Hormone seasonality in medical records suggests circannual endocrine circuits

Abstract

Hormones control the major biological functions of stress response, growth, metabolism, and reproduction. In animals, these hormones show pronounced seasonality, with different set-points for different seasons. In humans, the seasonality of these hormones remains unclear, due to a lack of datasets large enough to discern common patterns and cover all hormones. Here, we analyze an Israeli health record on 46 million person-years, including millions of hormone blood tests. We find clear seasonal patterns: The effector hormones peak in winter-spring, whereas most of their upstream regulating pituitary hormones peak only months later, in summer. This delay of months is unexpected because known delays in the hormone circuits last hours. We explain the precise delays and amplitudes by proposing and testing a mechanism for the circannual clock: The gland masses grow with a timescale of months due to trophic effects of the hormones, generating a feedback circuit with a natural frequency of about a year that can entrain to the seasons. Thus, humans may show coordinated seasonal set-points with a winter-spring peak in the growth, stress, metabolism, and reproduction axes.

Keywords: HPA axis; gonadal axis; growth axis; systems endocrinology; thyroid axis.

Fig. 1.

Seasonality of hypothalamic−pituitary axes hormones from Clalit medical records. (A) HPA axis with pituitary hormone ACTH and effector hormone cortisol. (B) Thyroid axis with pituitary hormone TSH (thyroid stimulating hormone) and effector hormones T4 and its derivative T3. (C) Sex axis with pituitary hormones FSH (follicular stimulating hormone) and LH (luteinizing hormone), and effector hormones testosterone and estradiol. (D) Growth axis with pituitary hormone GH (growth hormone) and effector hormone IGF1. (E) Lactation pathway with pituitary hormone PRL (prolactin) that controls breast milk production. Each panel indicates the number of tests n, zero-mean cosinor model (gray line), and $R^2$ where significant ($R_{\ast }^2$ for $\mathit{\text{P}}<5\cdot {10}^{-2}$; $R_{\ast \ast }^2$ for $\mathit{\text{P}}<{10}^{-3}$; ns, not significant), with first- or second-order model selected by the Akaike criterion (second-order model is indicated by ^ above $R$). Vertical dashed lines indicate solstices December 21 and June 21.

Fig. 2.

Most pituitary hormones peak in summer whereas effector hormones peak in winter−spring. (A) Peak phases (acrophase) and amplitudes of all hormones whose fit to the cosinor model exceeded $R^2>0.8$. December 21 and June 21 are indicated (vertical dashed lines), as well as winter to April (blue region) and summer (orange region); m and f indicate male and female. (B) Schematic showing spring shift of effector hormones (blue) and approximate antiphase of the pituitary hormones (orange).

Fig. 3.

Blood chemistry tests peak around the shortest and longest photoperiods. (A) Amplitude and time of peak (acrophase) of blood chemistry tests. In blue and orange are 2-mo regions around the solstices December 21 and June 21. (B) Examples of seasonality in blood-test data (red dots) and best-fit cosinor models (line).

Fig. 4.

Mechanism for hormone seasonal phases based on a gland-mass oscillator. (A) Classic model of the HPA axis assumes that the total functional mass of the cells that secrete ACTH and cortisol is constant. It predicts that an input maximal on December 21 will show both ACTH and cortisol peaks on December 21. (B) Model which considers the effect of hormones as growth factors for their downstream glands (red interactions). It predicts a spring delay of cortisol and a summer peak of ACTH. (C) The gland mass model effectively generates a feedback loop in which gland masses can entrain to yearly input cycles. When provided with noise, this can oscillate even without entraining signal, as shown in stochastic simulation of 2 y of entrainment to a yearly photoperiod input, which was $u\left(t\right)=1+gW\left(\varphi \right)cos\left(\omega t\right)+\text{noise}$ followed by 4 y without entraining input $u\left(t\right)=1+\text{noise}$, where $\varphi ={50}^o$, $g=0.5$, and $\omega =2\pi /\text{y}$. Noise was a uniformly distributed random number $U\left(\left[0.5,\hspace{0.17em}1.5\right]\right)$ that was constant over each simulated week. (D) Amplitude of cortisol seasonal variation increases with absolute latitude. Gland mass model, blue line. Blood tests from Australia (16) (open circle), blood (open circle) and urine (square) tests from present study, hair (14) (circle) from United Kingdom, and saliva (triangle) from Sweden (11). (E) Example of a segmented pituitary (red) in an MRI image from the human connectome dataset. (F) Mean pituitary volume from MRI images binned by four seasons (red), with gland mass model prediction (purple).