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Analysis of the Copulsatility of Anterior Pituitary Hormones^*

JOHANNES D. VELDHUIS, MICHAEL L. JOHNSON and EUGENE SENETA

National Science Foundation Science Center in Biological Timing Charlottesville, Virginia 22908
Interdisciplinary Graduate Biophysics Program Charlottesville, Virginia 22908
The Division of Endocrinology and Metabolism, Department of Internal Medicine, University of Virginia Health Sciences Center Charlottesville, Virginia 22908
The Department of Pharmacology, University of Virginia Health Sciences Center Charlottesville, Virginia 22908
The Department of Mathematics, University of Virginia Charlottesville, Virginia 22908

Address all correspondence and requests for reprints to: Dr. Johannes D. Veldhuis, Box 202, Department of Internal Medicine, University of Virginia Health Sciences Center, Charlottesville, Virginia 22908.

We have used combinatorial algebra and computer simulations to calculate expected means, variances, and probabilities of hormone-peak coincidences in 2 or more endocrine pulse series. We illustrate application of this conditional probability analysis to pulsatile LH, FSH, and/or PRL data. We observed that 1) serum LH and FSH pulses in 14 young men were randomly associated on different days (P > 0.10), but highly synchronized on any given day (P < 0.0001); 2) serum LH and FSH (P < 0.0001), LH and PRL (P = 0.023), and FSH and PRL (P = 0.0003) peaks were significantly coupled in healthy postmenopausal women; and 3) the number of triple coincidences among LH, FSH, and PRL release episodes in postmenopausal women significantly exceeded chance expectations (P < 0.0001).

We conclude that suitable statistical coincidence analysis can offer an informative tool with which to evaluate nonrandom event concordance in endocrine investigations, such as clinical studies of the temporally coordinated release of anterior pituitary hormones.

^* This work was supported in part by NIH Grant RR-00847 (to the University of Virginia Clinical Research Center), Research Career Development Award 1-KO4-HD-00634 (to J.D.V.) NIH Grants AM-30302 and GM-28928 (to M.L.J.), NIH Diabetes Endocrinology Research Center Grant DK-38942, NIH-supported Clinfo Data Reductions Systems, and the NSF Science Center in Biological Timing.

Current address: School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia.

Received November 19, 1990.

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