Understanding Human Biology: Two Distinct Seasons Unveiled
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Chapter 1: The Seasons of Our Biology
The changing hues of autumn leaves, the first snowfall of winter, the blooming daffodils of spring, and the hot summer days are familiar to those living in temperate regions of Europe and the Americas. These four seasons significantly influence people's lives. However, recent findings suggest that human biology operates on a different timeline.
In a groundbreaking study published in Nature Communications, Stanford geneticist Dr. Michael Snyder investigated how biological data varies throughout the year. Analyzing over 1,000 measurements from more than 100 individuals—including genes, proteins, metabolic markers, immune responses, and microbiome data—he found that rather than adhering to four distinct seasons, human biology experiences two primary transitions: one at the onset of winter and another in mid-spring.
Elemental had the opportunity to discuss this research with Dr. Snyder, exploring the motivations behind his study, the implications of these biological seasons, and their potential impact on health. The conversation has been slightly edited for brevity and clarity.
Section 1.1: The Motivation Behind the Study
Elemental: What prompted your exploration of seasonal biological changes?
Michael Snyder: I often pondered why we categorize the year into four seasons. This classification seems arbitrary—perhaps there are 15 seasons or just three. Why not let the data reveal the true number of seasons from a biological perspective? My curiosity combined with a desire to comprehend health patterns inspired this study.
Section 1.2: Key Findings from the Research
What did your research uncover?
Over several years, we observed a group of 109 individuals, collecting more than a thousand measurements. Initially, we identified known biological patterns, such as hemoglobin A1C levels peaking in spring. Our extensive analysis also revealed new patterns. For instance, we discovered that the circadian rhythm gene CIR1 exhibited fluctuations, peaking in late April or early May. Additionally, we noted significant changes in various cytokines involved in immune responses, as well as notable shifts in the microbiome.
After analyzing individual molecules, we sought overarching trends across all the data. Surprisingly, we identified two major patterns: one aligned with late December to early January, indicative of winter, and another emerging in late April to early May, rather than the anticipated peak in summer.
Chapter 2: Seasonal Patterns and Their Implications
The first video, titled "3 Body Problem Creators Reveal How Many Seasons They Need to Tell the Complete Story," discusses the narrative structure and the creators' insights into the storytelling process, which may parallel the biological findings in understanding human experiences through seasons.
The second video, "Dr. Oz | S4 | Ep 10 | Restart Your Body and Reverse Years of Damage," provides tips on enhancing health and reversing biological aging, resonating with the implications of understanding our biological seasons.
Section 2.1: Local Variations in Biological Seasons
All participants in the study were based in Northern California, where seasonal experiences differ from regions like New England or the Southeast. Do you think this two-season pattern is consistent across different climates, or might it vary based on local environmental factors?
While I can't definitively say, I believe that our approach can be adapted to other locations if we gather sufficient data. There’s no reason to assume there are only two seasons; in some areas, there might be three, or even ten. It would be intriguing to explore that further.
Section 2.2: Analyzing Molecular Changes
What types of molecules did you examine? In previous research, you focused on the genome, metabolome, and microbiome. Where did you identify the most significant variations in this study?
We aimed to measure a broad range of molecules, including clinical markers, RNA, proteins, and metabolites—totaling around 20,000 molecules along with microbial data. We observed significant fluctuations in microbes within the nasal cavity and gut, likely influenced by seasonal changes in exercise and diet.
Fascinating. What do you believe accounts for these seasonal variations? Are they primarily driven by biological factors or environmental influences?
The winter pattern aligns with increased viral infections, which alter biological responses. However, the microbiome also plays a role, with bacteria linked to acne peaking during winter. In spring, factors like asthma and allergies contribute to numerous biological changes, but so do metabolic shifts. Our hypothesis suggests that during California’s rainy season, people may be less active, leading to a buildup of metabolic issues that become evident as activity increases in spring.
Section 2.3: The Interplay Between Environment and Health
Could you elaborate on the connection between environmental factors and health? Are the immune system and inflammation changes strictly due to viral infections in winter, or could they indicate an underlying susceptibility?
That’s an insightful question. It’s likely a combination of both factors. We observe increased cytokine levels, which may correlate with viral infections, but it’s also true that people tend to be less healthy in winter, which could heighten their susceptibility to infections.
The spring pattern is more intricate. It features signatures of allergies and asthma, alongside metabolic markers like hemoglobin A1C, which are linked to diabetes and cardiovascular health. We have yet to publish findings that correlate external factors like pollen with internal metabolic changes.
Section 2.4: Understanding Health Seasons
What are the implications of recognizing our biological "seasons"?
The findings have two main implications. Firstly, longitudinal data isn't utilized effectively in medicine. When individuals visit a doctor, their measurements are often compared against population averages rather than tracked over time. Understanding seasonal effects allows for better interpretation of health trends. For example, if hemoglobin A1C levels rise in late April, it may be attributed to reduced activity rather than a chronic issue, which can guide health management.
Alternatively, it suggests that individuals might need to maintain a higher level of activity during rainy seasons to mitigate peaks in cardiovascular and metabolic markers. This knowledge can enhance health interpretation and inform proactive measures.