Brain Imaging Biomarkers Research Articles

Brain Imaging and Blood Biomarker Abnormalities in Children With Autosomal Dominant Alzheimer Disease: A Cross-Sectional Study.

Brain imaging and fluid biomarkers are characterized in children at risk for autosomal dominant Alzheimer disease (ADAD). To characterize and compare structural magnetic resonance imaging (MRI), resting-state and task-dependent functional MRI, and plasma amyloid-β (Aβ) measurements in presenilin 1 (PSEN1) E280A mutation-carrying and noncarrying children with ADAD. Cross-sectional measures of structural and functional MRI and plasma Aβ assays were assessed in 18 PSEN1 E280A carriers and 19 noncarriers aged 9 to 17 years from a Colombian kindred with ADAD. Recruitment and data collection for this study were conducted at the University of Antioquia and the Hospital Pablo Tobon Uribe in Medellín, Colombia, between August 2011 and June 2012. All participants had blood sampling, structural MRI, and functional MRI during associative memory encoding and resting-state and cognitive assessments. Outcome measures included plasma Aβ1-42 concentrations and Aβ1-42:Aβ1-40 ratios, memory encoding-dependent activation changes, resting-state connectivity, and regional gray matter volumes. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to AD. Similar to findings in adult mutation carriers, in the later preclinical and clinical stages of ADAD, mutation-carrying children were distinguished from control individuals by significantly higher plasma Aβ1-42 levels (mean [SD]: carriers, 18.8 [5.1] pg/mL and noncarriers, 13.1 [3.2] pg/mL; P < .001) and Aβ1-42:Aβ1-40 ratios (mean [SD]: carriers, 0.32 [0.06] and noncarriers, 0.21 [0.03]; P < .001), as well as less memory encoding task-related deactivation in parietal regions (eg, mean [SD] parameter estimates for the right precuneus were -0.590 [0.50] for noncarriers and -0.087 [0.38] for carriers; P < .005 uncorrected). Unlike carriers in the later stages, mutation-carrying children demonstrated increased functional connectivity of the posterior cingulate cortex with medial temporal lobe regions (mean [SD] parameter estimates were 0.038 [0.070] for noncarriers and 0.190 [0.057] for carriers), as well as greater gray matter volumes in temporal regions (eg, left parahippocampus; P < . 049, corrected for multiple comparisons). Children at genetic risk for ADAD have functional and structural brain changes and abnormal levels of plasma Aβ1-42. The extent to which the underlying brain changes are either neurodegenerative or developmental remains to be determined. This study provides additional information about the earliest known biomarker changes associated with ADAD.

Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition.

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease.

ORBITOFRONTAL THICKNESS AS A MEASURE FOR TREATMENT RESPONSE PREDICTION IN OBSESSIVE-COMPULSIVE DISORDER.

Early prediction of treatment response could reduce exposure to ineffective treatments and optimize the use of medical resources. Neuroimaging techniques have been used to identify biomarkers that are predictive of outcomes. The aims of this study were to investigate orbitofrontal cortex (OFC) thickness as a potential morphometric biomarker to discriminate outcomes in obsessive-compulsive disorder (OCD) and then to reexamine this biomarker in an independent cohort Using a logistic regression model based on the mean baseline thickness of subregions of the OFC, we estimated the probability of treatment response in 29 treatment-naïve OCD patients who participated in a clinical trial. That algorithm was then tested in an independent cohort of 12 patients with a confirmed diagnosis of refractory OCD RESULTS: Among the treatment-naïve OCD patients, measures of OFC thickness statistically significantly differentiated responders (n = 13) and nonresponders (n = 16), with an overall classification accuracy of ≈80%, a sensitivity of 77% (10/13), and a specificity of 81% (13/16). Of the refractory OCD patients in the second independent cohort, 67% were correctly classified as nonresponders. The most discriminative measures in the initial cohort of treatment-naïve patients were the thicknesses of the left and right medial OFC (P = .009 and P = .028, respectively) We found OFC thickness to be a strong predictor of treatment response in treatment-naïve OCD patients. Although there are not yet any brain imaging biomarkers with clinical utility, our results highlight the potential of these measures as tools for predicting treatment outcomes in OCD.

Boosting Classification Accuracy of Diffusion MRI Derived Brain Networks for the Subtypes of Mild Cognitive Impairment Using Higher Order Singular Value Decomposition.

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD), and around 10-15% of people with MCI develop AD each year. More recently, MCI has been further subdivided into early and late stages, and there is interest in identifying sensitive brain imaging biomarkers that help to differentiate stages of MCI. Here, we focused on anatomical brain networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying early versus late MCI.

Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: a cross-sectional study.

Age-associated changes in brain imaging and fluid biomarkers are characterized and compared in presenilin 1 (PSEN1)E280A mutation carriers and noncarriers from the world's largest known autosomal dominant Alzheimer disease (AD) kindred. To characterize and compare age-associated changes in brain imaging and fluid biomarkers in PSEN1 E280A mutation carriers and noncarriers. Cross-sectional measures of 18F-florbetapir positron emission tomography, 18F-fludeoxyglucose positron emission tomography, structural magnetic resonance imaging, cerebrospinal fluid (CSF), and plasma biomarkers of AD were assessed from 54 PSEN1 E280A kindred members (age range, 20-59 years). We used brain mapping algorithms to compare regional cerebral metabolic rates for glucose and gray matter volumes in cognitively unimpaired mutation carriers and noncarriers. We used regression analyses to characterize associations between age and the mean cortical to pontine 18F-florbetapir standard uptake value ratios, precuneus cerebral metabolic rates for glucose, hippocampal gray matter volume, CSF Aβ1-42, total tau and phosphorylated tau181, and plasma Aβ measurements. Age at onset of progressive biomarker changes that distinguish carriers from noncarriers was estimated using best-fitting regression models. Compared with noncarriers, cognitively unimpaired mutation carriers had significantly lower precuneus cerebral metabolic rates for glucose, smaller hippocampal volume, lower CSF Aβ1-42, higher CSF total tau and phosphorylated tau181, and higher plasma Aβ1-42 measurements. Sequential changes in biomarkers were seen at age 20 years (95% CI, 14-24 years) for CSF Aβ1-42, age 16 years (95% CI, 11-24 years) for the mean cortical 18F-florbetapir standard uptake value ratio, age 15 years (95% CI, 10-24 years) for precuneus cerebral metabolic rate for glucose, age 15 years (95% CI, 7-20 years) for CSF total tau, age 13 years (95% CI, 8-19 years) for phosphorylated tau181, and age 6 years (95% CI, 1-10 years) for hippocampal volume, with cognitive decline up to 6 years before the kindred's estimated median age of 44 years (95% CI, 43-45 years) at mild cognitive impairment diagnosis. No age-associated findings were seen in plasma Aβ1-42 or Aβ1-40. This cross-sectional study provides additional information about the course of different AD biomarkers in the preclinical and clinical stages of autosomal dominant AD.

Regional vulnerability of longitudinal cortical association connectivity: Associated with structural network topology alterations in preterm children with cerebral palsy.

Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior–anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior–anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal–thalamic–striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with alteration in eigenvector centrality, clustering coefficient (inter-regional) and participation co-efficient (inter-modular) alterations of frontal–striatal and fronto-limbic nodes suggesting re-organization of these pathways. Both along tract and structural topology network measurements correlated strongly with motor and visual clinical outcome scores. This study shows the value of combining along-tract analysis and structural network topology in depicting not only selective parietal occipital regional vulnerability but also reorganization of frontal–striatal and frontal–limbic pathways in preterm children with cerebral palsy. These finding also support the concept that widespread, but selective posterior–anterior neural network connectivity alterations in preterm children with cerebral palsy likely contribute to the pathogenesis of neurosensory and cognitive impairment in this group.

Prediction of Alzheimer's dementia

The prediction of Alzheimer's dementia is relevant for the development and design of prevention trials but also for individual counselling of patients. There are two key characteristics which determine the level of prediction that can be achieved. Firstly, the prevalence of Alzheimer's dementia in the respective setting is important. In low prevalence settings, such as primary care populations, it is probably impossible to achieve positive predictive values above 50%. In high prevalence settings, such as memory clinics, the positive predictive value of Alzheimer's dementia can be much higher. The second major characteristic is the level of cognitive impairment of an individual. The predictive power for Alzheimer's dementia increases from the cognitively healthy status to the status of progressive mild cognitive impairment. Prediction can further be increased by the use of cerebral spinal fluid and brain imaging biomarkers of Alzheimer's disease. The combination of different biomarkers may increase prediction even further. The present article reviews studies and outlines the principles of prediction of Alzheimer's dementia.

Bipolar and Schizophrenia Network for Intermediate Phenotypes: Outcomes Across the Psychosis Continuum

Bipolar and schizophrenia network for intermediate phenotypes is a network of investigator-driven laboratories focused on developing phenotypes, genotypes, and biomarkers for psychosis. Over the last 5 years, the consortium has accomplished a dense phenotyping protocol using probands with a lifetime history of psychosis, their relatives, and healthy controls. This has established a library of biomarker information on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis. The founding goal of establishing disease biomarkers for current psychotic diagnoses has been poorly met, because the cognitive, electrophysiologic, eye movement, and brain imaging biomarkers did not regularly discriminate individuals with different DSM psychosis diagnoses. In future, we will use this biomarker information to establish a pathway to biomarker-based classification in psychoses.

Biomarcadores en la enfermedad de Alzheimer

The new diagnostic criteria for Alzheimer's disease (AD) include brain imaging and cerebrospinal fluid (CSF) biomarkers, with the aim of increasing the certainty of whether a patient has an ongoing AD neuropathologic process or not. Three CSF biomarkers, Aß42, total tau, and phosphorylated tau, reflect the core pathological features of AD. It is already known that these pathological processes of AD starts decades before the first symptoms, so these biomarkers may provide means of early disease detection. At least three stages of AD could be identified: preclinical AD, mild cognitive impairment due to AD, and dementia due to AD. In this review, we aim to summarize the CSF biomarker data available for each of these stages. We also review the actual research on blood-based biomarkers. Recent studies on healthy elderly subjects and on carriers of dominantly inherited AD mutations have also found biomarker changes that allow separate groups in these preclinical stages. These studies may aid for segregate populations in clinical trials and objectively evaluate if there are changes over the pathological processes of AD. Limits to widespread use of CSF biomarkers, apart from the invasive nature of the process itself, is the higher coefficient of variation for the analyses between centres. It requires strict pre-analytical and analytical procedures that may make feasible multi-centre studies and global cut-off points for the different stages of AD.

Hemorrhagic Transformation after Ischemic Stroke in Animals and Humans

Hemorrhagic transformation (HT) is a common complication of ischemic stroke that is exacerbated by thrombolytic therapy. Methods to better prevent, predict, and treat HT are needed. In this review, we summarize studies of HT in both animals and humans. We propose that early HT (<18 to 24 hours after stroke onset) relates to leukocyte-derived matrix metalloproteinase-9 (MMP-9) and brain-derived MMP-2 that damage the neurovascular unit and promote blood-brain barrier (BBB) disruption. This contrasts to delayed HT (>18 to 24 hours after stroke) that relates to ischemia activation of brain proteases (MMP-2, MMP-3, MMP-9, and endogenous tissue plasminogen activator), neuroinflammation, and factors that promote vascular remodeling (vascular endothelial growth factor and high-moblity-group-box-1). Processes that mediate BBB repair and reduce HT risk are discussed, including transforming growth factor beta signaling in monocytes, Src kinase signaling, MMP inhibitors, and inhibitors of reactive oxygen species. Finally, clinical features associated with HT in patients with stroke are reviewed, including approaches to predict HT by clinical factors, brain imaging, and blood biomarkers. Though remarkable advances in our understanding of HT have been made, additional efforts are needed to translate these discoveries to the clinic and reduce the impact of HT on patients with ischemic stroke.

Biomarkers of Alzheimer's disease: The present and the future

A paradigm shift has occurred in the last ten years in the diagnostic field of Alzheimer's disease (AD). Scientific thought has enriched the concept of AD as a pathophysiological continuum and emphasized contribution of biological, morphological and functional brain imaging biomarkers for diagnosis, in particular during the early stages of the disease. We address here the present and the future of these biological biomarkers. Most of them are linked to the pathophysiological lesions of the Alzheimer process: aggregates of hyperphosphorylated tau proteins, also called neurofibrillary tangles (NFT), and extracellular deposit of amyloid-beta peptides (Aβ), also called senile plaques. The detection in the cerebrospinal fluid (CSF) of tau and Aβ represents the current diagnostic practice of AD. Improvement for a more accurate and earlier biological diagnosis is however expected using a new generation of biomarkers, mostly in relation with tau and Aβ metabolism.

Retinal periphlebitis is associated with multiple sclerosis severity

To assess the association of primary retinal inflammation, namely retinal periphlebitis (RP) and microcystic macular edema, with clinical, brain, and retinal imaging biomarkers of multiple sclerosis (MS) severity. One hundred patients with MS underwent a neurologic and ophthalmic examination, MRI, and optical coherence tomography. Disability was assessed using the Expanded Disability Status Scale at baseline and after a 1-year follow-up. The normalized brain volume, the normal-appearing gray matter volume, and T1 lesion volume were assessed at baseline as radiologic biomarkers of disease severity. Retinal nerve fiber layer thickness and macular volume at baseline were used as surrogate markers of axonal damage. We used general linear models adjusted for sex, age, disease duration, and MS treatment to compared adjusted means of these parameters among patients with RP and patients without primary retinal inflammation. Five patients showed RP, 2 showed microcystic macular edema, and the retina was normal in the remaining 93. Patients with RP had a tendency toward a higher adjusted-mean Expanded Disability Status Scale score at baseline and disability progression after a 1-year follow-up compared with patients without primary retinal inflammation. These patients also had a higher adjusted-mean T1 lesion volume (adjusted differences: 10.4, 95% confidence interval [CI]: 0.6 to 20.2; p = 0.038) and lower T1 brain volume (adjusted differences: -68, 95% CI: -139 to 2; p = 0.059). Patients with RP had a lower adjusted-mean retinal nerve fiber layer thickness (adjusted differences: -13.4, 95% CI: -24.4 to -2.3; p = 0.018) and a trend toward lower macular volume. These results support the role of RP as a biomarker of MS severity.

Estimated maximal and current brain volume predict cognitive ability in old age

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging.

Brain Imaging Biomarkers to Predict Relapse in Alcohol Addiction

The finding that various regions were associated with relapse and craving is consistent with the organization of the brain into functional networks comprising complex connections among multiple regions. It is notable that the regions with the strongest prediction for relapse (vmPFC/ACC and precuneus) are central nodes of the default mode network (DMN), which is involved with the processing of internal states (including selfmonitoring) and deactivated when engaging in various behavioral tasks or when responding to the environment 9 (Figure). Also, the ventral striatum, which is one of the main targets for

Ushering in the study and treatment of preclinical Alzheimer disease

Researchers have begun to characterize the subtle biological and cognitive processes that precede the clinical onset of Alzheimer disease (AD), and to set the stage for accelerated evaluation of experimental treatments to delay the onset, reduce the risk of, or completely prevent clinical decline. In this Review, we provide an overview of the experimental strategies, and brain imaging and cerebrospinal fluid biomarker measures that are used in early detection and tracking of AD, highlighting at-risk individuals who could be suitable for preclinical monitoring. We discuss how advances in the field have contributed to reconceptualization of AD as a sequence of biological changes that occur during progression from preclinical AD, to mild cognitive impairment and finally dementia, and we review recently proposed research criteria for preclinical AD. Advances in the study of preclinical AD have driven the recognition that efficacy of at least some AD therapies may depend on initiation of treatment before clinical manifestation of disease, leading to a new era of AD prevention research.

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders.

Fluid biomarkers in Alzheimer’s disease – current concepts

The diagnostic guidelines of Alzheimer’s disease (AD) have recently been updated to include brain imaging and cerebrospinal fluid (CSF) biomarkers, with the aim of increasing the certainty of whether a patient has an ongoing AD neuropathologic process or not. The CSF biomarkers total tau (T-tau), hyperphosphorylated tau (P-tau) and the 42 amino acid isoform of amyloid β (Aβ42) reflect the core pathologic features of AD, which are neuronal loss, intracellular neurofibrillary tangles and extracellular senile plaques. Since the pathologic processes of AD start decades before the first symptoms, these biomarkers may provide means of early disease detection. The updated guidelines identify three different stages of AD: preclinical AD, mild cognitive impairment (MCI) due to AD and AD with dementia. In this review, we aim to summarize the CSF biomarker data available for each of these stages. We also review results from blood biomarker studies. In summary, the core AD CSF biomarkers have high diagnostic accuracy both for AD with dementia and to predict incipient AD (MCI due to AD). Longitudinal studies on healthy elderly and recent cross-sectional studies on patients with dominantly inherited AD mutations have also found biomarker changes in cognitively normal at-risk individuals. This will be important if disease-modifying treatment becomes available, given that treatment will probably be most effective early in the disease. An important prerequisite for this is trustworthy analyses. Since measurements vary between studies and laboratories, standardization of analytical as well as pre-analytical procedures will be essential. This process is already initiated. Apart from filling diagnostic roles, biomarkers may also be utilized for prognosis, disease progression, development of new treatments, monitoring treatment effects and for increasing the knowledge about pathologic processes coupled to the disease. Hence, the search for new biomarkers continues. Several candidate biomarkers have been found in CSF, and although biomarkers in blood have been harder to find, some recent studies have presented encouraging results. But before drawing any major conclusions, these results need to be verified in independent studies.

Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: a case-control study

We have previously characterised functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer's disease. To gain further knowledge on the preclinical phase of Alzheimer's disease, we sought to characterise structural and functional MRI, CSF, and plasma biomarkers in a cohort of young adults carrying a high-penetrance autosomal dominant mutation that causes early-onset Alzheimer's disease. Between January and August, 2010, 18-26-year-old presenilin 1 (PSEN1) E280A mutation carriers and non-carriers from the Colombian Alzheimer's Prevention Initiative Registry in Medellín Antioquia, Colombia, had structural MRI, functional MRI during associative memory encoding and novel viewing and control tasks, and cognitive assessments. Consenting participants also had lumbar punctures and venepunctures. Outcome measures were task-dependent hippocampal or parahippocampal activations and precuneus or posterior cingulate deactivations, regional grey matter reductions, CSF Aβ(1-42), total tau and phospho-tau(181) concentrations, and plasma Aβ(1-42) concentrations and Aβ(1-42):Aβ(1-40) ratios. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to Alzheimer's disease. Cognitive and fluid biomarkers were compared using Mann-Whitney tests. 44 participants were included: 20 PSEN1 E280A mutation carriers and 24 non-carriers. The carrier and non-carrier groups did not differ significantly in their dementia ratings, neuropsychological test scores, or proportion of apolipoprotein E (APOE) ɛ4 carriers. Compared with non-carriers, carriers had greater right hippocampal and parahippocampal activation (p=0·001 and p<0·014, respectively, after correction for multiple comparisons), less precuneus and posterior cingulate deactivation (all p<0·010 after correction), and less grey matter in several parietal regions (all p<0·002 uncorrected and corrected p=0·009 in the right parietal search region). In the 20 participants (ten PSEN1 E280A mutation carriers and ten non-carriers) who had lumbar punctures and venepunctures, mutation carriers had higher CSF Aβ(1-42) concentrations (p=0·008) and plasma Aβ(1-42) concentrations (p=0·01) than non-carriers. Young adults at genetic risk for autosomal dominant Alzheimer's disease have functional and structural MRI findings and CSF and plasma biomarker findings consistent with Aβ(1-42) overproduction. Although the extent to which the underlying brain changes are either neurodegenerative or developmental remain to be determined, this study shows the earliest known biomarker changes in cognitively normal people at genetic risk for autosomal dominant Alzheimer's disease. Banner Alzheimer's Foundation, Nomis Foundation, Anonymous Foundation, Forget Me Not Initiative, Boston University Department of Psychology, Colciencias, National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the State of Arizona.

Genome Sequencing Set to Hunt for Alzheimer's Clues

T he largest genome-sequencing project ever is the newest weapon against Alzheimer’s. The project will examine the genetic codes of more than 800 people, generating more than 165 terabytes – 165,000 gigabytes – of new information about Alzheimer’s disease and its genetic roots. “This is the biggest single whole-genome scan that has ever been done in any disease, and in one of the best-characterized research cohorts ever seen,” said William Thies, PhD. “We are bound to discover new things.” Improvements in both technology and cost make the project feasible for the fi rst time. The genome sequencing will take about 16 weeks from start to fi nish, said Dr. Thies, chief medical and scientifi c offi cer of the Alzheimer’s Association. The project’s price tag is $2 million ($1 million each from the Alzheimer’s Association and the nonprofi t Brin Wojcicki Foundation). The project is an off shoot of the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Dr. Thies said in an interview. ADNI is a global eff ort to improve ways of identifying the best patients for clinical trials by using brain imaging and other biomarkers. The North American section of ADNI has a pool of 800 patients who have been followed since 2004. The cohort “has been characterized to an extent that is almost unheard of in genetic studies,” Dr. Thies said. Upon enrollment, subjects are stratifi ed as having normal cognition, mild cognitive impairment, or Alzheimer’s disease. Close follow-up allows researchers to identifying cognitive and physiological changes as they occur, as well as risk factors that predispose people to disease. Three genetic markers for familial (or early-onset) Alzheimer’s have been discovered so far: mutations in the genes for presenilin-1 and -2 and the amyloid precursor protein. The e4 allele of the gene for apolipoprotein E is known to have the greatest impact on risk for sporadic (or late-onset) Alzheimer’s. With genomic sequencing of the ADNI cohort,“I’m absolutely certain we will learn much more about how to diagnose and treat the disease,” Dr. Thies said. Like all of ADNI’s data, the genomic information will be publicly available to researchers all over the world. “More papers have been published outside of ADNI than by researchers in the group. That is really impressive. Sharing is clearly the road to progress.” How any new genetic information might be used is still an unknown, Dr. Thies said, but it’s likely to advance every aspect of Alzheimer’s care, from risk assessment to diagnosis to treatment. These kinds of data off er the possibility of being able to test people early in life and establish their risk of developing Alzheimer’s. “Having that information is going to very rapidly put us into the world of risk stratifi cation, so that we can optimally manage any interventions we develop.” Genetic information will also inform the search for preventive therapies, he said. “This will point us to new pathways in the disease process. Once those are identifi ed, we can try to fi nd early interventions that might help reduce the risk of getting Alzheimer’s.” Dr. Thies foreshadowed some expected results: “We are seeing risk genes beginning to clump around a number of areas, including those that have to do with amyloid, infl ammation, vascular areas, and lipid metabolism. ... These genes may end up showing just a modest eff ect on risk, but could still open the door to early intervention. If you can identify and treat someone for 20 years, a small but consistent eff ect may be enough to prevent Alzheimer’s from developing.” Dr. Robert Green of Brigham and Women’s Hospital and Harvard Medical School, both in Boston, will lead ADNI. The project is funded by a number of bodies, including the National Institute on Aging and the National Institute of Biomedical Imaging and Bioengineering, pharmaceutical companies, and nonprofi t groups. CfA

Brain Resuscitation in the Drowning Victim

Drowning is a leading cause of accidental death. Survivors may sustain severe neurologic morbidity. There is negligible research specific to brain injury in drowning making current clinical management non-specific to this disorder. This review represents an evidence-based consensus effort to provide recommendations for management and investigation of the drowning victim. Epidemiology, brain-oriented prehospital and intensive care, therapeutic hypothermia, neuroimaging/monitoring, biomarkers, and neuroresuscitative pharmacology are addressed. When cardiac arrest is present, chest compressions with rescue breathing are recommended due to the asphyxial insult. In the comatose patient with restoration of spontaneous circulation, hypoxemia and hyperoxemia should be avoided, hyperthermia treated, and induced hypothermia (32-34 °C) considered. Arterial hypotension/hypertension should be recognized and treated. Prevent hypoglycemia and treat hyperglycemia. Treat clinical seizures and consider treating non-convulsive status epilepticus. Serial neurologic examinations should be provided. Brain imaging and serial biomarker measurement may aid prognostication. Continuous electroencephalography and N20 somatosensory evoked potential monitoring may be considered. Serial biomarker measurement (e.g., neuron specific enolase) may aid prognostication. There is insufficient evidence to recommend use of any specific brain-oriented neuroresuscitative pharmacologic therapy other than that required to restore and maintain normal physiology. Following initial stabilization, victims should be transferred to centers with expertise in age-specific post-resuscitation neurocritical care. Care should be documented, reviewed, and quality improvement assessment performed. Preclinical research should focus on models of asphyxial cardiac arrest. Clinical research should focus on improved cardiopulmonary resuscitation, re-oxygenation/reperfusion strategies, therapeutic hypothermia, neuroprotection, neurorehabilitation, and consideration of drowning in advances made in treatment of other central nervous system disorders.