Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis:an application to perfusion imaging

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow

Recommendations, guidelines, and best practice for the use of human induced pluripotent stem cells for neuropharmacological studies of neuropsychiatric disorders

The number of individuals suffering from neuropsychiatric disorders (NPDs) has increased worldwide, with 3 million disability-adjusted life-years calculated in 2019. Though research using various approaches including genetics, imaging, clinical and animal models has advanced our knowledge regarding NPDs, we still lack basic knowledge regarding the underlying pathophysiological mechanisms. Moreover, there is an urgent need for highly effective therapeutics for NPDs i. Human induced pluripotent stem cells (hiPSCs) generated from somatic cells enabled scientists to create brain cells in a patient-specific manner. However, there are challenges to the use of hiPSCs that need to be addressed. In the current paper, consideration of best practices for neuropharmacological and neuropsychiatric research using hiPSCs will be discussed. Specifically, we provide recommendations for best practice in patient recruitment, including collecting demographic, clinical, medical (before and after treatment and response), diagnostic (incl. scales) and genetic data from the donors. We highlight considerations regarding donor genetics and sex, in addition to discussing biological and technical replicates. Furthermore, we present our views on selecting control groups/lines, experimental designs, and considerations for conducting neuropharmacological studies using hiPSC-based models in the context of NPDs. In doing so, we explore key issues in the field concerning reproducibility, statistical analysis, and how to translate in vitro studies into clinically relevant observations. The aim of this article is to provide a key resource for hiPSC researchers to perform robust and reproducible neuropharmacological studies, with the ultimate aim of improving identification and clinical translation of novel therapeutic drugs for NPDs

Morphometrical and microdensitometrical studies on peptide- and tyrosine hydroxylase-like immunoreactivities in the forebrain of rats prenatally exposed to methylazoxymethanol acetate.

Methylazoxymethanol acetate (MAM Ac) injected into pregnant rats at a dose of 25 mg/kg at gestational day 15 causes microcephaly due to an atrophy of various telencephalic areas, mainly neocortex, hippocampus and basal ganglia. Previous studies demonstrated alterations in various neurochemical markers of classical transmitter systems in these regions. The present paper deals with changes in peptide and tyrosine hydroxylase (TH)-containing neurons in MAM Ac-induced microcephaly using immunocytochemistry coupled with computer-assisted morphometry and microdensitometry. No change in the number of vasoactive intestinal polypeptide (VIP)-immunoreactive neurons in the neocortex and neuropeptide Y (NPY)-immunoreactive neurons in the nucleus caudatus-putamen was found whereas cholecystokinin (CCK)-and NPY-immunoreactive neurons in the neocortex and CCK- and VIP-immunoreactive neurons in the hippocampus were decreased. The reduction of the latter peptide containing neuronal populations led to a maintained density of cells in MAM Ac-exposed rats, due to the parallel reduction of the overall mass of these regions. TH immunoreactivity was found to be unchanged in the basal ganglia, and increased in the cerebral cortex in agreement with previous reports on noradrenaline cortical system after MAM Ac exposure. The present results show a heterogenous vulnerability of different peptide immunoreactive neuronal populations to MAM Ac exposure. The sparing of VIP- and NPY-immunoreactive neurons may be due to their late development in the neocortex and striatum, respectively. The hypothesis is introduced that cortical VIP interneurons can develop independent of marked alterations in the intrinsic circuitry of the cortical region

Overexpression of forebrain CRH during early life increases trauma susceptibility in adulthood

Although early-life stress is a significant risk factor for developing anxiety disorders, including posttraumatic stress disorder (PTSD), the underlying mechanisms are unclear. Corticotropin releasing hormone (CRH) is disrupted in individuals with PTSD and early-life stress and hence may mediate the effects of early-life stress on PTSD risk. We hypothesized that CRH hyper-signaling in the forebrain during early development is sufficient to increase response to trauma in adulthood. To test this hypothesis, we induced transient, forebrain-specific, CRH overexpression during early-life (pre-puberty, CRHOEdev) in double-mutant mice (Camk2a-rtta2 × tetO-Crh) and tested their behavioral and gene expression responses to the predator stress model of PTSD in adulthood. In one cohort of CRHOEdev exposed and unexposed mice, avoidance and arousal behaviors were examined 7-15 days after exposure to predator stress. In another cohort, gene expression changes in Crhr1, Crhr2, and Fkbp51 in forebrain of CRHOEdev exposed and unexposed mice were examined 7 days after predator stress. CRHOEdev induced robust increases in startle reactivity and reductions in startle inhibition independently of predator stress in both male and female mice. Avoidance behaviors after predator stress were highly dependent on sex and CRHOEdev exposure. Whereas stressed females exhibited robust avoidance responses that were not altered by CRHOEdev, males developed significant avoidance only when exposed to both CRHOEdev and stress. Quantitative real-time-PCR analysis indicated that CRHOEdev unexposed males exhibit significant changes in Crhr2 expression in the amygdala and bed nucleus stria terminalis in response to stress, whereas males exposed to CRHOEdev did not. Similar to CRHOEdev males, females exhibited no significant Crhr2 gene expression changes in response to stress. Cortical Fkbp51 expression was also significantly reduced by stress and CRHOEdev exposure in males, but not in females. These findings indicate that forebrain CRH hyper-signaling in early-life is sufficient to increase enduring effects of adult trauma and attenuate Crhr2 expression changes in response to stress in males. These data support growing evidence for significant sex differences in response to trauma, and support further study of CRHR2 as a candidate mechanism for PTSD risk.Neuropsychopharmacology advance online publication, 9 December 2015; doi:10.1038/npp.2015.338

Morphometrical and microdensitometrical studies on phenylethanolamine-N-methyltransferase- and neuropeptide Y-immunoreactive nerve terminals and on glucocorticoid receptor-immunoreactive nerve cell nuclei in the paraventricular hypothalamic nucleus in adult and old male rats.

The phenylethanolamine-N-methyltransferase- and neuropeptide Y-immunoreactive nerve terminal profiles and the glucocorticoid receptor-immunoreactive nuclear profiles have been characterized in the parvocellular part of the paraventricular hypothalamic nucleus of the adult (3 month) and the old (24 month) male rat. The phenylethanolamine-N-methyltransferase-, neuropeptide Y- and glucocorticoid receptor-immunoreactive structures have been demonstrated by means of the indirect immunoperoxidase procedure and analysed in a quantitative way by means of morphometrical and microdensitometrical approaches using both semiautomatic and automatic image analysis. During aging there is (a) a marked reduction in the number of neuropeptide Y-immunoreactive profiles, a moderate reduction of phenylethanolamine-N-methyltransferase-immunoreactive profiles and a small reduction in the number of glucocorticoid receptor-immunoreactive profiles without a significant change in the evenness of distribution of such profiles as evaluated by means of Gini's index; (b) a loss of the significant correlation in the distribution of the glucocorticoid receptor- and phenylethanolamine-N-methyltransferase-immunoreactive profiles at the two most caudal levels analysed (A5150 and A5270 micron) while a significant correlation developed between these two distributions at a more rostral level (A5400 micron); (c) a substantial decline in the overlap area of the glucocorticoid receptor- and phenylethanolamine-N-methyltransferase-immunoreactive profiles at four out of five rostrocaudal levels analysed; (d) a marked reduction in the density-intensity of the neuropeptide Y-immunoreactive profiles and a small significant reduction in the density-intensity of the phenylethanolamine-N-methyltransferase-immunoreactive profiles without any associated changes in the intensity of the glucocorticoid receptor-immunoreactive profiles. Furthermore, three-dimensional reconstructions of the overall distribution of the glucocorticoid receptor-, phenylethanolamine-N-methyltransferase- and neuropeptide Y-immunoreactive structures have been made in the paraventricular hypothalamic nucleus of the adult male rat. The present results indicate a reduction of neuropeptide Y- and phenylethanolamine-N-methyltransferase-immunoreactive nerve terminal profiles in the parvocellular part of the paraventricular hypothalamic nucleus during aging. These results may in part reflect a loss of neuropeptide Y-like peptides in phenylethanolamine-N-methyltransferase-immunoreactive nerve terminals of the paraventricular hypothalamic nucleus, favouring our view that during aging the modulatory peptides may be lost

A clinical-genetic approach to assessing cardiovascular risk in patients with CKD

BACKGROUND: Coronary heart disease (CHD) is the primary cause of death in individuals with chronic kidney disease (CKD), but current equations for assessing coronary risk have low accuracy in this group. We have reported that the addition of a genetic risk score (GRS) to the Framingham risk function improved its predictive capacity in the general population. The aims of this study were to evaluate the association between this GRS and coronary events in the CKD population and to determine whether the addition of the GRS to coronary risk prediction functions improves the estimation of coronary risk at the earliest possible stages of kidney disease. METHODS: A total of 632 CKD patients, aged 35-74 years, who had Stage 4-5 CKD, were on dialysis, had a functioning renal transplant or had returned to dialysis after transplant failure were included and followed up for a mean of 9.3 years. The transitions between disease states and the development of coronary events were registered. The increase in predictive ability that was obtained by including the GRS was measured as the improvement in the C-statistic and as the net reclassification index. RESULTS: The GRS was independently associated with the risk of CHD (hazards ratio 1.34; 95% confidence interval 1.04-1.71; P = 0.022), especially in Stages 4 and 5 CKD, and kidney transplant patients. A coronary risk prediction function that incorporated chronic kidney disease (CKD) disease state, age, sex and the GRS had significantly greater predictive capacity (AUC 70.1, P = 0.01) and showed good reclassification (net reclassification improvement 28.6). CONCLUSION: This new function, combining genetic and clinical data, identifies CKD patients with a high risk of coronary events more accurately, allowing us to prevent such events more effectively

Structural brain changes in patients with recurrent major depressive disorder presenting with anxiety symptoms

Major depressive disorder (MDD) presents with extensive clinical heterogeneity. In particular, overlap with anxiety symptoms is common during depressive episodes and as a comorbid disorder. The aim of this study was to test for morphological brain differences between patients having a history of recurrent MDD with, and without, anxiety symptoms (MDD+A and MDD−A)

Sparse multivariate measures of similarity between intra-modal neuroimaging datasets

An increasing number of neuroimaging studies are now based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labelling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow

Neural responses to happy facial expressions in major depression following antidepressant treatment

OBJECTIVE: Processing affective facial expressions is an important component of interpersonal relationships. However, depressed patients show impairments in this system. The present study investigated the neural correlates of implicit processing of happy facial expressions in depression and identified regions affected by antidepressant therapy. METHOD: Two groups of subjects participated in a prospective study with functional magnetic resonance imaging (fMRI). The patients were 19 medication-free subjects (mean age, 43.2 years) with major depression, acute depressive episode, unipolar subtype. The comparison group contained 19 matched healthy volunteers (mean age, 42.8 years). Both groups underwent fMRI scans at baseline (week 0) and at 8 weeks. Following the baseline scan, the patients received treatment with fluoxetine, 20 mg daily. The fMRI task was implicit affect recognition with standard facial stimuli morphed to display varying intensities of happiness. The fMRI data were analyzed to estimate the average activation (overall capacity) and differential response to variable intensity (dynamic range) in brain systems involved in processing facial affect. RESULTS: An attenuated dynamic range of response in limbic-subcortical and extrastriate visual regions was evident in the depressed patients, relative to the comparison subjects. The attenuated extrastriate cortical activation at baseline was increased following antidepressant treatment, and symptomatic improvement was associated with greater overall capacity in the hippocampal and extrastriate regions. CONCLUSIONS: Impairments in the neural processing of happy facial expressions in depression were evident in the core regions of affective facial processing, which were reversed following treatment. These data complement the neural effects observed with negative affective stimuli