Brain Aging

Models, Methods, and Mechanisms

David R. Riddle

• Publisher: CRC Press
• Year: 2007
• Print ISBN: 9780849338182
• eBook ISBN: 9781000611557
• Topic: Medicine
• Subtopic: Anatomy

Recognition that aging is not the accumulation of disease, but rather comprises fundamental biological processes that are amenable to experimental study, is the basis for the recent growth of experimental biogerontology. As increasingly sophisticated studies provide greater understanding of what occurs in the aging brain and how these changes occur

Section II

Quantifying Aging-Related Changes in the Brain

4	Design-Based Stereology in Brain Aging Research Christoph Schmitz and Patrick R. Hof

CONTENTS

I.	Introduction
II.	Recent Progress in Brain Aging Research with Design-Based Stereology A. Design-Based Stereologic Analyses of the Aging Human Brain B. Design-Based Stereologic Analyses of the Brain of Nonhuman Primates and Rodents C. Design-Based Stereologic Analyses of the Brain in Alzheimer’s Disease
III.	Design-Based Stereologic Methods for Brain Aging Research A. How to Obtain Rigorous Results in Brain Aging Research with Design-Based Stereology B. Defining the Borders of a Brain Region C. Estimating the Volume of a Brain Region D. Determining the Number of Cells within a Given Tissue Volume E. Determining the Total Number of Neurons within a Given Brain Region F. Estimating Mean Cellular/Nuclear Size G. Estimating Total Lengths and Length Densities of Capillaries and Fibers H. Quantitative Analysis of the Three-Dimensional Cytoarchitecture of a Given Brain Region I. Equipment Required for Design-Based Stereologic Analyses in Brain Aging Research J. Additional Sources of Information
IV.	The Future of Design-Based Stereology in Brain Aging Research
Acknowledgments
References

I. INTRODUCTION

In recent years, the application of design-based stereologic methods to the analysis of the central nervous system has contributed considerably to our understanding of the functional and pathological morphology of the aging brain. Design-based stereology has become the method of choice in quantitative histological analysis. Its advantages over other quantitative techniques in respect to rigor, accuracy, and consistency of results have been documented extensively in the scientific literature.

Originally, design-based stereology was described as a set of methods that provide a three-dimensional interpretation of structures based on observations made on two-dimensional sections [1]. However, in the current use of design-based stereology, many methods make use of three-dimensional sections. The term “design-based” indicates that the methods and the sampling schemes that define the newer methods in stereology are “designed,” that is, defined a priori, in such a manner that one need not take into consideration the size, shape, spatial orientation, and spatial distribution of the cells to be investigated [2]. Eliminating the need for information about the geometry of the cells under investigation results in more robust data because potential sources of systematic errors in the calculations are eliminated [2, 3, 4].

Design-based stereology can be divided into analyses of the global and local characteristics of tissues, the most important of which are volume, number, connectivity, spatial distribution, and length of linear biological structures. These characteristics can be expressed as absolute values (e.g., the volume of the granule cell layer in the human hippocampus, the number of granule cells in the human hippocampal granule cell layer, etc.) or as relative values (e.g., the volume fraction of the human hippocampus occupied by the granule cell layer, the density of granule cells within the human hippocampal granule cell layer, etc.). Both global and local characteristics can be analyzed by a variety of stereologic methods.

This chapter is divided into three parts. The first part provides an overview of recent progress in brain aging research on humans, non-human primates, and rodents with design-based stereology and reviews the main outcome of such investigations. The second part of the chapter provides an introduction into the use of design-based stereologic methods that most neuroscientists interested in their use would need to analyze volumes of brain regions, numbers of cells (neurons, glial cells) within these brain regions, mean volumes (nuclear, perikaryal) of these cells, length densities of linear biological structures such as vessels and nerve fibers, and the cytoarchitecture of brain regions (i.e., the spatial distribution of cells within a region of interest). The chapter closes with a short outlook on the future of design-based stereology in brain aging research.

II. RECENT PROGRESS IN BRAIN AGING RESEARCH WITH DESIGN-BASED STEREOLOGY

The application of design-based stereologic methods to the analysis of the central nervous system has considerably contributed to our understanding of the functional and pathological morphology of the aging brain. The main outcome of such investigations revealed first that there is no substantial global neuron or synapse loss in the aging brain, as previously thought [1, 5]. Rather, certain brain regions show a regionally specific loss of neurons and synapses during aging, and various types of neurons change their gene expression profiles during aging (“functional loss”). Second, the patterns of age-related neuron loss in nonhuman primates and rodents are not entirely comparable to those seen in the human brain, which should be considered when using animal models of brain aging. Third, neuron and synapse loss observed in pathological conditions such as Alzheimer’s disease seem to be the result of the disease process but not a consequence of normal aging. It should also be noted that design-based stereologic studies in brain aging research are always performed on postmortem autopsy tissue. Accordingly, all findings discussed in the following represent results from cross-sectional studies rather than longitudinal studies.

A. DESIGN-BASED STEREOLOGIC ANALYSES OF THE AGING HUMAN BRAIN

Pakkenberg and Gundersen [6] performed the most comprehensive investigation of age-related alterations in the total number of neurons in the human cerebral cortex. Analyzing 94 brains covering the age range from 20 to 90 years, they found an average total number of 23 billion neocortical neurons in male brains (and 19 billion in female brains). Only approximately 10% of all neocortical neurons were lost over the lifespan in both sexes. In a follow-up study, total numbers of glial cells in the neocortex were compared between six aged individuals (age range 81 to 98 years) and six young individuals (age range 18 to 35 years) [7]). No differences between the groups were found (36 billion vs. 39 billion glial cells).

These reports of only minor alterations in global neuron and glial cell numbers are in contrast with reports of regional neuron loss in the aging human cerebral cortex. Kordower and colleagues [8] found on average an approximately 40% loss of layer II entorhinal cortex neurons and an approximately 25% loss of perikaryal volume of these neurons in the brains of individuals with mild cognitive impairment (but no Alzheimer’s disease), compared with individuals with no cognitive impairment. Both loss and atrophy of layer II entorhinal cortex neurons significantly correlated with performance on clinical tests of declarative memory. Age-related loss of layer II entorhinal cortex neurons in neurologically normal subjects was recently confirmed in an independent sample [9], whereas earlier studies found no age-related loss of these cells in cognitively normal individuals [10, 11].

According to West [12], the human hippocampus also shows a regionally specific pattern of age-related neuron loss across the age range of 13 to 85 years, with substantial loss of neurons in the subiculum (52%) and the hilus of the dentate gyrus (31%) but no significant changes in the remaining hippocampal subdivisions. This specific loss of neurons in the hippocampus and the entorhinal cortex may qualify as a morphological correlate of senescent decline in memory in that they can be expected to compromise the functional integrity of brain regions known to be intimately involved in memory processing.

Concerning synapse loss in the aging human cerebral cortex, Scheff and colleagues [13] found that the synaptic volume density in lamina III and V of the superior-middle frontal cortex did not correlate with age in a sample of 37 cognitively normal individuals ranging in age from 20 to 89 years. Corresponding data for the hippocampus have not been published. On the other hand, there seems to occur a 30 to 40% reduction in the total length of myelinated fibers within the white matter of the human brain, with a particular decline of myelinated fibers with the smallest diameter [14, 15].

The human locus coeruleus does not show age-related loss of neurons [16, 17], and in the cerebellum, substantial loss of Purkinje and granule cells during aging was only observed in the anterior lobe (approximately 40% [18]). In the substantia nigra, conflicting data have been reported, of either no age-related loss of melanin-containing neurons [19] or an approximately 40% loss of these neurons during aging [20, 21]. Nevertheless, the well-established decrease in dopaminergic nigrostriatal function with age seems to be related to phenotypic age-related changes (functional loss) rather than to frank neuronal degeneration. This is supported by reports of dramatic age-related loss of neurons immunoreactive for tyrosine hydroxylase (on average, approximately 45% [19]), the dopamine transporter (on average, approximately 75% [20]), guanosine triphosphate cyclohydrolase I (a critical enzyme in catecholamine function, on average approximately 80% [22]), and nuclear receptor-related factor 1 (associated with the induction of dopaminergic phenotypes in developing ...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Series Preface
• Preface
• About the Editor
• Contributors
• SECTION I Assessing Cognitive Aging
• SECTION II Quantifying Aging-Related Changes in the Brain
• SECTION III Assessing Functional Changes in the Aging Nervous System
• SECTION IV Mechanisms Contributing to Brain Aging
• Index