Late-Onset Alzheimer's Disease Polygenic Risk Profile Score Predicts Hippocampal Function.

BACKGROUND: We explored the cumulative effect of several late-onset Alzheimer's disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry. METHODS: In a sample of 231 healthy control subjects (19-55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level-dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects. RESULTS: There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested. CONCLUSIONS: There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes.

Altered hippocampal-parahippocampal function during stimulus encoding: a potential indicator of genetic liability for schizophrenia.

IMPORTANCE: Declarative memory-the ability to learn, store, and retrieve information-has been consistently reported to be altered in schizophrenia, and hippocampal-parahippocampal dysfunction has been implicated in this deficit. To elucidate the possible role of genetic risk factors in such findings, it is necessary to study healthy relatives of patients with schizophrenia who carry risk-associated genes but not the confounding factors related to the disorder. OBJECTIVE: To investigate whether altered brain responses, particularly in the hippocampus and parahippocampus, during the encoding phase of a simple declarative memory task are also observed in unaffected siblings who are at increased genetic risk for schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Functional magnetic resonance imaging was used with a simple visual declarative memory paradigm to test for differences in neural activation across normal control participants, patients with schizophrenia, and their healthy siblings. This study was conducted at a research center and included a total of 308 participants (181 normal control participants, 65 healthy siblings, and 62 patients with schizophrenia); all participants were white of European ancestry. MAIN OUTCOMES AND MEASURES: All participants completed a declarative memory task involving incidental encoding of neutral visual scenes interleaved with crosshair fixation while undergoing functional magnetic resonance imaging. Differences in hippocampus and parahippocampus activation and coupling across groups and correlations with accuracy were analyzed. Analyses were repeated in pairwise-matched samples. RESULTS: Both patients with schizophrenia and their healthy siblings showed reduced parahippocampal activation (bilaterally) and hippocampal-parietal (BA 40) coupling during the encoding of novel stimuli when compared with normal control participants. There was a significant positive correlation between parahippocampal activation during encoding and the visual-memory score. CONCLUSIONS AND RELEVANCE: These results suggest that altered hippocampal-parahippocampal function during encoding is an intermediate biologic phenotype related to increased genetic risk for schizophrenia. Therefore, measuring hippocampal-parahippocampal function with neuroimaging represents a potentially useful approach to understanding genetic mechanisms that confer risk for schizophrenia.

MicroSNiPer: a web tool for prediction of SNP effects on putative microRNA targets.

MicroRNAs are short, approximately 22 nucleotide noncoding RNAs binding to partially complementary sites in the 3'UTR of target mRNAs. This process generally results in repression of multiple targets by a particular microRNA. There is substantial interest in methods designed to predict the microRNA targets and effect of single nucleotide polymorphisms (SNPs) on microRNA binding, given the impact of microRNA on posttranscriptional regulation and its potential relation to complex diseases. We developed a web-based application, MicroSNiPer, which predicts the impact of a SNP on putative microRNA targets. This application interrogates the 3'-untranslated region and predicts if a SNP within the target site will disrupt/eliminate or enhance/create a microRNA binding site. MicroSNiPer computes these sites and examines the effects of SNPs in real time. MicroSNiPer is a user-friendly Web-based tool. Its advantages include ease of use, flexibility, and straightforward graphical representation of the results. It is freely accessible at http://cbdb.nimh.nih.gov/microsniper.

Data-driven methodology illustrating mechanisms underlying word list recall: applications to clinical research.

OBJECTIVE: Word list learning tasks such as the California Verbal Learning Test (CVLT; Delis, Kramer, Kaplan, & Ober, 1987) are widely used to investigate recall strategies. Participants who recall the most words generally employ semantic techniques, whereas those with poor recall (e.g., patients with schizophrenia) rely on serial techniques. However, these conclusions are based on formulas that assume that categories reflect semantic associations, bind strategy to overall performance, and neglect strategy changes over 5 trials. Therefore, we derived novel measures-independent of recall performance-to compute strategies across trials and identify whether diagnosis predicts recall strategy. METHOD: Participants were included on the basis of performance on the CVLT (i.e., total words recalled over 5 trials). The 50 highest and 50 lowest performers among healthy volunteers (n = 100) and patients with schizophrenia (n = 100) were selected. Novel measures of recall and transition probability were calculated and analyzed by permutation tests. RESULTS: Recall patterns and strategies of patients resembled those of controls with similar performance levels: Regardless of diagnosis, low performers were more likely to recall the first 2 and last 4 items from the list; high performers increased engagement of semantically based transitions across the 5 trials, whereas low performers did not. CONCLUSIONS: Cognitive strategy must be considered independent of overall performance before attributing poor performance to degraded learning processes. Our results demonstrate the importance of departing from global scoring techniques, especially when working with clinical populations such as patients with schizophrenia for whom episodic memory deficits are a hallmark feature.

Bio-swarm-pipeline: a light-weight, extensible batch processing system for efficient biomedical data processing.

A streamlined scientific workflow system that can track the details of the data processing history is critical for the efficient handling of fundamental routines used in scientific research. In the scientific workflow research community, the information that describes the details of data processing history is referred to as "provenance" which plays an important role in most of the existing workflow management systems. Despite its importance, however, provenance modeling and management is still a relatively new area in the scientific workflow research community. The proper scope, representation, granularity and implementation of a provenance model can vary from domain to domain and pose a number of challenges for an efficient pipeline design. This paper provides a case study on structured provenance modeling and management problems in the neuroimaging domain by introducing the Bio-Swarm-Pipeline. This new model, which is evaluated in the paper through real world scenarios, systematically addresses the provenance scope, representation, granularity, and implementation issues related to the neuroimaging domain. Although this model stems from applications in neuroimaging, the system can potentially be adapted to a wide range of bio-medical application scenarios.

Neural correlates of probabilistic category learning in patients with schizophrenia.

Functional neuroimaging studies of probabilistic category learning in healthy adults report activation of cortical-striatal circuitry. Based on previous findings of normal learning rate concurrent with an overall performance deficit in patients with schizophrenia, we hypothesized that relative to healthy adults, patients with schizophrenia would display preserved caudate nucleus and abnormal prefrontal cortex activation during probabilistic category learning. Forty patients with schizophrenia receiving antipsychotic medication and 25 healthy participants were assessed on interleaved blocks of probabilistic category learning and control tasks while undergoing blood oxygenation level-dependent functional magnetic resonance imaging. In addition to the whole sample of patients with schizophrenia and healthy adults, a subset of patients and healthy adults matched for good learning was also compared. In the whole sample analysis, patients with schizophrenia displayed impaired performance in conjunction with normal learning rate relative to healthy adults. The matched comparison of patients and healthy adults classified as good learners revealed greater caudate and dorsolateral prefrontal cortex activity in the healthy adults and greater activation in a more rostral region of the dorsolateral prefrontal, cingulate, parahippocampal and parietal cortex in patients. These results demonstrate that successful probabilistic category learning can occur in the absence of normal frontal-striatal function. Based on analyses of the patients and healthy adults matched on learning and performance, a minority of patients with schizophrenia achieve successful probabilistic category learning and performance levels through differential activation of a circumscribed neural network which suggests a compensatory mechanism in patients showing successful learning.

Heritability of brain morphology related to schizophrenia: a large-scale automated magnetic resonance imaging segmentation study.

BACKGROUND: Schizophrenia is a devastating psychiatric disorder with a strong genetic component that has been related to a number of structural brain alterations. Currently available data on the heritability of these structural changes are inconsistent. METHODS: To examine heritability of morphological alterations in a large sample, we used a novel and validated fully-automated whole brain segmentation technique to study disease-related variability and heritability in anatomically defined regions of interest in 221 healthy control subjects, 169 patients with schizophrenia, and 183 unaffected siblings. RESULTS: Compared with healthy control subjects, patients showed a bilateral decrease in hippocampal and cortical gray matter volume and increases in bilateral dorsal striatum and right lateral ventricle. No significant volumetric differences were found in unaffected siblings compared with normal control subjects in any structure. Post hoc analysis of the dorsal striatum showed the volumetric increase to be widespread, including caudate, putamen, and globus pallidus. With Risch's lambda (lambda(s)), we found strong evidence for heritability of reduced cortical volume and moderate evidence for hippocampal volume, whereas abnormal striatal and ventricle volumes showed no sign of heritability. Additional exploratory analyses were performed on amygdala, thalamus, nucleus accumbens, ventral diencephalon, and cerebral and cerebellar cortex and white matter. Of these regions, patients showed increased volume in ventral diencephalon and cerebellum. CONCLUSIONS: These findings support evidence of genetic control of brain volume even in adults, particularly of hippocampal and neocortical volume and of cortical volumetric reductions being familial, but do not support measures of subcortical volumes per se as representing intermediate biologic phenotypes.

Differentiating allocation of resources and conflict detection within attentional control processing.

Increasing demands for conflict detection and for allocation of attentional resources increase the need for attentional control. While prior evidence suggests that different cortical regions are preferentially engaged by these two attentional processes, the effect of increasing demand for conflict detection and/or allocation of attentional resources has been relatively unexplored. We designed a novel task (the 'variable attentional control'--VAC--task) that varies the demand for attentional control by increasing conflict detection and allocation of attentional resources within the same stimuli. We studied 34 subjects who underwent event-related functional magnetic resonance imaging while performing the VAC task. Increasing demand for attentional control, as reflected by longer reaction time and reduced accuracy, was associated with greater activation in the dorsolateral prefrontal cortex, parietal cortex and dorsal cingulate. Furthermore, an increase in conflict detection was associated with greater dorsal cingulate activity, whereas an increase in demand for allocation of attentional resources implied greater activation in the dorsolateral prefrontal and parietal cortices. In essence, in addition to allowing the exploration of the overall effects of increasing demand for attentional control, our novel task also allowed parsing of the neural components of attentional control into those related to allocation of attentional resources and those related to conflict detection.

Brain regions underlying response inhibition and interference monitoring and suppression.

Response inhibition and interference monitoring and suppression are two important aspects of cognitive control. Previous functional imaging studies have suggested a common network of brain regions underlying these cognitive processes; the dorsolateral prefrontal cortex (DLPFC), the ventrolateral prefrontal cortex (VLPFC), the dorsal cingulate (dACC), and the parietal cortex (PC). The relative contribution of these regions to these cognitive subprocesses, however, has not been determined. Based on previous findings supporting a role for dACC in the monitoring of conflicting information within a stimulus, we hypothesized greater activity in this cortical region during interference monitoring and suppression relative to response inhibition. On the other hand, as response inhibition is characterized by differential cognitive processes such as control implementation, top down modulation of the response, expectancy, and inhibition of behavioural response, we hypothesized increased activity in the other cortical nodes of the cognitive control network relative to interference monitoring and suppression. To this end, we conducted an event-related functional magnetic resonance imaging (fMRI) study in 57 healthy volunteers using a task preferentially involving either interference monitoring and suppression or response inhibition. Accuracy for response inhibition was lower than for interference monitoring and suppression. Imaging data showed activation in DLPFC, dACC, VLPFC, PC for both conditions. Comparisons between the two conditions indicated greater activation bilaterally in DLPFC, VLPFC and PC during response inhibition, and greater activation in the dACC during interference monitoring and suppression. These results extend previous findings by suggesting regional functional specialization within a cortical network supporting cognitive control.

Neural mechanisms underlying probabilistic category learning in normal aging.

Probabilistic category learning engages neural circuitry that includes the prefrontal cortex and caudate nucleus, two regions that show prominent changes with normal aging. However, the specific contributions of these brain regions are uncertain, and the effects of normal aging have not been examined previously in probabilistic category learning. In the present study, using a blood oxygenation level-dependent functional magnetic resonance imaging block design, 18 healthy young adults (mean age, 25.5 +/- 2.6 years) and 15 older adults (mean age, 67.1 +/- 5.3 years) were assessed on the probabilistic category learning "weather prediction" test. Whole-brain functional images acquired using a 1.5T scanner (General Electric, Milwaukee, WI) with gradient echo, echo planar imaging (3/1 mm; repetition time, 3000 ms; echo time, 50 ms) were analyzed using second-level random-effects procedures [SPM99 (Statistical Parametric Mapping)]. Young and older adults displayed equivalent probabilistic category learning curves, used similar strategies, and activated analogous neural networks, including the prefrontal and parietal cortices and the caudate nucleus. However, the extent of caudate and prefrontal activation was less and parietal activation was greater in older participants. The percentage correct and reaction time were mainly positively correlated with caudate and prefrontal activation in young individuals but positively correlated with prefrontal and parietal cortices in older individuals. Differential activation within a circumscribed neural network in the context of equivalent learning suggests that some brain regions, such as the parietal cortices, may provide a compensatory mechanism for healthy older adults in the context of deficient prefrontal cortex and caudate nuclei responses.