Biology subjects

Rowe, J. B.

Publications and source records attributed to Rowe, J. B..

32 records · Page 2Linked to original sources

bioRxiv2019

Evidence of a Causal Association Between Cancer and Alzheimer’s Disease: a Mendelian Randomization Analysis

ObjectivesTo determine whether cancer confers protection against Alzheimers disease and to evaluate the relationship in the context of smoking-related cancers versus non-smoking related cancers\n\nDesignMendelian randomization analysis using cancer-associated genetic variants as instrumental variables\n\nSettingInternational Genomics of Alzheimers Project\n\nParticipants17,008 Alzheimers disease cases and 37,154 controls\n\nMain outcome measuresOdds ratio of Alzheimers disease per 1-unit higher log odds of genetically predicted cancer\n\nResultsWe found that genetically predicted lung cancer (OR 0.91, 95% CI 0.84-0.99, p=0.019), leukemia (OR 0.98, 95% CI 0.96-0.995, p=0.012), and breast cancer (OR 0.94, 95% CI 0.89-0.99, p=0.028) were associated with 9.0%, 2.4%, and 5.9% lower odds of Alzheimers disease, respectively, per 1-unit higher log odds of cancer. When genetic predictors of all cancers were pooled, cancer was associated with 2.5% lower odds of Alzheimers disease (OR 0.98, 95% CI 0.96-0.988, p=0.00027) per 1-unit higher log odds of cancer. Finally, genetically predicted smoking-related cancers showed a more robust inverse association with Alzheimers disease than non-smoking related cancers (5.2% lower odds, OR 0.95, 95% CI 0.92-0.98, p=0.0026, vs. 1.9% lower odds, OR 0.98, 95% CI 0.97-0.995, p=0.0091).\n\nConclusionsGenetically predicted lung cancer, leukemia, breast cancer, and all cancers in aggregate are associated with lower odds of incident Alzheimers disease. Furthermore, the risk of Alzheimers disease was lower in smoking-related versus non-smoking related cancers. These results add to the substantial epidemiological evidence of an inverse association between history of cancer and lower odds of Alzheimers disease, by suggesting a causal basis for this relationship.

epidemiology↗

bioRxiv2019

Correlation Of Microglial Activation With White Matter Changes In Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the second-leading degenerative dementia after Alzheimers disase. Neuropathologically, it is characterized by alpha-synuclein protein deposition with variable degree of concurrent Alzheimer pathology. Neuroinflammation is increasingly recognized as a significant contributor of degeneration.\n\nObjectiveto examine the relationship between microglial activation as measured with [11C]-PK11195 brain PET and MR diffusion tensor imaging (DTI) in DLB.\n\nMethodsnineteen clinically probable DLB and 20 similarly aged controls underwent structural MRI with T1-weighted and 3T DTI sequences. Eighteen DLB subjects also underwent [11C]-PK11195 PET imaging. Tract-Based Spatial Statistics (TBSS) were performed to compare DTI parameters in DLB relative to controls and identify associations of [11C]-PK11195 binding with white matter integrity.\n\nResultsTBSS showed widespread changes in all DTI parameters in the DLB group compared to controls (Threshold Free Cluster Enhancement (TFCE) p < 0.05). [11C]-PK11195 binding in parietal cortices also correlated with widespread lower mean and radial diffusivity (TFCE p < 0.05).\n\nConclusionOur study demonstrates that higher PK11195 binding is associated with a relative preservation of white matter, positioning neuroinflammation as a potential early marker in the DLB pathogenic cascade.

neuroscience↗

bioRxiv2019

Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance

Neuroinflammation is a key part of the etio-pathogenesis of Alzheimers disease. We test the relationship between neuroinflammation and the disruption of functional connectivity in large-scale networks, and their joint influence on cognitive impairment. We combined [11C]PK11195 positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) in 28 humans (13 females/15 males) with clinical diagnosis of probable Alzheimers disease or mild cognitive impairment with positive PET biomarker for amyloid, and 14 age-, sex-, and education-matched healthy humans (8 females/6 males). Source-based inflammetry was used to extract principal components of [11C]PK11195 PET signal variance across all participants. rs-fMRI data were pre-processed via independent component analyses to classify neuronal and non-neuronal signals. Multiple linear regression models identified sources of signal co-variance between neuroinflammation and brain connectivity profiles, in relation to group and cognitive status. Patients showed significantly higher [11C]PK11195 binding relative to controls, in a distributed spatial pattern including the hippocampus, medial, and inferior temporal cortex. Patients with enhanced loading on this [11C]PK11195 binding distribution displayed diffuse abnormal functional connectivity. The expression of a stronger association between such abnormal connectivity and higher levels of neuroinflammation correlated with worse cognitive deficits. Our study suggests that neuroinflammation relates to the pathophysiological changes in network function that underlie cognitive deficits in Alzheimers disease. Neuroinflammation, and its association with functionally-relevant reorganisation of brain networks, is proposed as a target for emerging immuno-therapeutic strategies aimed at preventing or slowing the emergence of dementia. Significance StatementNeuroinflammation is an important aspect of Alzheimers disease (AD), but it was not known whether the influence of neuroinflammation on brain network function in humans was important for cognitive deficit. Our study provides clear evidence that in vivo neuroinflammation in AD impairs large-scale network connectivity; and that the link between inflammation and functional network connectivity is relevant to cognitive impairment. We suggest that future studies should address how neuroinflammation relates to network function as AD progresses; and whether the neuroinflammation in AD is reversible, as the basis of immunotherapeutic strategies to slow the progression of AD.

neuroscience↗

bioRxiv2019

Tau pathology in early Alzheimer’s disease disrupts selective neurophysiological networks dynamics

The role of aggregation of misfolded Tau protein in the pathogenesis of Alzheimers disease is the subject of rapid biomarker development and new therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography (E/MEG) in combination with [18F]AV1451 PET scanning to quantify Tau-dependent network disruption. Using a graph theoretical approach to MEG connectivity, we quantified nodal measures of functional segregation, centrality and efficiency of information transfer. We correlated these metrics against the nodes uptake of [18F]AV1451. There were both regional- and frequency-specific effects of Tau levels on the efficiency of information transfer and network segregation in early AD. Tau correlated with temporal regional participation coefficient (in delta, theta, beta bands); and temporal lobar eigenvector centrality (in theta, alpha, beta bands), but greater eccentricity at higher frequencies (gamma). The results support the translational development of neurophysiological "signatures" as biomarkers of Alzheimers disease, with potential to facilitate experimental medicines studies.

neuroscience↗

bioRxiv2019

Neuropathological validation of the MDS-PSP criteria with PSP and other frontotemporal lobar degeneration

BackgroundProgressive supranuclear palsy (PSP) is clinically heterogeneous. Clinical diagnostic criteria were revised in 2017, to increase sensitivity and operationalize the diagnosis of PSP Richardsons syndrome (PSP-RS) and \"variant\" syndromes (vPSP).\n\nObjectivesTo determine the (1) sensitivity and specificity of the 1996 NINDS-SPSP and 2017 MDS-PSP criteria; (2) false positive rates in frontotemporal dementia with frontotemporal lobar degeneration (FTLD); and (3) clinical evolution of variant PSP syndromes (vPSP).\n\nMethodsRetrospective multicenter review of 108 neuropathologically-confirmed PSP patients and 81 patients with other forms of FTLD: 38 behavioral variant frontotemporal dementia (bvFTD), 14 non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and 29 corticobasal degeneration (CBD), Sensitivity and specificity of the MDS-PSP criteria were compared to the NINDS-SPSP criteria at baseline. In a subset of cases, the timing and frequency of clinical features were compared across groups over six years.\n\nResultsSensitivity for recognition of probable and possible PSP pathology was higher by MDS-PSP criteria (72.2-100%) than NINDS-SPSP criteria (48.1-61.1%). Specificity was higher by NINDS-SPSP criteria (97.5-100%) than MDS-PSP criteria (53.1-95.1%). False positives by MDS-PSP criteria were few for bvFTD (10.5-18.4%) but common for CBD and nfvPPA (fulfilling \"suggestive of PSP). Most vPSP cases developed PSP-RS-like features within six years, including falls and supranuclear gaze palsy, distinguishing frontal presentations of PSP from bvFTD, and speech/language presentations of PSP from nfvPPA.\n\nConclusionsThe 2017 MDS-PSP criteria successfully identify PSP, including variant phenotypes. This independent validation of the revised clinical diagnostic criteria strengthens the case for novel therapeutic strategies against PSP to include variant presentations.

neuroscience↗

bioRxiv2019

Left anterior temporal lobe is necessary for efficient lateralised processing of spoken word identity

In the healthy human brain, the processing of spoken words is strongly left-lateralised, while the processing of complex non-linguistic sounds recruits brain regions bilaterally. Here we asked whether the left anterior temporal lobe, strongly implicated in semantic processing, is critical to this special treatment of linguistic stimuli. Nine patients with semantic dementia (SD) and fourteen age-matched controls underwent magnetoencephalography and structural MRI. Voxel based morphometry demonstrated the stereotypical pattern of SD: severe grey matter loss restricted to the left anterior temporal lobe. During magnetoencephalography, participants listened to word sets in which identity and meaning were ambiguous until utterance completion, for example played vs plate. Whereas left-hemispheric responses were similar across groups, patients demonstrated increased right hemisphere activity 174-294ms after stimulus disambiguation. Source reconstructions confirmed recruitment of right-sided analogues of language regions in SD: atrophy of left anterior temporal lobe was associated with increased activity in right temporal pole, middle temporal gyrus, inferior frontal gyrus and supramarginal gyrus. Moreover only healthy controls had differential responses to words versus non-words in right auditory cortex and planum temporale. Overall, the results indicate that anterior temporal lobe is necessary for normal and efficient processing of word identity in the rest of the language network.

neuroscience↗

bioRxiv2018

In vivo assay of cortical microcircuitry in frontotemporal dementia: a platform for experimental medicine studies

The analysis of neural circuits can provide critical insights into the mechanisms of neurodegeneration and dementias, and offer potential quantitative biological tools to assess novel therapeutics. Here we use behavioural variant frontotemporal dementia (bvFTD) as a model disease. We demonstrate that inversion of canonical microcircuit models to non-invasive human magnetoecphalography can identify the regional- and laminar-specificity of bvFTD pathophysiology, and their parameters can accurately differentiate patients from matched healthy controls. Using such models, we show that changes in local coupling in frontotemporal dementia underlie the failure to adequately establish sensory predictions, leading to altered prediction error responses in a cortical information-processing hierarchy. Using machine learning, this model-based approach provided greater case-control classification accuracy than conventional evoked cortical responses. We suggest that this approach provides an in vivo platform for testing mechanistic hypotheses about disease progression and pharmacotherapeutics.

neuroscience↗

bioRxiv2018

Meta-analytic evidence for the plurality of mechanisms in transdiagnostic structural MRI studies of hallucination status

BACKGROUNDHallucinations are transmodal and transdiagnostic phenomena, occurring across sensory modalities and presenting in psychiatric, neurodegenerative, neurological, and non-clinical populations. Despite their cross-category occurrence, little empirical work has directly compared between-group neural correlates of hallucinations.\n\nMETHODSWe performed whole-brain voxelwise meta-analyses of hallucination status across diagnoses using AES-SDM, and conducted a comprehensive systematic review in PubMed and Web of Science until May 2018 on other structural correlates of hallucinations, including cortical thickness and gyrification.\n\nFINDINGS3214 abstracts were identified. Patients with psychiatric disorders and hallucinations (eight studies) exhibited reduced gray matter (GM) in the left insula, right inferior frontal gyrus, left anterior cingulate/paracingulate gyrus, left middle temporal gyrus, and increased in the bilateral fusiform gyrus, while patients with neurodegenerative disorders with hallucinations (eight studies) showed GM decreases in the left lingual gyrus, right supramarginal gyrus/parietal operculum, left parahippocampal gyrus, left fusiform gyrus, right thalamus, and right lateral occipital gyrus. Group differences between meta-analyses were formally confirmed and a jackknife sensitivity analysis established the reproducibility of results across nearly all study combinations. For other measures (28 studies), the most consistent findings associated with hallucination status were reduced cortical thickness in temporal gyri in schizophrenia and altered hippocampal volume in Parkinsons disease and dementia.\n\nINTERPRETATIONDistinct patterns of neuroanatomical alteration characterize hallucination status in patients with psychiatric and neurodegenerative diseases, suggesting a plurality of anatomical signatures. This approach has implications for treatment, theoretical frameworks, and generates refutable predictions for hallucinations in other diseases and their occurrence within the general population.\n\nFUNDINGNone.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThere is increasing recognition that hallucinations occur beyond the archetype of schizophrenia, presenting in other psychiatric disorders, neurological and neurodegenerative conditions, and among the general population. Not only are hallucinations a transdiagnostic phenomenon, but also the experience of hallucinating is phenomenologically diverse, varying in modality, content, frequency, and affect. It has been suggested that no one type of hallucination is pathognomic to any one disorder, but rather that hallucinations may exist on a continuum. However, limited research has been done to directly compare the underlying neuroanatomy of hallucinations between different disorders. With this aim, we conducted a meta-analysis and systematic review of structural MRI studies comparing individuals who experience hallucinations with those who do not, to investigate the brain morphology related to the transdiagnostic presentation of hallucinations. We searched PubMed and Web of Science with no start date limit, up to May 2018 using the keyword combination (hallucinat*) AND (MRI OR magnetic resonance imaging OR morphology OR voxel?based OR morphometr* OR neural correlate OR structur*). We included only studies with a within-group no-hallucination control to tease out structural changes specific to hallucinations from effects of the broader pathology. Neuroimaging meta-analyses were conducted on studies performing whole-brain voxelwise gray matter differences, while studies assessing other structural correlates were qualitatively synthesized.\n\nAdded value of this studyThis is the first meta-analysis to illustrate the brain structural correlates of hallucination occurrence derived from T1-weighted MRI, and to do so in a comparative manner across clinical groups. We identified two distinct gray matter substrates for hallucination presence in psychiatric compared to neurodegenerative diseases, which we hypothesise constitute at least two distinct mechanisms. In addition, we qualitatively assessed other structural neuroimaging studies over a variety of morphometric indices. We therefore provide a complete characterization of current knowledge of the brain morphology associated with hallucinations across clinical status and modality.\n\nImplications of all the available evidenceOur findings show at least two structural substrates that link to the hallucinatory experience. This informs theoretical work on hallucinations which have to date been limited in generating unifying direction-specific predictions of brain structure and function. Understanding the plurality of anatomical signatures of hallucinations may also inform treatment strategies. We predict that other disorders in which patients experience hallucinations can be categorised by our approach based on the broader phenotype; for example, hallucinations in personality disorder may be of the psychiatric type, and similarly for early onset hallucinations in the general population, whilst later onset will be neurodegenerative. Moreover, by differentiating the mechanisms of hallucinations we recommend the contextualising of research by the appropriate phenotype.

neuroscience↗

bioRxiv2018

Brain correlates of action word memory

When understanding language semantically related to actions, the motor cortex is active and may be sensitive to semantic information, for example about the body-part-relationship of displayed action-related words. Conversely, movements of the hands or feet can impair memory performance for arm- and leg-related action words respectively, suggesting that the role of motor systems extends to verbal working memory. Here, we studied brain correlates of verbal memory load for action-related words using event-related fMRI during the encoding and memory maintenance of word lists. Seventeen participants saw either four identical or four different words from the same category, semantically related to actions typically performed either with the arms or with the legs. After a variable delay of 4-14 seconds, they performed a nonmatching-to-sample task. Hemodynamic activity related to the information load of words at presentation was most prominent in left temporo-occipital and bilateral posterior-parietal areas. In contrast, larger demand on verbal memory maintenance produced greater activation in left premotor and supplementary motor cortex, along with posterior-parietal areas, indicating that verbal memory circuits for action-related words include the cortical action system. Somatotopic memory load effects of arm- and leg-related words were not present at the typical precentral loci where earlier studies had found such word-category differences in reading tasks, although traces of somatotopic semantic mappings were observed at more anterior cortical regions. These results support a neurocomputational model of distributed action-perception circuits (APCs), according to which language understanding is manifest as full ignition of APCs, whereas working memory is realized as reverberant activity gradually receding to multimodal prefrontal and lateral temporal areas.

neuroscience↗

bioRxiv2018

Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: applied to GENFI study

Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimers disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure.\n\nIn this paper we propose a spatiotemporal analysis pipeline based Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects.\n\nWe found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease.

neuroscience↗

bioRxiv2018

Motor learning decline with age is related to differences in the explicit memory system

The ability to adapt ones movements to changes in the environment is fundamental in everyday life, but this ability changes across the lifespan. Although often regarded as an implicit process, recent research has also linked motor adaptation with explicit learning processes. To understand how these processes contribute to differences in motor adaptation with age, we combined a visuomotor learning paradigm with cognitive tasks that measure implicit and explicit processes, and structural brain imaging. In a large population-based cohort from the Cambridge Centre for Ageing and Neuroscience (n=322, aged 18-89 years) we first confirmed that the degree of adaptation to an angular perturbation of visual feedback declined with age. There were no associations between adaptation and sensory attenuation, which has been previously hypothesised to contribute to implicit motor learning. However, interactions between age and scores on two independent memory tasks showed that explicit memory performance was a progressively stronger determinant of motor learning with age. Similarly, interactions between age and grey matter volume in the medial temporal lobe, amygdala and hippocampus showed that grey matter volume in these regions became a stronger determinant of adaptation in older adults. The convergent behavioural and structural imaging results suggest that age-related differences in the explicit memory system is a contributor to the decline in motor adaptation in older age. These results may reflect the more general compensatory reliance on cognitive strategies to maintain motor performance with age.\n\nSIGNIFICANCE STATEMENTThe central nervous system has a remarkable capacity to learn new motor skills and adapt to new environmental dynamics. This capacity is impaired with age, and in many brain disorders. We find that explicit memory performance and its associated medial temporal brain regions deteriorate with age, but the association between this brain system and individual differences in motor learning becomes stronger in older adults. We propose that these results reflect an increased reliance on cognition in order to maintain adaptive motor skill performance. This difference in learning strategy has implications for interventions to improve motor skills in older adults.

neuroscience↗

bioRxiv2018

Cardiovascular risk factors for micro- and macro-structural brain changes in healthy ageing

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle- and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure and heart rate) and white matter macrostructure (lesion volume and number), and microstructure (as measured by Diffusion Weighted Imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18 to 88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance. Lower diastolic blood pressure, higher systolic blood pressure and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure and heart rate affect white matter via separate mechanisms.

neuroscience↗

bioRxiv2017

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we present a new machine learning technique - Subtype and Stage Inference (SuStaIn) - able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available crosssectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal new subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes, and characterises within-group heterogeneity for the first time. In Alzheimers disease, SuStaIn uncovers three subtypes, uniquely revealing their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p=7.18x10--4) or temporal stage (p=3.96x10-5). SuStaIn thus offers new promise for enabling disease subtype discovery and precision medicine.

neuroscience↗

bioRxiv2017

Sensory attenuation is related to dopamine dose in Parkinson’s disease

Abnormal initiation and control of voluntary movements are among the principal manifestations of Parkinsons disease (PD). However, the processes underlying these abnormalities and their potential remediation by dopamine treatment remain poorly understood. Normally, movements depend on the integration of sensory information with the predicted consequences of action. This integration leads to a suppression in the intensity of predicted sensations, and increases the relative salience of unexpected stimuli to facilitate the control of movements. We examined this integration process and its relation to dopamine in PD, by measuring sensorimotor attenuation - the reduction in the perceived intensity of predicted sensations from self-generated versus external actions. Patients with idiopathic PD (n=18) and population-derived controls (n=175) matched a set of target forces applied to their left index finger by a torque motor. To match the force, participants either pressed with their right index finger ( Direct condition) or used a linear potentiometer that controlled a motor ( Slider condition). We found that despite changes in sensitivity to different forces, overall sensory attenuation did not differ between medicated PD patients and controls. Importantly, the degree of attenuation was negatively related to PD motor severity but positively related to individual patient dopamine dose, as measured by levodopa dose equivalency. The results suggest that dopamine could regulate the integration of sensorimotor prediction with sensory information to facilitate the control of voluntary movements.

neuroscience↗