Sandra Rosenthal, Jack and Pamela Egan Professor of Chemistry and professor of pharmacology and chemical and biomolecular engineering, and collaborators have proposed that the seasonal rate of change in daylight has the greatest effect on illnesses with seasonal patterns, including bipolar disorder and major depressive disorder with a seasonal pattern, more commonly known as seasonal affective disorder.
This means that it is the change in the amount of sunlight from the day before, not the amount of sunlight itself, that affects how a person with such an illness feels and experiences the world.
The team used NASA’s solar insolation data – the amount of solar radiation that hits the ground – to calculate the rate of change at 51 sites around the world. Travis Josephs, an undergraduate in neuroscience conducting this work as his Immersion Vanderbilt project, extracted NASA’s data.
Localized to 11 square miles (roughly three-tenths the size of Walt Disney World), the data gave the team a granular level of detail that can help people identify exactly how changes to sunlight impact what they’re experiencing anywhere in the world.
“We noticed that even at the same latitude the patterns of change in solar insolation vary dramatically due to climate,” Rosenthal said. For example, during October in Los Angeles the rate of change of solar insolation ticks up because the Santa Ana winds push the marine layer out to sea. NASA data picked all of this up, including weather extremes like volcanic eruptions or smoke from wildfires.
Rosenthal has been living with bipolar disorder for 28 years and after the first seven years began to notice feeling better in spring and worse in fall. “In the third week of August I always went to the doctor because I always felt sick, like I had mono,” Rosenthal said.
This research has the potential to give people with bipolar disorder and major depressive disorder with a seasonal pattern a tool to self-manage their illnesses. With data on the rate of change of solar insolation, people can make more informed adjustments to their compensation strategies, including working with their health care providers to adjust their medication and the timing of their light or dark therapy.
Clinicians aware of this research now have a momentous opportunity to help their patients identify patterns that affect their lives. “Little lightbulbs went off about patterns I experienced once I saw this data,” Rosenthal said.
“This is no longer just a hunch. We now have the data to show that this pattern is real and true for people – not just myself. My hope is that this information resonates with others’ illnesses in a way that helps them.”
“Our collaboration began with a conversation about the photoperiod effects in an animal model of bipolar disorder, and we quickly realized that there was an interesting angle to pursue with respect to seasonal patterns in bipolar patients,” said Richard McCarty, a collaborator and professor of psychology.
“Sandra’s personal experience with bipolar disorder was essential in moving these ideas forward and shaping the two publications.”
Rosenthal and her colleagues are engaging with esteemed academic researchers working on differences in sunlight and bipolar disorder who have taken their work to clinical settings. By sharing their data and the team’s calculations, Rosenthal anticipates further confirming their work.
She also intends to build on her previous work with white light quantum dots to investigate if there is a way to study how mammals experience light and associated changes in brain chemistry.
Human physiology and behavior exhibit seasonal changes during the fall–winter time interval, including lower mood, reduced energy, sleepiness, decreased interest in social interactions, and increased preference for energy-rich starchy foods, leading to possible weight gain, with spontaneous resolution in spring or summer [1,2]. In certain individuals, seasonal changes in mood include episodes of depression during winter that can be improved with bright light exposure [1,3,4,5]. Seasonal and daily rhythms govern metabolic processes; therefore, alterations in these processes can have an impact on manifestations of metabolic conditions, such as diabetes, and cardiovascular risk [6,7]. The underlying mechanisms of these health outcomes and of physiological and behavioral seasonal changes could be the consequence of seasonal elongation of the duration of the nocturnal melatonin secretion in response to the shortened photoperiod [8], or delayed circadian rhythms due to progressively reduced exposure to morning light during fall and winter [9,10].
A large body of literature now indicates that the effects of light on physiology and behavior such as those described above (so-called non-image forming (NIF) responses) originate via a specific class of intrinsically photosensitive retinal ganglion cell (ipRGCs) [11,12]. The ipRGCs integrate phototransduction via their own photopigment, melanopsin, with synaptic input from rods and cones, and relay signals to the master circadian clock in the hypothalamic suprachiasmatic nuclei as well as other subcortical brain sites [13,14,15]. This arrangement enables ipRGCs to detect the pronounced changes in ambient illumination that occur across the solar day and coordinate downstream physiological responses accordingly. Mood-modulating effects of light are therefore believed to be mediated by ipRGCs, acting via effects on the biological clock, neuroendocrine function, serotonergic tone, and/or more direct impacts on the arousal state [16,17,18,19,20,21,22].
Given the growing awareness of the NIF system’s wide-ranging influence, there is now significant interest in understanding the extent to which ‘unnatural’ patterns of light exposure, associated with modern lifestyles, negatively impact health and well-being. Currently, there is an abundance of literature linking shift work as well as night-time artificial light exposure with a variety of negative health outcomes, including increased risk of developing metabolic disease [23], various forms of cancer [24,25,26], and mood disorders [27].
A key unresolved question, however, is the extent to which alterations in the daily and seasonal patterns of light exposure, associated with modern life, have led to impaired physical and psychological health in the general population [28]. Hence, increased night-time light and reduced daytime exposures to natural sunlight, resulting from increasingly dominant indoor occupational patterns and generalized access to modern electric lighting, are expected to alter the diurnal variations in ipRGC output. This output is required to appropriately coordinate daily physiological rhythms [29]. Similarly, increased evening exposure to short-wavelength light from LED lights, televisions, tablets, tablets, and smartphones [30] is believed to be particularly disruptive to circadian function [31,32]. Indeed, studies in community settings have reported how night-time artificial light exposure is associated with obesity, elevated blood pressure, and depression [33,34,35].
The Old Order Amish (OOA) are a unique population that can help assess the relationship between modern patterns of light exposure and health. The OOA are a predominantly agrarian society using non-grid-fed lights, and do not use artificial time cues with watches or alarm clocks [36]. Thus, their daily patterns of light exposure are expected to differ qualitatively and quantitatively from the general population. The OOA have lower incidence of seasonal affective disorder (depressive disorder triggered by seasonal changes) (<1%) [37,38], lower rates of diabetes [39], and different seasonal-adjusted sleep patterns (with lesser proportion of short sleepers, and earlier wake and sleep onset time) [40] relative to non-Amish. It is tempting to speculate that such differences between the OOA versus the general North American population may be mediated, at least in part, by differences in daily and/or seasonal patterns of light exposure between them.
Comparisons of quantitative and qualitative ambulatory light exposure, as well as comparisons of activity patterns in OOA with modern counterparts, may provide clues to understanding the low prevalence of metabolic and seasonal mood problems in the OOA community. Here, we address this question through a preliminary study that measures seasonal variations in daily activity and ambulatory light exposure (intensity, wavelength, and timing) among the OOA, via wrist-worn monitors. This study primarily aimed to assess seasonal changes in daily light exposure among the OOA and their association with physical activity. We hypothesized that physical activity and the amount and spectral content of light exposure would vary according to photoperiod.
Conclusions
Future studies should include mood ratings to account for bidirectional influences between mood and light exposure. Biomarkers of circadian rhythm changes (e.g., levels of melatonin and cortisol) may also offer unique insight into the mechanisms underlying these health differences in OOA. Recently, a lower frequency of short sleep and a relatively earlier phase of sleep have been reported in the OOA in comparison with non-Amish [40]. These could be, in part, important consequences of light exposure differences, in particular the higher diurnal variation of light exposure, with brighter days and darker nights, potentially contributing to better affective, metabolic and cardiovascular health in OOA relative to non-Amish [39,40,73].
We quantified daily variation in activity and ambulatory light exposure across the seasons within a population without access to grid-fed electricity. Collectively, our data support the notion that light exposure patterns typical of the OOA could be protective, at least in part, against conditions characterized by circadian, sleep, affective, and metabolic dysregulation. The well-documented genetic lineages of the OOA, as well as the availability of genetic data and material, and close physical proximity of comparator populations at identical latitudes, present an unparalleled opportunity for future work on genetic, epigenetic, and environmental chronobiological factors and their interactions, with a long-term aim to better understand and target the dysregulation of biological rhythms predictively associated with metabolic, cardiovascular and mental illness.
reference link : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344929/
More information: Sandra J. Rosenthal et al, Seasonal effects on bipolar disorder: A closer look, Neuroscience & Biobehavioral Reviews (2020). DOI: 10.1016/j.neubiorev.2020.05.017
Sandra J. Rosenthal et al, Rate of change in solar insolation is a hidden variable that influences seasonal alterations in bipolar disorder, Brain and Behavior (2021). DOI: 10.1002/brb3.2198
