Division of Rheumatology, Johns Hopkins University School of Medicine, 1830 East Monument Street Suite 7500, Baltimore, MD, 21205, USA.
Independent Researcher, London, UK.
Environ Health. 2021 Mar 16;20(1):28. doi: 10.1186/s12940-021-00692-4.
To examine the influence of solar cycle and geomagnetic effects on SLE disease activity.
The data used for the analysis consisted of 327 observations of 27-day Physician Global Assessment (PGA) averages from January 1996 to February 2020. The considered geomagnetic indices were the AP index (a daily average level for geomagnetic activity), sunspot number index R (measure of the area of solar surface covered by spots), the F10.7 index (measure of the noise level generated by the sun at a wavelength of 10.7 cm at the earth's orbit), the AU index (upper auroral electrojet index), and high energy (> 60 Mev) proton flux events. Geomagnetic data were obtained from the Goddard Space Flight Center Space Physics Data Facility. A time series decomposition of the PGA averages was performed as the first step. The linear relationships between the PGA and the geomagnetic indices were examined using parametric statistical methods such as Pearson correlation and linear regression, while the nonlinear relationships were examined using nonparametric statistical methods such as Spearman's rho and Kernel regression.
After time series deconstruction of PGA averages, the seasonality explained a significant fraction of the variance of the time series (R = 38.7%) with one cycle completed every 16 years. The analysis of the short-term (27-day) relationships indicated that increases in geomagnetic activity Ap index (p < 0.1) and high energy proton fluxes (> 60 Mev) (p < 0.05) were associated with decreases in SLE disease activity, while increases in the sunspot number index R anticipated decreases in the SLE disease activity expressed as PGA (p < 0.05). The short-term correlations became statistically insignificant after adjusting for multiple comparisons using Bonferroni correction. The analysis of the long-term (297 day) relationships indicated stronger negative association between changes in the PGA and changes in the sunspot number index R (p < 0.01), AP index (p < 0.01), and the F10.7 index (p < 0.01). The long-term correlations remained statistically significant after adjusting for multiple comparisons using Bonferroni correction.
The seasonality of the PGA averages (one cycle every 16 years) explains a significant fraction of the variance of the time series. Geomagnetic disturbances, including the level of geomagnetic activity, sunspot numbers, and high proton flux events may influence SLE disease activity. Studies of other geographic locales are needed to validate these findings.
研究太阳活动周期和地磁效应对 SLE 疾病活动的影响。
分析中使用的数据来自 1996 年 1 月至 2020 年 2 月的 327 次 27 天医生整体评估（PGA）平均值。考虑的地磁指数包括 AP 指数（地磁活动的日平均水平）、太阳黑子数 R 指数（测量太阳表面斑点覆盖的区域）、F10.7 指数（测量太阳在地球轨道上波长为 10.7cm 时产生的噪声水平）、AU 指数（上极光电喷流指数）和高能（>60Mev）质子通量事件。地磁数据来自戈达德太空飞行中心空间物理数据设施。作为第一步，对 PGA 平均值进行时间序列分解。使用参数统计方法（如 Pearson 相关和线性回归）检查 PGA 与地磁指数之间的线性关系，使用非参数统计方法（如 Spearman's rho 和核回归）检查非线性关系。
在 PGA 平均值的时间序列分解之后，季节性解释了时间序列方差的很大一部分（R=38.7%），每 16 年完成一个周期。短期（27 天）关系分析表明，地磁活动 Ap 指数的增加（p<0.1）和高能质子通量（>60Mev）（p<0.05）与 SLE 疾病活动的减少有关，而太阳黑子数 R 指数的增加预示着 SLE 疾病活动的减少，表现为 PGA（p<0.05）。使用 Bonferroni 校正调整多次比较后，短期相关性变得无统计学意义。长期（297 天）关系分析表明，PGA 变化与太阳黑子数 R 变化（p<0.01）、AP 指数（p<0.01）和 F10.7 指数（p<0.01）之间存在更强的负相关。使用 Bonferroni 校正调整多次比较后，长期相关性仍具有统计学意义。
PGA 平均值的季节性（每 16 年一个周期）解释了时间序列方差的很大一部分。地磁干扰，包括地磁活动水平、太阳黑子数和高能质子通量事件，可能会影响 SLE 疾病活动。需要对其他地理区域进行研究，以验证这些发现。
