Subtypes of Illicit Drug Users: A Latent Class Analysis of Data From an Australian Twin Sample

This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.

Phylogenetic analysis to define feline immunodeficiency virus subtypes in 31 domestic cats in South Africa

Feline immunodeficiency virus (FIV), a lentivirus, is an important pathogen of domestic cats around the world and has many similarities to human immunodeficiency virus (HIV). A characteristic of these lentiviruses is their extensive genetic diversity which has been an obstacle in the development of successful vaccines. Of the FIV genes, the envelope gene is the most variable and sequence differences in a portion of this gene have been used to define 5 FIV subtypes (A, B, C, D and E). In this study, the proviral DNA sequence of the V3-V5 region of the envelope gene was determined in blood samples from 31 FIV positive cats from 4 different regions of South Africa. Phylogenetic analysis demonstrated the presence of both subtypes A and C, with subtype A predominating. These findings contribute to the understanding of the genetic diversity of FIV

Binding and hydrodynamic properties of muscarinic receptor subtypes solubilized in 3-(3-cholamidopropyl)dimethylammonio-2-hydroxy-1-propanesulfonate

The muscarinic receptor from the cerebral cortex, heart, and lacrimal gland can be solubilized in the zwitterionic detergent 3-(3-cholamidopropyl)dimethylammonio-2-hydroxy-1-propane sulfonate (CHAPSO) with retention of high affinity [3H]N-methyls-copolamine binding. However, in this detergent there are significant differences in the binding properties of the receptors, compared with those observed in membranes and digitonin solution. Some agents retain a degree of selectivity. In the heart and cortex, agonists can bind with high affinity to a receptor-GTP-binding protein complex. A second, lower affinity, agonist binding state is also present, which resembles a class of sites seen in membranes but not in digitonin solution. The high affinity agonist binding state has been resolved from the lower affinity state on sucrose density gradient centrifugation. Hydrodynamic analysis suggests that the high affinity state is approximately 110,000 Da larger than the lower affinity state. The binding properties of the receptor in CHAPSO can be altered to those seen in digitonin by exchanging detergents after CHAPSO solubilization.

Quantitative microscopic analysis of histological sections of brain tissue

This article reviews methods for quantifying the abundance of histological features in thin tissue sections of brain such as neurons, glia, blood vessels, and pathological lesions. The sampling methods by which quantitative measures can be obtained are described. In addition, methods are described for determining the spatial pattern of an object and for measuring the degree of spatial correlation between two or more histological features.

Quantitative differences in beta/A4 protein subtypes in the parahippocampal gyrus and frontal cortex in Alzheimer's disease

The density of diffuse, primitive and classic beta/A4 protein deposits was estimated in sulci and gyri in the frontal cortex and parahippocampal gyrus (PHG) in 8 cases of Alzheimer's disease. Total beta/A4 deposit density was similar in the frontal cortex and PHG but the ratio of primitive and classic deposits to the total was greater in the PHG compared with the frontal cortex. Total beta/A4 deposit density was greater in the depths of the sulci, but the proportions of the various beta/A4 subtypes were similar in sulci and gyri. Hence, increased density of primitive and classic deposits in the PHG could reflect enhanced conversion of diffuse to mature deposits whereas increased density of mature beta/A4 subtypes in sulci versus gyri may reflect increased beta/A4 deposition in the sulci.

The identification of pathological subtypes of Alzheimer's disease using cluster analysis

A culster analysis was performed on 78 cases of Alzheimer's disease (AD) to identify possible pathological subtypes of the disease. Data on 47 neuropathological variables, inculding features of the gross brain and the density and distribution of senile plaques (SP) and neurofibrillary tangles (NFT) were used to describe each case. Cluster analysis is a multivariate statistical method which combines together in groups, AD cases with the most similar neuropathological characteristics. The majority of cases (83%) were clustered into five such groups. The analysis suggested that an initial division of the 78 cases could be made into two major groups: (1) a large group (68%) in which the distribution of SP and NFT was restricted to a relatively small number of brain regions, and (2) a smaller group (15%) in which the lesions were more widely disseminated throughout the neocortex. Each of these groups could be subdivided on the degree of capillary amyloid angiopathy (CAA) present. In addition, those cases with a restricted development of SP/NFT and CAA could be divided further into an early and a late onset form. Familial AD cases did not cluster as a separate group but were either distributed between four of the five groups or were cases with unique combinations of pathological features not closely related to any of the groups. It was concluded that multivariate statistical methods may be of value in the classification of AD into subtypes. © 1994 Springer-Verlag.

Measuring the spatial arrangement patterns of pathological lesions in histological sections of brain tissue

The development of abnormal protein aggregates in the form of extracellular plaques and intracellular inclusions is a characteristic feature of many neurodegenerative diseases such as Alzheimer's disease (AD), Creutzfeldt-Jakob disease (CJD) and the fronto-temporal dementias (FTD). An important aspect of a pathological protein aggregate is its spatial topography in the tissue. Lesions may not be randomly distributed within a histological section but exhibit spatial pattern, a departure from randomness either towards regularity or clustering. Information on the spatial pattern of a lesion may be useful in elucidating its pathogenesis and in studying the relationships between different lesions. This article reviews the methods that have been used to study the spatial topography of lesions. These include simple tests of whether the distribution of a lesion departs significantly from random using randomized points or sample fields, and more complex methods that employ grids or transects of contiguous fields and which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters. The usefulness of these methods in elucidating the pathogenesis of protein aggregates in neurodegenerative disease is discussed.

Methods of studying the planar distribution of objects in histological sections of brain tissue

This article reviews the statistical methods that have been used to study the planar distribution, and especially clustering, of objects in histological sections of brain tissue. The objective of these studies is usually quantitative description, comparison between patients or correlation between histological features. Objects of interest such as neurones, glial cells, blood vessels or pathological features such as protein deposits appear as sectional profiles in a two-dimensional section. These objects may not be randomly distributed within the section but exhibit a spatial pattern, a departure from randomness either towards regularity or clustering. The methods described include simple tests of whether the planar distribution of a histological feature departs significantly from randomness using randomized points, lines or sample fields and more complex methods that employ grids or transects of contiguous fields, and which can detect the intensity of aggregation and the sizes, distribution and spacing of clusters. The usefulness of these methods in understanding the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Creutzfeldt-Jakob disease is discussed. © 2006 The Royal Microscopical Society.

Measuring the degree of spatial correlation between histological features in thin sections of brain tissue

Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using χ2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

Analysis of spatial patterns in histological sections of brain tissue using a method based on regression

A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.

Analysis of spatial patterns in histological sections of brain tissue

A method is described which enables the spatial pattern of discrete objects in histological sections of brain tissue to be determined. The method can be applied to cell bodies, sections of blood vessels or the characteristic lesions which develop in the brain of patients with neurodegenerative disorders. The density of the histological feature under study is measured in a series of contiguous sample fields arranged in a grid or transect. Data from adjacent sample fields are added together to provide density data for larger field sizes. A plot of the variance/mean ratio (V/M) of the data versus field size reveals whether the objects are distributed randomly, uniformly or in clusters. If the objects are clustered, the analysis determines whether the clusters are randomly or regularly distributed and the mean size of the clusters. In addition, if two different histological features are clustered, the analysis can determine whether their clusters are in phase, out of phase or unrelated to each other. To illustrate the method, the spatial patterns of senile plaques and neurofibrillary tangles were studied in histological sections of brain tissue from patients with Alzheimer's disease.

The use of multivariate methods in the identification of subtypes of Alzheimer's disease: a comparison of principal components and cluster analysis

Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer's disease (AD). To compare the two methods, 78 cases of AD were analyzed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.

Analysis of population dispersion in histological sections

Stereology and other image analysis methods have enabled rapid and objective quantitative measurements to be made on histological sections. These mesurements may include total volumes, surfaces, lengths and numbers of cells and blood vessels or pathological lesions. Histological features, however, may not be randomly distributed across a section but exhibit 'dispersion', a departure from randomness either towards regularity or aggregation. Information of population dispersion may be valuable not only in understanding the two-or three-dimensional structure but also in elucidating the pathogenesis of lesions in pathological conditions. This article reviews some of the statistical methods available for studying dispersion. These range from simple tests of whether the distribution of a histological faeture departs significantly from random to more complex methods which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters.

A comparison of histological and immunohistochemical methods for quantifying the pathological lesions of Pick's disease

Counts of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were made in the frontal and temporal cortex from patients with Pick's disease (PD). Lesions were stained histologically with hematoxylin and eosin (HE) and the Bielschowsky silver impregnation method and labeled immunohistochemically with antibodies raised to ubiquitin and tau. The greatest numbers of PB were revealed by immunohistochemistry. Counts of PB revealed by ubiquitin and tau were highly positively correlated which suggested that the two antibodies recognized virtually identical populations of PB. The greatest numbers of PC were revealed by HE followed by the anti-ubiquitin antibody. However, the correlation between counts was poor, suggesting that HE and ubiquitin revealed different populations of PC. The greatest numbers of SP and NFT were revealed by the Bielschowsky method indicating the presence of Alzheimer-type lesions not revealed by the immunohistochemistry. In addition, more NFT were revealed by the anti-ubiquitin compared with the anti-tau antibody. The data suggested that in PD: (i) the anti-ubiquitin and anti-tau antibodies were equally effective at labeling PB; (ii) both HE and anti-ubiquitin should be used to quantitate PC; and (iii) the Bielschowsky method should be used to quantitate SP and NFT.