The clinical utility of the Cornell Scale for Depression in Dementia as a routine assessment in nursing homes

Objective To examine the clinical utility of the Cornell Scale for Depression in Dementia (CSDD) in nursing homes. Setting 14 nursing homes in Sydney and Brisbane, Australia. Participants 92 residents with a mean age of 85 years. Measurements Consenting residents were assessed by care staff for depression using the CSDD as part of their routine assessment. Specialist clinicians conducted assessment of depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders for residents without dementia or the Provisional Diagnostic Criteria for Depression in Alzheimer Disease for residents with dementia to establish expert clinical diagnoses of depression. The diagnostic performance of the staff completed CSDD was analyzed against expert diagnosis using receiver operating characteristic (ROC) curves. Results The CSDD showed low diagnostic accuracy, with areas under the ROC curve being 0.69, 0.68 and 0.70 for the total sample, residents with dementia and residents without dementia, respectively. At the standard CSDD cutoff score, the sensitivity and specificity were 71% and 59% for the total sample, 69% and 57% for residents with dementia, and 75% and 61% for residents without dementia. The Youden index (for optimizing cut-points) suggested different depression cutoff scores for residents with and without dementia. Conclusion When administered by nursing home staff the clinical utility of the CSDD is highly questionable in identifying depression. The complexity of the scale, the time required for collecting relevant information, and staff skills and knowledge of assessing depression in older people must be considered when using the CSDD in nursing homes.

Can we do better? Researchers' experiences with ethical review boards on projects with later life as a focus

The goal of this study was to describe researchers' experiences in submitting ethical proposals focused on older adult populations, including studies with persons with dementia, to ethical review boards. Ethical approval was granted for an online survey. Researchers were recruited via listservs and snowballing techniques. Participants included 157 persons (73% female) from Australia and the United States, with a mean age of 46 (±13). Six main issues were encountered by researchers who participated in this survey. In descending order, these included questions regarding: informed consent and information requirements (61.1%), participants' vulnerability, particularly for those with cognitive impairments (58.6%), participant burden (44.6%), data access (29.3%), adverse effects of data collection/intervention (26.8%), and study methodology (25.5%). An inductive content analysis of responses revealed a range of encounters with ethical review panels spanning positive, negative, and neutral experiences. Concerns voiced about ethical review boards included committees being overly focused on legal risk, as well as not always hearing the voice of older research participants, both potential and actual. Respondents noted inability to move forward on studies, as well as loss of researchers and participant groups from gerontological and clinical research as a result of negative interactions with ethics committees. Positive interactions with the committees reinforced researchers' need to carefully construct their research approaches with persons with dementia in particular. Suggested guidelines for committees when dealing with ethics applications involving older adults include self-reflecting on potential biases and stereotypes, and seeking further clarification and information from gerontological researchers before arriving at decisions.

Global, regional, and national age–sex specifi c all-cause and cause-specifi c mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0–65·6) in 1990, to 71·5 years (UI 71·0–71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8–48·2) to 54·9 million (UI 53·6–56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25–39 years and older than 75 years and for men aged 20–49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.

Validity of the geriatric depression scale and the collateral source version of the geriatric depression scale in nursing homes

Background Depression is a common psychiatric disorder in older people. The study aimed to examine the screening accuracy of the Geriatric Depression Scale (GDS) and the Collateral Source version of the Geriatric Depression Scale (CS-GDS) in the nursing home setting. Methods Eighty-eight residents from 14 nursing homes were assessed for depression using the GDS and the CS-GDS, and validated against clinician diagnosed depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID) for residents without dementia and the Provisional Diagnostic Criteria for Depression in Alzheimer Disease (PDCdAD) for those with dementia. The screening performances of five versions of the GDS (30-, 15-, 10-, 8-, and 4-item) and two versions of the CS-GDS (30- and 15-item) were analyzed using receiver operating characteristic (ROC) curves. Results Among residents without dementia, both the self-rated (AUC = 0.75–0.79) and proxy-rated (AUC = 0.67) GDS variations performed significantly better than chance in screening for depression. However, neither instrument adequately identified depression among residents with dementia (AUC between 0.57 and 0.70). Among the GDS variations, the 4- and 8-item scales had the highest AUC and the optimal cut-offs were >0 and >3, respectively. Conclusions The validity of the GDS in detecting depression requires a certain level of cognitive functioning. While the CS-GDS is designed to remedy this issue by using an informant, it did not have adequate validity in detecting depression among residents with dementia. Further research is needed on informant selection and other factors that can potentially influence the validity of proxy-based measures in the nursing home setting.

Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects

Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson's disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 706) and the Queensland Twin Imaging Study (QTIM; N = 639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (PMA = 4. 79 × 10-8). This commonly-carried genetic variant accounted for 2. 68 % and 0. 84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster's involvement in lentiform nucleus volume differences in human populations.

Discovery of genes that affect human brain connectivity: A genome-wide analysis of the connectome

Human brain connectivity is disrupted in a wide range of disorders from Alzheimer's disease to autism but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1-58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration. © 2012 IEEE.

Genetics of path lengths in brain connectivity networks: HARDI-based maps in 457 adults

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, highangular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Discovery and replication of gene influences on brain structure using LASSO regression

We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4, and CDH13. The top genes we identified with this method also displayed significant and widespread post hoc effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2.We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8±2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment

Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital-parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson's correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer's disease.

A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: Replication in elderly and young populations

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

Direct mapping of hippocampal surfaces with intrinsic shape context

We propose in this paper a new method for the mapping of hippocampal (HC) surfaces to establish correspondences between points on HC surfaces and enable localized HC shape analysis. A novel geometric feature, the intrinsic shape context, is defined to capture the global characteristics of the HC shapes. Based on this intrinsic feature, an automatic algorithm is developed to detect a set of landmark curves that are stable across population. The direct map between a source and target HC surface is then solved as the minimizer of a harmonic energy function defined on the source surface with landmark constraints. For numerical solutions, we compute the map with the approach of solving partial differential equations on implicit surfaces. The direct mapping method has the following properties: (1) it has the advantage of being automatic; (2) it is invariant to the pose of HC shapes. In our experiments, we apply the direct mapping method to study temporal changes of HC asymmetry in Alzheimer's disease (AD) using HC surfaces from 12 AD patients and 14 normal controls. Our results show that the AD group has a different trend in temporal changes of HC asymmetry than the group of normal controls. We also demonstrate the flexibility of the direct mapping method by applying it to construct spherical maps of HC surfaces. Spherical harmonics (SPHARM) analysis is then applied and it confirms our results on temporal changes of HC asymmetry in AD.

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N1198) using genome-wide search

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.