NeuroImage: Clinical 28 (2020) 102482 Contents lists available at ScienceDirect NeuroImage: Clinical journal homepage: www.elsevier.com/locate/ynicl Locus coeruleus connectivity alterations in late-life major depressive disorder during a visual oddball task Inés del Cerro a, b, c, Ignacio Martínez-Zalacaín a, b, Andrés Guinea-Izquierdo a, b, Jordi Gascón-Bayarri d, Vanesa Viñas-Diez d, Mikel Urretavizcaya a, b, c, Pablo Naval-Baudin e, Carlos Aguilera e, Ramón Reñé-Ramírez d, Isidre Ferrer f, g, h, José M. Menchón a, b, c, Virginia Soria a, b, c, *, Carles Soriano-Mas a, c, i, * a Bellvitge Biomedical Research Institute-IDIBELL, Department of Psychiatry, Bellvitge University Hospital, Barcelona, Spain b Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain c Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain d Dementia Diagnostic and Treatment Unit, Department of Neurology, Bellvitge University Hospital, Barcelona, Spain e Imaging Diagnostic Institute (IDI), Neuroradiology Unit, Bellvitge University Hospital, Barcelona, Spain f Department of Pathology and Experimental Therapeutics, Institute of Neurosciences, University of Barcelona, Barcelona, Spain g Bellvitge Biomedical Research Institute-IDIBELL, Department of Pathologic Anatomy, Bellvitge University Hospital, Barcelona, Spain h Network Center for Biomedical Research on Neurodegenerative Diseases (CIBERNED), Barcelona, Spain i Department of Psychobiology and Methodology in Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain A R T I C L E I N F O A B S T R A C T Keywords: The Locus Coeruleus (LC) is the major source of noradrenergic neurotransmission. Structural alterations in the LC Late-life major depressive disorder have been observed in neurodegenerative disorders and at-risk individuals, although functional connectivity Mild cognitive impairment studies between the LC and other brain areas have not been yet performed in these populations. Patients with Locus coeruleus late-life major depressive disorder (MDD) are indeed at increased risk for neurodegenerative disorders, and here Anterior cingulate cortex Functional magnetic resonance imaging we investigated LC connectivity in late-life MDD in comparison to individuals with amnestic type mild cognitive Visual oddball task impairment (aMCI) and healthy controls (HCs). We assessed 20 patients with late-life MDD, 16 patients with aMCI, and 26 HCs, who underwent a functional magnetic resonance scan while performing a visual oddball task. We assessed task-related modulations of LC connectivity (i.e., Psychophysiological Interactions, PPI) with other brain areas. A T1-weighted fast spin-echo sequence for LC localization was also obtained. Patients with late-life MDD showed lower global connectivity during target detection in a cluster encompassing the right caudal LC. Specifically, we observed lower LC connectivity with the left anterior cingulate cortex (ACC), the right fusiform gyrus, and different cerebellar clusters. Moreover, alterations in LC-ACC connectivity correlated negatively with depression severity (i.e., Geriatric Depression Scale and number of recurrences). Reduced connectivity of the LC during oddball performance seems to specifically characterize patients with late-life MDD, but not other pop­ ulations of aged individuals with cognitive alterations. Such alteration is associated with different measures of disease severity, such as the current presence of symptoms and the burden of disease (number of recurrences). 1. Introduction 2003; Braak and Del Tredici, 2015). Neuropathological studies have revealed that pretangle tau lesions may be observed in the LC of healthy The locus coeruleus (LC), the major noradrenergic (NA) source in the subjects before 30 years of age (Braak and Del Tredici, 2011), and tau central nervous system, has been suggested to be one of the initial sites alterations in the LC of asymptomatic individuals have been related to of appearance of pathologically altered tau aggregates in preclinical alterations in different metabolic pathways of LC neurons and increased stages of Alzheimer’s disease (AD) (Braak et al., 2011; Zarow et al., pro-inflammatory gene expression and microglia response, which are * Corresponding authors at: Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Feixa Llarga s/n, 08907, L’Hospitalet de Llobregat, Barcelona, Spain. E-mail addresses: vsoria@bellvitgehospital.cat (V. Soria), csoriano@idibell.cat (C. Soriano-Mas). https://doi.org/10.1016/j.nicl.2020.102482 Received 24 April 2020; Received in revised form 25 September 2020; Accepted 19 October 2020 Available online 27 October 2020 2213-1582/© 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 accompanied by compensatory increases in α2A adrenergic receptor 2. Methods protein levels in regions receiving noradrenergic input from the LC, such as the amygdala or the hippocampus (Andrés-Benito et al., 2017). 2.1. Participants Individuals with mild cognitive impairment (MCI), with an esti­ mated AD-conversion rate around 10–15% per year (Petersen, 2004), The final sample of the study included 20 patients with late-life MDD accumulate tau pathological changes in the LC to a larger extent than (13 women), 16 aMCI (10 women) and 26 HCs (16 women) (see cognitively preserved individuals (Grudzien et al., 2007). Such accu­ Table S1 for a description of the number of participants initially mulation, however, is smaller than in AD, suggesting that LC degener­ recruited and the reasons for their exclusion). Late-life MDD patients ation increases throughout the MCI-AD continuum (Grudzien et al., were consecutively recruited from the Department of Psychiatry at 2007). Moreover, individuals with amnestic MCI (aMCI), with AD con­ Bellvitge University Hospital (Barcelona, Spain), and diagnosed version odds greater than the non-amnestic subtype (Busse et al., 2006), following DSM-IV-TR criteria for MDD. In all cases, major depression also present alterations in pupillary response (Granholm et al., 2017), was their primary diagnosis, and the first depressive episode appeared which has been shown to be associated to altered task-induced phasic after 40 years of age. Individuals with aMCI were consecutively activity of LC neurons (Elman et al., 2017), although pupil dilation may recruited from the Department of Neurology of the same hospital. They also depend on other neurotransmitter systems, such as serotonin were diagnosed following Petersen criteria6, with Clinical Dementia (Weinberg-Wolf et al., 2018). Rating (CDR) scores of 0.5 (Hughes et al., 1982), and were characterized Subjects with late-life major depressive disorder (MDD) have a as amnestic MCI using the delayed recall test (5 points or less) of the twofold increased risk of progression to AD (Byers and Yaffe, 2011; Wechsler Memory Scale III (Wechsler, 1997). Importantly, aMCI sub­ Green et al., 2003), and also show alterations in the LC, such as a jects did not present MDD comorbidity. It is important to note that our decreased neuronal count (Baumann et al., 1999). More importantly, definition of aMCI is based on a syndromal categorical cognitive staging MDD patients present a decreased neuron density in LC projection areas approach, and not in the use of biomarkers (Jack et al., 2018). Healthy (e.g., hippocampus or prefrontal cortex) (Tsopelas et al., 2011), which controls were recruited from the same geographical area through ad­ has led to suggest that decreased NA input may be related to neural vertisements and underwent a medical anamnesis to rule out the pos­ degeneration in different brain regions (Gannon and Wang, 2019). sibility of current or lifetime psychiatric or neurologic disorder, as well Nevertheless, to our knowledge, no previous studies have evaluated as the use of psychotropic medication. potential abnormalities in the connectivity between the LC and the All participants underwent a comprehensive neuropsychological multiple areas receiving NA input in late-life MDD. This could be ach­ testing, including the Mini Mental State Examination (MMSE) (Folstein ieved by non-invasive means with functional magnetic resonance im­ et al., 1975) and different tests covering the domains of attention, verbal aging (fMRI) estimations of functional connectivity between the LC and learning and memory, executive functioning, language, visual gnosias the rest of the brain. and motor praxis (Table S2). Since groups differed in premorbid intel­ In physiological conditions, phasic discharge in LC neurons occurs in ligence (i.e., Vocabulary score, F(2,59) = 24.99, p < 0.0001), this variable front of salient events (Aston-Jones and Cohen, 2005), and NA activity was used as confounding covariate in across-group comparisons of has been linked to fast orienting and flexible behavior by optimizing neurocognitive variables. The Spanish brief version of the Geriatric signal-to-noise ratio in regions receiving LC input (Devilbiss, 2004). In Depression Scale (GDS) (Martínez de la Iglesia et al., 2002) and the experimental settings, such phasic activity of the LC has been tradi­ Hamilton Depression Rating Scale (Hamilton, 1960) were administered tionally assessed by means of oddball paradigms (Rajkowski et al., 1994) to assess depression severity, but not for diagnostic purposes, and the evaluating the capacity to rapidly detect unpredictable, infrequent and Functional Assessment Staging scale (FAST) (Sclan and Reisberg, 1992) salient stimuli (i.e., oddball stimuli) (Aston-Jones et al., 1994). Despite was used as a measure of functionality. the limited temporal resolution of BOLD fMRI, putative alterations in Exclusion criteria included < 60 or > 75 years, current or past his­ functional connectivity between the LC and the rest of brain areas tory of other psychiatric or neurological disorders, acute and severe should therefore be better captured during event-related tasks than depressive symptoms hampering neurocognitive assessment, a Hachin­ during resting-state or blocks of continuous activation. ski Ischemia Score > 3, CDR scores > 0.5, mental disability, any severe Here, we aim to evaluate whole-brain functional connectivity of the medical condition, current or past substance abuse (excluding nicotine), LC during a visual oddball paradigm in patients with late-life MDD, who sensorial impairment preventing undertaking any of the assessments, were compared to patients with aMCI and healthy controls (HCs). We presence of contraindications to magnetic resonance imaging (MRI), or also aimed at correlating neuroimaging measurements with clinical and gross abnormalities in the MRI scan. Written informed consent was neuropsychological data. Importantly, although the oddball task has obtained from all participants after a complete description of the study, been strongly associated with LC and NA activity, to evaluate the which was performed in accordance with the Declaration of Helsinki and specificity of our potential findings, we first performed a global con­ approved by the ethical committee in clinical research of Bellvitge nectivity degree analysis (i.e., voxel-to-voxel, or V2V) to identify voxels University Hospital. showing functional connectivity alterations during oddball detection within a pons area encompassing different nuclei that could be also 2.2. Visual oddball task involved in oddball detection. Such an approach also allowed for detecting significant differences in distinct LC subregions. Moreover, to All participants undertook a visual oddball task during the acquisi­ ascertain that our findings were indeed located in the LC, our functional tion of an fMRI sequence. They were instructed to lie still without findings were contrasted against a specific structural sequence allowing moving, focusing their attention on a centrally presented visual stimuli visualization of the LC. Finally, we performed a seed-based analysis with consisting of a purple cross (0.65◦ of the visual angle) and standard and the results from the V2V analysis to characterize LC connectivity. We target/oddball stimuli (purple circles with diameters subtending 3.2◦ hypothesized that individuals with late-life MDD and aMCI will show and 1.6◦ of the visual angle, respectively). All stimuli were presented impairment in the oddball task in combination with a disrupted con­ against a dark-grey background matched for luminance. A total of 200 nectivity from the LC to other brain areas during oddball detection, and standard stimuli and 50 targets were presented for 100 ms each, with an this will likely relate to measures of task performance and disorder interstimulus interval pseudorandomly varying between 2.5 and 3.5 s. severity. We also anticipate that such alterations will discriminate be­ Target stimuli (20% of the trials) were pseudorandomly distributed tween the clinical groups. throughout the task ensuring a minimum inter-target interval of 10 s. Finally, seven 14 s cross blocks were interspersed throughout the task to minimize fatigue. Task was presented using E-Prime software 2 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 (Psychology Software Tools Inc., Pittsburgh, PA) and a 32 LCD Bold body realignment parameters, as well as their first order derivatives), Screen for fMRI (Cambridge Research Systems Ltd) placed at the rear of controlling for total grey matter (GM) signal, linear detrending, the ART the bore, which was visible though a mirror mounted at the MRI head scrubbing protocol, and band-pass filtering (0.008–0.09 Hz). The ART coil. Subjects indicated the detection of the oddball stimuli with a right- scrubbing protocol regressed out the effect of outlier volumes which handed index-press using an MRI-compatible three-button fiber optic signal intensity deviated >5 standard deviations from whole series mean response box (Lumina 3G Controller, Cedrus Corporation). Task dura­ signal intensity or showed evidence of displacement superior to 0.9 mm tion was 14 min 42 s. in relation to the preceding volume. Finally, physiological noise was removed with the anatomical component-based noise correction method 2.3. Image acquisition (aCompCor) (Behzadi et al., 2007). Importantly, after implementing these different steps, none of the subjects was removed from the analysis Imaging data were acquired using a 3 T Ingenia scan (Philips because, according to current guidelines (Satterthwaite et al., 2013; Van Healthcare, Best, The Netherlands) equipped with a 32-channel head Dijk et al., 2010), all individual functional series included at least a 95% coil at Imaging Diagnostic Institute (IDI, Duran i Reynals Hospital, of original volumes after scrubbing. Moreover, the number of outlier Barcelona, Spain). The functional sequence consisted of 435 echo-planar volumes did not differ across the study groups. image volumes (excluding the four initial dummy volumes) comprising 40 interleaved slices acquired in the oblique axial direction perpendic­ 2.5. Functional MRI data analysis: task-related connectivity ular to the floor of the fourth ventricle (repetition time = 2000 ms; echo time = 25 ms; flip angle = 90◦ ; 3 mm isotropic voxels; field of view = 24 Changes in LC connectivity over time were also assessed using the cm, 80x80 pixel matrix). CONN toolbox v17.f (Whitfield-Gabrieli and Nieto-Castanon, 2012). For anatomical reference and imaging preprocessing purposes, we Specifically, analyses were divided in two parts: voxel-to-voxel and also acquired for each participant a whole-brain T1-weighted anatom­ generalized psychophysiological interactions analysis. ical three-dimensional inversion-recovery prepared spoiled gradient echo sequence (233 axial slices; repetition time = 10.46 ms; echo time = 2.5.1. Voxel-to-voxel analysis (V2V) 4.79 ms; flip angle = 8◦ ; 0.75 mm isotropic voxels; field of view = 24 cm; We performed an Intrinsic Connectivity Contrast (ICC) analysis pixel matrix = 320 × 318; total duration = 5 min, 04 s). (Martuzzi et al., 2011), which provides an estimation of the number of Moreover, a T1-weighted fast spin-echo sequence was also acquired significant (positive or negative) V2V connections and therefore allowed for LC localization. This sequence lasted 15 min 02 s and consisted of 15 characterizing global connectivity strength between each voxel and the slices covering the brainstem area to the level of the caudal pons with rest of the brain during oddball detection in relation to standard stimuli. the following parameters: repetition time = 600 ms; echo time = 14 ms; In first-level (within-subject) analyses, the matrix of V2V bivariate flip angle = 90◦ ; 2.5 mm slice thickness; 0 mm gap; matrix size 404x250; correlation coefficients was computed for each participant using the FOV 170x170 mm2; acquisition voxel size 0.42x0.68x2.5 mm3; recon­ residual BOLD time series from all the 2-mm isotropic gray matter voxels structed voxel size 0.39x0.39x2.5 mm3). The sections were acquired in of a whole-brain mask. The correlations of each voxel with the rest of the oblique axial direction perpendicular to the floor of the fourth brain voxels were then averaged and displayed in a brain map format as ventricle covering from the posterior commissure to the inferior border beta-values representing the strength of the whole-brain correlations for of the pons. See supplementary material for details on LC localization, each voxel. Realignment parameters, scan-to-scan changes in global and Figs. S1 and S2. Throughout the acquisition protocol, we used foam BOLD signal (Z-scores), framewise displacement timeseries (in mm) and pads and made sure that patients’ head was comfortably placed within outlier scans were included as nuisance parameters in this analysis. the head coil to avoid excessive movement. Next, in the second level (between-subject) analysis, we used the indi­ vidual beta-maps from the first level analysis to estimate a one-way 2.4. Imaging data preprocessing and denoising ANOVA model and compare the voxel-wise connectivity strengths across the three study groups. In accordance with our hypothesis, First, functional time series were initially despiked using the Brain­ however, this second-level analysis was restricted to pons voxels to Wavelet toolbox v2.0 (Patel et al., 2014). Next, using MATLAB version specifically assess across-group changes in global connectivity strength 9.3 (R2017b) (The MathWorks Inc, Natick, Massachusetts) and the from these areas to the rest of the brain. For this, we used a pons par­ MATLAB-based CONN-fMRI Functional Connectivity toolbox version cellation from the WFU PickAtlas toolbox (Maldjian et al., 2003) 17.f (Whitfield-Gabrieli and Nieto-Castanon, 2012), implemented in encompassing gray matter voxels from the pontine tegmentum, where SPM12 (Wellcome Department of Imaging Neuroscience, London, UK; the LC and other nuclei are located, and the basilar pontine nuclei in the www.fil.ion.ucl.ac.uk/spm), functional images were aligned to the first ventral-caudal pons (see Fig. S3). volume of the time series using a six-parameter rigid body spatial transformation and a least-squares minimization in combination with an 2.5.2. Generalized psychophysiological interactions analysis (gPPI) unwarping algorithm aimed at correcting motion and motion-related We performed a gPPI analysis to study the specific LC task-related distortions. Slice-timing correction was then applied. The ART-based connectivity and identify the brain regions showing more significant automatic volume outlier detection (https://www.nitrc.org/projects/ changes in connectivity with the LC between target and standard con­ artifact_detect/) was also run for later scrubbing. Likewise, both func­ ditions (contrast oddball > standard stimuli). Specifically, we assessed tional and structural images were subjected to simultaneous grey, white the influence of the task (‘psychological factor’) on the strength of time- matter and cerebrospinal fluid segmentation, and a bias correction was course correlations between signal from the peak cluster resulting from performed to remove smoothly varying intensity differences across im­ the above ICC analysis and signal from all other brain voxels (‘physio­ ages. Such image segments were subsequently spatially normalized logical factor’). The resulting contrast images were used in subsequent through non-linear transformations to the Montreal Neurological Insti­ one-way ANOVA analyses (second-level) to assess across-group differ­ tute (MNI) stereotactic space, and images were resliced to a 2-mm ences in task-induced changes in connectivity between the LC and the isotropic resolution. Finally, images were smoothed with an 8-mm rest of the brain. full-width at half-maximum (FWHM) isotropic Gaussian kernel. All analyses were controlled for age and sex. Moreover, to set a After preprocessing, data were denoised from residual movement multiple comparison corrected significance threshold, a voxel-wise non and physiological noise. Denoising steps included a temporal despiking, parametric permutation testing with 5000 permutations (Nichols and regressing out confounding factors (i.e., effect of BOLD signal small Holmes, 2001) using the Threshold-Free Cluster Enhancement (TFCE) ramping effects at the beginning of each scan session and the six rigid method (Smith and Nichols, 2009, SPM-TFCE toolbox v138: http://dbm. 3 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 neuro.uni-jena.de/tfce/) was applied. Statistical significance was set at post hoc tests showed that, overall, MDD and aMCI groups performed p < 0.05, Family-Wise Error (FWE) corrected across all voxels of interest. worse than HCs. Specifically, MDD presented higher GDS scores and Finally, to confirm our findings were indeed involving the LC, results lower MMSE compared to HCs, and higher HDRS scores in comparison from V2V analyses were overlapped onto the MNI-normalized LC map of to the other two groups. aMCI individuals showed lower scores in the our sample (see Supplementary material for details). MMSE, the FAST and executive functioning. Memory impairments were present in aMCI in comparison to both MDD and HCs. As for the oddball 2.5.3. Correlations between imaging and clinical and neuropsychological task, both clinical groups made more omission errors than HCs, and variables aMCI subjects made more commission errors than MDD and HCs groups. To explore for the potential association of imaging with clinical and neuropsychological variables, we extracted the first eigenvariate (the 3.2. Functional connectivity results factor accounting for the highest percentage of variance of voxel values within a cluster) of significant clusters in above analyses and conducted 3.2.1. Global connectivity a series of correlations using SPSS v.25 (SPSS Inc., Chicago, IL). Partial In comparison to aMCI and HC groups, MDD patients showed lower correlations (controlling for age), were performed between imaging global connectivity strength during oddball trials in relation to standard results and measures of oddball performance, severity scores (i.e., GDS trials from a cluster located in the right caudal LC (peak voxel: x = 6, y = and MMSE), and other clinical variables such as age at disorder’s onset, -38, z = -36; TFCE = 54.11; kE = 10; pFWE = 0.035) to other gray matter number of MDD recurrences, and delayed memory scores, and non- voxels throughout the brain (Fig. 1). To confirm the location of this parametric statistics were used in post-hoc analyses involving a finding, we overlapped the functional cluster onto the LC distribution limited number of subjects (see Results section below). Transformations map obtained from our sample, what confirmed that the cluster was were applied when the distribution of variables deviated from normality located at the most caudal portion of the LC (Fig. 1A). Importantly, to (i.e., skewness). Given the exploratory nature of these analyses, signif­ further confirm the specificity of our findings and the effects of signal icance threshold was set at p < 0.05. from surrounding structures, we estimated across-group differences from 5 additional seeds in the pontine tegmentum and 2 additional seeds 3. Results in the fourth ventricle. All analyses reported null findings (see Figs. S4 and S5). When exploring results at a more lenient threshold (p < 0.01, 3.1. Sociodemographic, clinical and neuropsychological characteristics uncorrected), a similar cluster appeared in the left hemisphere, with the peak coordinate at x = -4, y = -38, z = -30, although this result did not Sociodemographic, clinical and neuropsychological characteristics survive TFCE correction. of all participants are described in Table 1 and Table S3. Overall, we observed significant across-group differences in clinical and different 3.2.2. gPPI results neuropsychological domains and oddball task performance. Scheffé’s In the oddball > standard contrast, MDD patients showed, in com­ parison to HCs, lower positive connectivity between the right caudal LC Table 1 cluster from the above analysis and the left anterior cingulate cortex Sociodemographic and clinical characteristics of the study participants. (ACC), the right fusiform gyrus (FG) and the right cerebellum. When compared to aMCI, we observed lower positive connectivity between the MDD (n aMCI (n HCs (n = 20) = 16) = 26) right caudal LC and the posterior cerebellum in MDD patients during oddball stimuli detection as compared to standard stimuli. No differ­ Mean Mean Mean F df p Value ences were observed between aMCI and HCs (see Table 2 and Fig. 2A, C- (SD) (SD) (SD) Age, years 67.05 71.13 67.42 5.606 0.006* E). (4.31) (2.83) (4.33) Finally, in the MDD group, connectivity between the LC and the ACC Number of 3.35 correlated inversely with GDS score (r = − 0.471, p = 0.036). As can be depressive (1.69) seen in Fig. 2B, this correlation was indeed reflecting that we had two recurrences GDS 5.27 2.79 0.85 10.717 60 0.001*,‡ groups of subjects, those in active depression episode (n = 7) and those (4.88) (2.42) (1.14) asymptomatic (n = 13). These two groups differed not only in their GDS HDRS 10.27 3.93 0.90 23.377 61 0.001*,†,‡ scores (below and above the 4–5 points used as cut-off), but also in their (6.70) (3.13) (1.33) LC-ACC PPI estimates (Mann-Whitney’s U = 17; Z = − 2.26; p = 0.024). FAST 18.73 25.07 13.70 3.966 61 0.024*,§ We also observed a significant negative correlation with the number of (10.07) (15.56) (10.97) MMSE 26.67 25.86 29.15 14.784 60 0.001*,‡,§ recurrences (Ln transformed; r = − 0.507, p = 0.022) (Fig. 2B). These (2.23) (2.41) (1.14) analyses were controlled for age. Controlling for psychotropic medica­ Oddball task tion intake (15 patients were taking dual noradrenaline-serotonin anti­ Reaction time 452.61 453.77 429.71 0.504 60 0.607 depressants, while 5 subjects were taking SSRIs) did not modify our (86.21) (105.36) (44.21) Commission 5.47 17.79 2.60 7.239 58 0.002*,†,§ findings. We detected no further correlations between gPPI results and errors (4.55) (23.75) (1.79) the rest of clinical and performance variables, including the number of Omission 6.13 6.00 2.80 3.210 60 0.048* errors. errors (6.26) (5.34) (3.43) Vocabulary 28.10 31.44 45.08 24.986 59 0.001*,‡,§ 4. Discussion WAIS-III (7.78) (8.72) (9.18) Abbreviations: aMCI = amnestic type mild cognitive impairment individuals; In this study, we used an attentional oddball paradigm to assess FAST = Functional Assessment Staging; GDS = Geriatric Depression Scale; HCs subjects with late-life MDD in comparison to individuals with aMCI and = healthy controls; HDRS = Hamilton Depression Rating Scale; MDD = late-life HCs. Significant alterations in LC connectivity were specifically major depression disorder; MMSE = Mini-mental State Examination; SD = observed in the MDD group, and, remarkably, such alterations were standard deviation. Post-hoc tests of pair-wise differences. associated with clinical severity. Therefore, our results suggest that * p < 0.05 after FDR correction. disrupted connectivity of the LC characterizes individuals with late-life ‡ MDD – HCs. MDD, scaling with disease severity. Contrary to our expectations, † MDD – aMCI. however, the aMCI group did not show evidence of LC connectivity § aMCI – HCs. alteration, although this group showed an impaired task performance. 4 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 Fig. 1. Global connectivity results. Patients with late-life MDD showed lower global connectivity de­ gree in the right caudal LC in comparison to aMCI and HC groups. (A) Basal and sagittal view of the LC cluster (in light blue) and peak coordinate (dark blue) (pFWE < 0.05, TFCE corrected). The cluster is overlaid onto the LC study-specific mask (red con­ tour, see Supplementary material for details). This mask was down-sampled to the resolution of the functional time-series. As can be observed, our clus­ ter was located in the most caudal part of the LC. (B) Box-plot depicting global connectivity degree of the right caudal LC cluster for the three study groups. Values in the Y axis are normalized to fit a Gaussian distribution with zero mean and unitary variance, and, therefore, negative values should not be inter­ preted as negative connectivity. L = Left, R = Right. *pFWE < 0.05. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) (Bernard et al., 2011). Moreover, chemical damage to the LC with se­ Table 2 lective neurotoxins has been associated to depressive-like behaviors Between-group differences in LC connectivity during the oddball task. (Szot et al., 2016), such as reduced exploratory activity (van den Buuse Contrast Region MNI kE p TFCE et al., 2001), fewer social interactions (Cornwell-Jones et al., 1992), or Coordinates (x, value† value increased immobility in the forced swim test (Harro et al., 1999). y, z) Interestingly, our findings were lateralized to the right LC, although, MDD < Left anterior − 2, 32, 20 76 0.028 413.75 when lowering the significance threshold, we also observed similar al­ HCs cingulate cortex Right fusiform gyrus 40, − 48, − 24 1100 0.002 602.65 terations in the left LC. Why in our patients with MDD this alleged Vermis lobule VIII 6, − 58, − 28 115 0.033 403.21 pathological processes seems to start in the right hemisphere remains an Right Cerebellum 10, − 38, − 18 14 0.036 397.86 open question. lobe III Our findings were also located in the most caudal portion of the LC. Right Cerebellum 34, − 50, − 56 162 0.013 466.62 lobe VIII Although neurons from this location have been reported to be prefer­ Right Cerebellum 8, − 56, − 42 64 0.022 431.80 entially connecting to the spinal cord (Nakazato, 1987), we observed lobe IX functional connectivity alterations from there to brain regions such as MDD < Right Cerebellum 8, − 36, − 16 372 0.001 662.75 the ACC and the FG, as well as to the cerebellum. Previous research has aMCI lobe III (extending shown that, notwithstanding the fact that the LC is not entirely homo­ to Left lobe III) geneous, neurons projecting to cortical targets may be scattered Abbreviations: aMCI = amnestic type mild cognitive impairment individuals; throughout the LC (Schwarz and Luo, 2015). Moreover, it has been HCs = healthy controls; kE = cluster extent; MDD = late-life major depressive observed that LC neurons receive input from at least 9–15 different brain disorder patients; MNI = Montreal Neurological Institute, TFCE = Threshold- regions, which suggests that neural activity in the LC is largely inte­ Free Cluster Enhancement. grative (Schwarz et al., 2015), and is in agreement with our findings † All p-values were FWE-corrected, p < 0.05. showing that the same cluster displays connectivity alterations with cortical and cerebellar regions. The location of our findings in the caudal Specifically, although the clinical groups, when tested against controls, part of the LC may therefore be the result of the interaction of multiple displayed more omission errors, only aMCI individuals showed a higher factors, including the specific clinical groups assessed and the task number of commission errors during oddball performance, which con­ selected, as well as the existence of a rostro-caudal gradient of neural curs with previous reports (Tsolaki et al., 2017). loss and dysfunction related to age and neurodegeneration staging Individuals with late-life MDD displayed lower LC connectivity with (Theofilas et al., 2017). In this sense, patients with aMCI have been other brain regions. The role of the LC in depression has been evidenced reported to show connectivity alterations from the LC during resting- in previous research, ranging from a loss of NA neurons (Chan-Palay and state in relation to episodic memory (Jacobs et al., 2015), and the pos­ Asan, 1989), to intra and extra neuronal signaling pathway alterations sibility exists that they will show impaired connectivity during oddball 5 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 Fig. 2. gPPI results. (A) In comparison to HCs, the MDD group showed lower functional connectivity between the right LC and the left anterior cingulate cortex. (B) Scatter plots depicting the negative correlations between connectivity of the right LC with the left ACC and total Geriatric Depression Score (GDS) (left), and the number of depressive recurrences (Ln transformed, right). In the left plot, the qualitative distinction between asymptomatic patients and those in active depression episode is depicted with boxplots. Values in plots are age-adjusted. (C) The functional connectivity between LC and the right fusiform gyrus, (D) the lobule VIII of the vermis, and the right cerebellar lobules III, VIII and IX was also lower in MDD patients in comparison to HCs. (E) In comparison to the aMCI group, patients with MDD showed lower connectivity between the right LC and the bilateral cerebellar lobule III. L = Left, R = Right. performance from this caudal location at more advanced disease stages, et al., 2017). Such reduced connectivity between the LC and the ACC in relation to advanced age and neurodegenerative staging. Neverthe­ presumably involves both ascending and descending projections (Aston- less, some of the previous studies showing functional LC alterations in Jones and Cohen, 2005). As a central node of the salience network aMCI (Granholm et al., 2017; Elman et al., 2017) did not exclude pa­ (Menon and Uddin, 2010), the ACC is involved in the detection of tients with comorbid depression, while our aMCI sample was free from relevant stimuli through an adequate arousal inducing NA input (Gompf this confounding effect. This may also partially account for the lack of LC et al., 2010). At the same time, ACC efferent neural signals reach the LC connectivity findings reported here in individuals with aMCI. In any to inform about performance related costs associated with task difficulty case, since we did not make use of any imaging or cerebrospinal fluid and processing conflicts (Aston-Jones and Cohen, 2005). Positive biomarker, we cannot confirm that these subjects belong to the AD benefit-cost ratios may shift LC activity into phasic mode, which allows continuum and will eventually develop AD, which must be considered a accurately engaging in task performance (Aston-Jones and Cohen, study limitation. 2005). Regarding the regions showing lower LC input, the ACC has been Moreover, it is also important to highlight that disrupted connec­ consistently reported to show functional alterations in MDD (Bürger tivity between the LC and the ACC was associated with MDD severity 6 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 (GDS scores and number of recurrences), indicating that benefit-cost clinical data were exploratory and not corrected for multiple compari­ attentional processes may be increasingly impaired with both current sons, and should therefore be interpreted with caution. symptom severity and disease burden. Structural ACC abnormalities In conclusion, this study provides the first evidence of altered func­ have indeed been previously related to disease severity in MDD (Bij­ tional connectivity of the LC in patients with late-life MDD. Although sterbosch et al., 2018; Satterthwaite et al., 2016). Notably, the corre­ previous research has identified AD-related neuropathological signs in lation with GDS scores was indeed the result of a qualitative difference this noradrenergic source, we have not detected any significant alter­ between asymptomatic patients and those in an active depressive ation in patients with aMCI, and, therefore, our finding seems to spe­ episode, which suggests that LC-ACC connectivity may be a state marker cifically characterize the late-life MDD phenotype. In this sense, we have in late-life MDD. also observed that connectivity alterations from the LC involved We also observed reduced connectivity in MDD between the LC and different brain areas, such as the ACC, relevantly involved in MDD the FG, a region robustly related to both neutral (Strange et al., 2000) pathophysiology, and such alterations were related to current clinical and emotional oddball stimuli processing (Aleman et al., 2008). During severity and burden of disease. Further research assessing the putative visual attentional tasks, the FG may show hyperreactivity to distracters modulation of our results by noradrenergic agents, such as dual action in patients with MDD, hampering performance (Robertson et al., 2007). antidepressants, will elucidate whether interventions on the noradren­ Interestingly, treatment with the dual action antidepressant bupropion, ergic system may be considered as the first-line treatment option for which increases synaptic NA levels, modulates such hyperreactivity to patients with late-life MDD. distracters in the latter study. This result concurs with our findings and the alleged role of NA in increasing signal-to-noise ratio (Aston-Jones Declaration of Competing Interest and Waterhouse, 2016), which should result in enhanced focused attention. The authors report no biomedical financial interests or potential Finally, the LC of MDD patients also showed lower functional con­ conflicts of interest regarding this work. Dr. Soria served as a consultant nectivity with the cerebellum, mainly encompassing the vermis and the or continuing medical education (CME) speaker for Lundbeck, Otsuka, posterior cerebellar lobes. Anatomical connections between the LC and Janssen-Cilag, Exeltis. Dr. Urretavizcaya has received compensation for the cerebellum have been well established (Sara and Bouret, 2012), and lectures, advisories, or grants from Janssen-Cilagand, Lundbeck. Dr. NA connections between these two structures have been implicated in Menchón has received grants and served as a consultant, advisor or CME attentional orienting and sensorimotor processing of salient stimuli speaker for Janssen-Cilag, Lundbeck, Medtronic, Otsuka. All other au­ (Zhang et al., 2016), alterations of arousal state (Song et al., 2017), thors have nothing to disclose nor have any financial relationships with learning and memory processes through modulation of inhibitory commercial interests. neurotransmission in Purkinje neurons (Hoffer et al., 1973), and enhanced synaptic plasticity resulting from improvements in signal-to- Acknowledgments noise ratio of evoked activity (Gould et al., 1997). The vermis and the posterior cerebellar lobes are also densely connected with high-order The authors are grateful to all of the study participants and their cognitive regions such as the prefrontal, parahippocampal or cingulate families, and to the staff and technicians of Bellvitge University Hospital cortices, and, consequently, decreased NA input to the cerebellum may and Duran i Reynals Hospital who helped to recruit the sample for this indirectly alter neural processing in such areas (Arrigo et al., 2014; Kelly study. We thank CERCA Programme / Generalitat de Catalunya for and Strick, 2003). Indeed, abnormal functional connectivity between institutional support. the cerebellum and fronto-parieto-temporal regions has been shown in MDD samples (Yin et al., 2015). Funding This is the first study comparing functional preservation of the LC in two clinical groups by means of an interregional correlation analysis This study was supported by the Agency for Management of Uni­ during a visual oddball task. Moreover, since the LC is a tiny structure versity and Research Grants of the Catalan Government difficult to localize in fMRI time-series, our functional findings were (2017SGR1247), the Department of Health of the Generalitat de Cata­ overlaid onto a study-specific LC map, which confirmed the precise lunya (PERIS grant SLT002/16/249), the Carlos III Health Institute, location of our findings in the most caudal part of the nucleus. In any Spain (Grant PIE14/00034 and CIBERSAM), and FEDER Funds/Euro­ case, some limitations should be acknowledged. Despite all participants pean Regional Development Fund (ERDF) (‘A way to build Europe’). IdC were carefully characterized at the clinical and neuropsychological is supported by CIBERSAM and previously by a Ph.D. FI Grant from level, because of our naturalistic and consecutive recruitment strategy, AGAUR-Catalan Government (2016FI_B 00712), grant co-funded by the the aMCI group was somewhat older that the other two groups. Never­ European Social Fund (ESF) “ESF, Investing in your future”. IM-Z is theless, age was controlled for in all analyses, and the main results of the supported by a P-FIS grant (FI17/00294) from the Carlos III Health study involved the MDD group, which did not differ in age from HCs. Institute (Spain). AG-I was supported by a FPU 14/04822 grant. MU has Likewise, our study would have probably benefited from the comparison been funded by the Carlos III Health Institute through the Spanish with a group of younger patients with MDD, what would have also Ministry of Economy and Competitiveness. IF is supported by CIBERNED allowed to ascertain whether the reported findings characterize the and JMM has received grants from the Spanish Ministry of Economy and MDD phenotype regardless of the age of the subjects. Moreover, our Competitiveness and CIBERSAM. VS has received grants from the group patients with aMCI included fewer participants that the other two Institute of Health Carlos III through the Spanish Ministry of Economy groups, which may have limited the power to detect significant differ­ and Competitiveness and CS-M is supported by a Miguel Servet contract ences. The methods employed in this study do also have some limita­ (CPII16/00048) from the Carlos III Health Institute (Spain). tions. More specifically, our functional sequence was acquired with large voxels and we used a large smoothing kernel, which was needed to Appendix A. Supplementary data keep a good signal-to-noise ratio, certainly at the expenses of a greater spatial resolution. Further research with high-field MRI is warranted to Supplementary data to this article can be found online at https://doi. overcome this issue (see, for instance, Jacobs et al. (2020)). BOLD fMRI, org/10.1016/j.nicl.2020.102482. in addition, does not probably allow to detect fast changes in neuronal firing related to shifts from tonic to phasic activity in the LC. In this case, it might be of interest to combine fMRI with methods of higher temporal resolution. Finally, our correlation analyses between imaging and 7 I. del Cerro et al. NeuroImage: Clinical 28 (2020) 102482 References Granholm, E.L., Panizzon, M.S., Elman, J.A., et al., 2017. Pupillary responses as a biomarker of early risk for Alzheimer’s disease. J. 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