A New Nonlinear Regression Approach That Allows Detection of Inter-Individual Differences in Single-Point Radioligand Binding Studies

Abstract

In biochemical experiments measuring radio ligands binding or enzyme activities, it is often convenient to pool tissue from different animals if only small amounts are available. Pooling of tissues from different animals may conceal or obscure significant and important differences between individuals in a population. Although linear in nature, the statistical approach and solution to test for inter-individual differences is not straightforward. We therefore introduce a new solution with a nonstandard linear regression equation based on nonlinear iterative least squares regression theory. This procedure has the advantage that it is easy to implement and allows for a full statistical exploration of this and even more complex models. As an example, single-point radioligand binding experiments were carried out to test for inter-individual differences in corticotropin-releasing hormone (CRH) receptor densities in 6 different brain sections of 7 rats. These rats were shown to differ substantially in their behavioral response to central administration of corticotropin-releasing hormone. The studies were performed with [125I]Tyro-oCRH as a radioligand, and replicates of total binding and nonspecific binding were determined. The variable of interest (specific binding) was then calculated as the difference between total binding and nonspecific binding. Two nested regression models were compared using a partial F-test, which in the case of a significant result (a = 0.05, two-sided) was followed post-hoc by a modification of Scheffe's test. Using Monte-Carlo randomization techniques, statistical power was empirically determined for each brain section. As a result, only the piriformis cortex was found to have statistically significant inter-individual differences (p = 0.024), which is also confirmed by the relatively high power of 82% (a =0.05, two-sided).

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2000
Accession Number
ADA455975

Entities

People

  • C.-m. Staschen
  • L. D. Homer
  • M. J. Munazza
  • P. B. Massell
  • S. T. Ahlers

Organizations

  • Naval Medical Research Center

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Biomedical Research
  • Brain
  • Cerebellum
  • Data Analysis
  • Data Science
  • Equations
  • Governments
  • Health Services
  • Hypothalamus
  • Information Science
  • Laboratory Animals
  • Monte Carlo Method
  • Probability
  • Regression Analysis
  • Standards
  • Statistical Algorithms
  • Statistical Analysis

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