Common Blood Flow Changes Across Visual Tasks: I. Increases in Subcortical Structures and Cerebellum but Not in Nonvisual Cortex

Nine positron emission tomography (PET) studies of human visual information processing were reanalyzed to determine the consistency across experiments of blood flow increases during active tasks relative to passive viewing of the same stimulus array. No consistent blood flow increases were found in cerebral cortex outside of the visual system, but increases were seen in the thalamus and cerebellum. Although most tasks involve increases in arousal, establishing an intention or behavioral goal, setting up control structures for sequencing task operations, detecting targets, etc., these operations do not produce blood flow increases, detectable with the present methods, in localized cortical regions that are common across tasks. Common subcortical regions, however, may be involved. A left cerebellar and a medial cerebellar focus reflected motor-related processes. Blood flow increases in these regions only occurred in experiments in which the subject made an overt response and were largest when the response was made in the active but not passive condition. These motor-related processes were more complex than simple motor execution, however, since increases were still present when the response was made in both the active and passive conditions. These cerebellar increases may reflect processes related to response selection.Blood flow increases in a right cerebellar region were not motor-related. Increases were not modulated by the presence or absence of motor responses during either the active or passive conditions, and increases were sensitive to within-experiment variables that held the motor response constant. Increases occurred in both language and nonlanguage tasks and appeared to involve a general nonmotor process, but the nature of that process was difficult to specify. A right thalamic focus was sensitive to variables related to focal attention, suggesting that this region was involved in attentional engagement. Right thalamic increases were also correlated over conditions with increases in the left and medial cerebellum, perhaps reflecting additional contributions from motor-related nuclei receiving cerebellar projections. Blood flow increases in a left thalamic focus were completely uncorrelated over conditions with increases in the right thalamus, indicating that it was involved in different functions. Both the left thalamus and right cerebellum yielded larger blood flow increases when subjects performed a complex rather than simple language task, possibly reflecting a language-related pathway. Blood flow increases in the left thalamus were also observed, however, during nonlanguage tasks.Psycholog

Stochastic and epistemic uncertainty propagation in LCA

Purpose: When performing uncertainty propagation, most LCA practitioners choose to represent uncertainties by single probability distributions and to propagate them using stochastic methods. However the selection of single probability distributions appears often arbitrary when faced with scarce information or expert judgement (epistemic uncertainty). Possibility theory has been developed over the last decades to address this problem. The objective of this study is to present a methodology that combines probability and possibility theories to represent stochastic and epistemic uncertainties in a consistent manner and apply it to LCA. A case study is used to show the uncertainty propagation performed with the proposed method and compare it to propagation performed using probability and possibility theories alone. Methods: Basic knowledge on the probability theory is first recalled, followed by a detailed description of hal-00811827, version 1- 11 Apr 2013 epistemic uncertainty representation using fuzzy intervals. The propagation methods used are the Monte Carlo analysis for probability distribution and an optimisation on alpha-cuts for fuzzy intervals. The proposed method (noted IRS) generalizes the process of random sampling to probability distributions as well as fuzzy intervals, thus making the simultaneous use of both representations possible

Intermediate Phenotypes Identify Divergent Pathways to Alzheimer's Disease

Background: Recent genetic studies have identified a growing number of loci with suggestive evidence of association with susceptibility to Alzheimer's disease (AD). However, little is known of the role of these candidate genes in influencing intermediate phenotypes associated with a diagnosis of AD, including cognitive decline or AD neuropathologic burden. Methods/Principal Findings: Thirty-two single nucleotide polymorphisms (SNPs) previously implicated in AD susceptibility were genotyped in 414 subjects with both annual clinical evaluation and completed brain autopsies from the Religious Orders Study and the Rush Memory and Aging Project. Regression analyses evaluated the relation of SNP genotypes to continuous measures of AD neuropathology and cognitive function proximate to death. A SNP in the zinc finger protein 224 gene (ZNF224, rs3746319) was associated with both global AD neuropathology (p = 0.009) and global cognition (p = 0.002); whereas, a SNP at the phosphoenolpyruvate carboxykinase locus (PCK1, rs8192708) was selectively associated with global cognition (p = 3.57×10−4). The association of ZNF224 with cognitive impairment was mediated by neurofibrillary tangles, whereas PCK1 largely influenced cognition independent of AD pathology, as well as Lewy bodies and infarcts. Conclusions/Significance: The findings support the association of several loci with AD, and suggest how intermediate phenotypes can enhance analysis of susceptibility loci in this complex genetic disorder

Susceptibility to neurofibrillary tangles: role of the PTPRD locus and limited pleiotropy with other neuropathologies

Tauopathies, including Alzheimer’s disease (AD) and other neurodegenerative conditions, are defined by a pathological hallmark: neurofibrillary tangles (NFT). NFT accumulation is thought to be closely linked to cognitive decline in AD. Here, we perform a genome-wide association study for NFT pathologic burden and report the association of the PTPRD locus (rs560380, p=3.8×10−8) in 909 prospective autopsies. The association is replicated in an independent dataset of 369 autopsies. The association of PTPRD with NFT is not dependent on the accumulation of amyloid pathology. In contrast, we find that the ZCWPW1 AD susceptibility variant influences NFT accumulation and that this effect is mediated by an accumulation of amyloid β plaques. We also performed complementary analyses to identify common pathways that influence multiple neuropathologies which co-exist with NFT and found suggestive evidence that certain loci may influence multiple different neuropathological traits, including tau, amyloid β plaques, vascular injury and Lewy bodies. Overall, these analyses offer an evaluation of genetic susceptibility to NFT, a common endpoint for multiple different pathologic processes

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Rare Functional Variant in TM2D3 is Associated with Late-Onset Alzheimer's Disease

We performed an exome-wide association analysis in 1393 late-onset Alzheimer's disease (LOAD) cases and 8141 controls from the CHARGE consortium. We found that a rare variant (P155L) in TM2D3 was enriched in Icelanders (similar to 0.5% versus <0.05% in other European populations). In 433 LOAD cases and 3903 controls from the Icelandic AGES substudy, P155L was associated with increased risk and earlier onset of LOAD [odds ratio (95% CI) = 7.5 (3.5-15.9), p = 6.6x10(-9)]. Mutation in the Drosophila TM2D3 homolog, almondex, causes a phenotype similar to loss of Notch/Presenilin signaling. Human TM2D3 is capable of rescuing these phenotypes, but this activity is abolished by P155L, establishing it as a functionally damaging allele. Our results establish a rare TM2D3 variant in association with LOAD susceptibility, and together with prior work suggests possible links to the beta-amyloid cascade.Peer reviewe

Multi-ancestry genome-wide association meta-analysis of Parkinson?s disease

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations

Defining the causes of sporadic Parkinson's disease in the global Parkinson's genetics program (GP2)

The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development