squirming and running or climbing at inappropriate times. However, the most common is the combined type, when people have symptoms of both inattentive and hyperactive-impulsive subtypes (Association and Association, 2013).
Despite its prevalence and impact, neural mechanisms underlying ADHD remain unclear (Won et al., 2011). Neuroimaging studies have reported altered structural and functional brain networks in ADHD individuals compared to the healthy controls. For instance, children with ADHD have a lower whole brain volume and cortical gray matter volume (Batty et al., 2010). Besides cortex, the hippocampus is one of the brain regions that may be affected by ADHD (Hoogman et al., 2017, Plessen et al., 2006). Previous structural MRI studies (often used relatively small ADHD sample size, N = ∼50) have reported inconsistent results in terms of global hippocampal volume changes in ADHD. For instance, studies reported either disorder-related enlargement (Plessen et al., 2006) or reduction (Posner et al., 2014) in hippocampal volumes. In addition, a recent mega-analysis of over 3000 MRI scans reported a global hippocampal volume reduction in patients with ADHD (Hoogman et al., 2017). However, the contribution of hippocampal subfield changes to the ADHD is less clear and has not been studied (Hoogman et al., 2017).
The hippocampus is essential for the acquisition, consolidation and retrieval of spatial and episodic long-term memory (Burgess and Maguire, 2002, Eichenbaum and Harris, 2000), including working memory (Axmacher et al., 2010). However, given its extensive connections and distinct substructures, the hippocampus is likely to be involved in more than one isolated cognitive function (e.g., memory). Specifically, the hippocampus is thought to be involved in such cognitive functions as response inhibition, episodic memory, and spatial cognition. For instance, the hippocampus is involved in attentional processes such as visuospatial working memory (Spellman et al., 2015) and it is known to modulate executive functions (Frodl et al., 2006). Importantly, disturbances in these cognitive functions constitute the core symptoms of ADHD (Plessen et al., 2006). As an example, children with combined ADHD relative to inattentive ADHD and healthy controls perform worse on a go-nogo task (Booth et al., 2005, Desman et al., 2008). Therefore, the study showed that ADHD may result in executive problems with response inhibition and also pointed to an ADHD-type differentiation. Furthermore, ADHD-related working memory deficits seem to reflect a combination of impaired central executive and phonological storage/rehearsal processes (Alderson et al., 2015). In other words, the authors showed that it is not only the executive control that is impaired in ADHD, but also the working memory related episodic buffer. Finally, there is some evidence that working memory problems are particularly associated with the visuospatial cognition. For instance, it was shown that the visuospatial working memory test is a sensitive measure of cognitive deficits in ADHD (Westerberg et al., 2004). Therefore, the contribution of the hippocampus to attention deficit in ADHD is highly likely, since attention and memory are complimentary and synergistic in nature (Chun and Jiang, 1998, Haskell and Anderson, 2016). While attention facilitates encoding and retrieval of memory in the hippocampus (Aly and Turk-Browne, 2016, Aly and Turk-Browne, 2016), hippocampal memories can also guide attention to previously inspected objects or locations and thus facilitate a quick scan of the environment and object recognition (Bar, 2004, Chun, 2000, Goldfarb et al., 2016).
The hippocampus is subdivided along its longitudinal axis into several subfields, i.e., cornu amonis regions (CA1, CA2/3, and CA4), fimbria, hippocampal fissure, presubiculum, subiculum, hippocampal tail, parasubiculum, granule cell layers of the dentate gyrus (DG), molecular layer within the subiculum, and the hippocampal amygdala transition area (HATA; Fig. 1. These subfields are anatomically and functionally distinct (Duvernoy et al., 2005), and seem to be differentially affected in a disorder-specific manner (Geuze et al., 2005, Malykhin and Coupland, 2015). Hence, a detailed identification of the local hippocampal subfield volumes could provide a better insight into the understanding of the role of individual subfields in ADHD. In the current study, we aimed to investigate differences in hippocampal subfield volumes in a large sample of patients with ADHD and healthy participants. We analyzed 880 anatomical datasets aggregated across 8 independent imaging sites (ADHD 200, http://fcon_1000.projects.nitrc.org/indi/adhd200/). Note that ADHD200 cohort was also part of the large analysis by Hoogman et al. (2017). We used 553 datasets from normally developing individuals and 327 from children and adolescents with ADHD (age range in both groups: 7–21 years old2; inattentive type = 196 patients, combined = 131). Please note that we excluded 13 hyperactive-impulsive patients due to a small sample size that would not have allowed a meaningful analysis. We also assessed hippocampal subfield volumes using the most recent version of the software Freesurfer 6.0 (FreeSurfer, 2012, Iglesias et al., 2015) which provides a state-of-the-art segmentation of subfield volumes. Based on the recent mega-sample study by Hoogman and colleagues (>3000 samples, (Hoogman et al., 2017), we hypothesized that ADHD patients would have smaller overall hippocampal subfield volumes than healthy control subjects (Hoogman et al., 2017). Furthermore, in subsequent analyses, we examined hippocampal subfield volume changes in different ADHD subtypes relative to normal controls. The critical question was which hippocampal substructures differ between ADHD and normal controls and if so, whether there are differences between different subtypes of ADHD.
Section snippets
Results
Individual ANCOVAs comparing hippocampal volumes across the three experimental groups revealed significant effects for the hippocampal tail (F(2, 874) = 9.64, p < 0.0001, ηp2 = 0.022), subiculum (F(2, 874) = 20.89, p < 0.0001, ηp2 = 0.046), CA1 (F(2, 874) = 12.29, p < 0.0001, ηp2 = 0.027), CA4 (F(2, 874) = 9.64, p < 0.0001, ηp2 = 0.022), presubiculum (F(2, 874) = 9.06, p < 0.0001, ηp2 = 0.02), molecular layer (F(2, 874) = 13.11, p < 0.0001, ηp2 = 0.029), granule cell layers of the dentate gyrus
Discussion
We observed reduction of several hippocampal volumes in ADHD relative to healthy controls. This reduction was most marked (and statistically significant) in CA1, CA4, molecular layer, presubiculum, subiculum, fimbria and hippocampal tail. Interestingly, reductions were found only for the combined, but not inattentive, ADHD-subtype. We also found negative correlations between hippocampal subfields in the two ADHD groups and total ADHD index, index of inattentiveness and hyperimpulsivity, and a
Participants
The T1-weighted structural MRI data were obtained from the ADHD-200 database (ADHD-200 Consortium). The dataset consists of 973 structural MRI scans and additionally includes diagnostic and demographic information: gender, age, handedness, and measures of IQ. We excluded 78 subjects from the total ADHD 200 dataset since additional permission was required to use these datasets and 13 hyperactive-impulsive patients due to a small sample size.
Additionally, any hippocampal subfields that exceeded
Acknowledgment
This research was not supported by any Foundation or Grant. We would also like to show our gratitude to the International Neuroimaging Data-sharing Initiative (INDI) for providing a public access to the ADHD200 database.
Financial Disclosures
Md. Mamun Al-Amin, Artyom Zinchenko and Prof. Dr. Thomas Geyer reported no biomedical financial interests or potential conflicts of interest.
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These authors have equally contributed to the work.