Increased Environmental Temperature Damages DNA and Is an Emerging Health Risk That Correlates with Rates of Acute Lymphoblastic Leukemia (ALL) in Europe
Bibliographic record
Abstract
Introduction: ALL incidence rates are increasing worldwide, and while the etiology of ALL remains elusive it may be associated with climate variables, such as elevated temperature. The World Meteorological Organization (WMO) has calculated that European temperatures have increased more than double the global average over the last 30 years1, but little research has focused on how this might play a role in the etiology of ALL. Both latitude and temperature are potential risk factors in the development of ALL2,3. The intensity of ambient temperature covaries with Latitude, and both could influence the risk of ALL. Furthermore, high ambient temperature during pregnancy was associated with increased likelihood of childhood ALL4. Global climate increases in temperature escalate the likelihood of extreme heat events, which increases reactive oxygen species, increases DNA damage, and suppresses the immune system. Few studies have evaluated both increases in ambient temperature and DNA damage as ALL risk factors. Objective:To investigate the relationship between population-weighted country centroids (location of greatest population density), average country yearly temperature, and ALL rates in European countries between the years 2010-2019. The effect of increased temperature stress on DNA damage in vitro was also investigated. Methods:Incidence and prevalence rates for ALL (Age-standardized data with males and females) were obtained from the Global Health Data Exchange (GHDx) database. Population-weighted latitude/longitude centroids for Europe were obtained from Baylor University and input into the Global Solar Atlas to obtain the average yearly global horizontal irradiance values. European temperature data was obtained from the Climatic Research Unit at the University of East Anglia (Copernicus Climate Data Store). ALL incidence and prevalence rates per 100,000 people for 40 European countries were compared using univariate and mixed linear modeling (including GDP and internet usage), compared to each country's annual mean and maximum temperature at the population centroids. DNA damage was determined in isolated DNA from Leukemic cells using electrophoresis. Statistical analyses were performed using GraphPad Prism and Excel. Results: Using both univariate and mixed linear modelling our preliminary data shows European ALL incidence to be significantly and positively (p < 0.001) associated with maximum mean monthly temperature (°C) between years 2012-2019. supporting the impact of elevated temperature on ALL. In univariate analysis of all years, we detected a significant positive correlation between ALL incidence and prevalence rates with mean annual temperature across countries for each year of analysis (for example in 2014 the ALL prevalence p-value = 0.01 and R = 0.4) and this relationship increased over time between 2010 and 2019. We also detected a significant positive correlation between the increase in mean annual temperature across Europe and an increase in ALL over the past decade. In determining an underlying mechanism, we found DNA damage to be significantly greater in leukemic cells exposed to elevated temperatures (38-41°C) compared to 37°C. Conclusions:Increasing mean and maximum annual temperatures may increase susceptibility to DNA damage and ALL. We speculate this is connected to extreme hot weather events causing increased oxidative stress, DNA damage, and/or immune system suppression. Considering the global climate crisis, our findings of heat induced DNA damage and significance between temperature and ALL rates, provide new possibilities for investigating the etiology of ALL. References World Meteorological Organization. Temperatures in Europe increase more than twice global average. (2022). Pordanjani, S. R., Kavousi, A., Mirbagheri, B., Shahsavani, A. & Etemad, K. Temporal trend and spatial distribution of acute lymphoblastic leukemia in Iranian children during 2006-2014: a mixed ecological study. Epidemiol. Health42, (2020). Coste, A. et al. Residential exposure to ultraviolet light and risk of precursor B-cell acute lymphoblastic leukemia: assessing the role of individual risk factors, the ESCALE and ESTELLE studies. Cancer Causes Control28, 1075-1083 (2017). Rogne, T. et al. High Ambient Temperature in Pregnancy and Risk of Childhood Acute Lymphoblastic Leukemia. medRxiv (2023). doi:10.1101/2023.05.19.23290227
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".