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The possible effects of the solar and geomagnetic activity on multiple sclerosis

Clinical Neurology and Neurosurgery, July 2016, Pages 82 - 89


  • MS patient admittance rates were correlated with the solar and geophysical data.
  • Increase in the admittance rates 7–8 months after intense geomagnetic activity.
  • More prolonged increase in the admittances with prolonged helio-geomagnetic events.
  • Instant rise in the admittances the following month after storms with DST <−150 nT.
  • Highest numbers of admissions 7–8 months after storms with DST index <−200 nT.



Increasing observational evidence on the biological effects of Space Weather suggests that geomagnetic disturbances may be an environmental risk factor for multiple sclerosis (MS) relapses. In the present study, we aim to investigate the possible effect of geomagnetic disturbances on MS activity.

Patients and methods

MS patient admittance rates were correlated with the solar and geophysical data covering an eleven-year period (1996–2006, 23rd solar cycle). We also examined the relationship of patterns of the solar flares, the coronal mass ejections (CMEs) and the solar wind with the recorded MS admission numbers.


The rate of MS patient admittance due to acute relapses was found to be associated with the solar and geomagnetic events. There was a “primary” peak in MS admittance rates shortly after intense geomagnetic storms followed by a “secondary” peak 7–8 months later.


We conclude that the geomagnetic and solar activity may represent an environmental health risk factor for multiple sclerosis and we discuss the possible mechanisms underlying this association. More data from larger case series are needed to confirm these preliminary results and to explore the possible influence of Space Weather on the biological and radiological markers of the disease.

Keywords: Multiple sclerosis, Acute relapses, Environmental risk factor, Geomagnetic disturbances, Solar flares, Solar wind, Coronal mass ejections.

1. Introduction

Solar activity collectively represents Sunspots, Flares, Coronal Mass Ejections (CMEs) and assorted solar eruptive events. This activity results in the injection of large amounts of radiation (X-rays, UV radiation, etc), high energy particles (electrons and occasionally protons) and high speed solar plasma (as solar wind) to the interplanetary space. These phenomena affect the Earth's upper atmosphere, ionosphere and magnetic field [1] and [2]. The solar activity exhibits an 11-year periodic variation known as a solar cycle which is quantified by the sunspot number. Each cycle is divided into three phases; the rise phase with an increasing range of active phenomena, the maximum phase as the phenomena peak and the decline phase as they gradually decay to the quiet Sun levels.

Earth is protected from the solar activity by its magnetosphere [2]. Yet, under certain conditions solar energy and mass can penetrate the terrestrial environment resulting in magnetospheric disturbances known as geomagnetic activity which includes magnetic storms and substorms. These disturbances are quantified by geomagnetic indices. The DST (Disturbance Storm Index) represents magnetic activity and is derived from a network of near-equatorial geomagnetic observatories measuring the intensity of the globally symmetrical equatorial electrojet (the ring current). It varies, in practice, from +30 nano Tesla (nT) to −200 nT; the range −50 nT to −100 nT characterizes a substorm while values below −100 nT indicate a magnetic storm [2].

A continuously growing body of evidence suggests that the helio-geomagnetic activity may influence various medical conditions and human behaviour (e.g. heart attacks, psychiatric diseases, myocardial infractions, stroke, epilepsy, suicides, and traffic accidents) [3]. The underlying mechanisms (e.g. melatonin suppression [4] and [5], Schumann resonances [6], etc), however, remain speculative.

Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system (CNS) which affects mainly young adults. Attempts have been made to link a number of external stimuli to the pathogenesis of MS including viral and bacterial infections, exposure to sunlight, shifts in environmental temperature, ionizing and non-ionizing radiation, nutrition, hormonal changes, etc., with conflicting results [7] and [8].

Previous studies on the possible association between the solar and geomagnetic factors with multiple sclerosis indicate that the geographic distribution of MS appears to be better related to the geomagnetic than the geographic latitude [9] and [10]. The prevalence of MS is lower in equatorial regions, and increases rapidly as we move towards the north and the south, until it peaks at about 60° [11]. Herein, we study the hypothesis that the geomagnetic activity and the associated solar drivers affect MS activity and we present data from the patient records of the Department of Neurology, University Hospital of Patras, Greece within the 23rd solar cycle (1996–2006).

2. Materials and methods

The data for the solar activity and the geomagnetic index DST were obtained from

the OMNI database [12] for the number of sunspots and the near-Earth solar wind speed, the GOES satellite database [13] for the number of flares, the SOHO/LASCO satellite database for the number of CMEs, and the Kyoto Observatory [14] for the daily values of the DST index.

Cases of MS covering a 23 year period (1984–2006) had been already identified during an epidemiological survey [15]. In this study we included all cases of MS patients who were admitted to the Department of Neurology of the University Hospital of Patras due to an acute episode from 1996 until 2006. These included both the newly diagnosed patients and those with a known history of relapsing-remitting MS (RRMS). The data were collected using the Clinic’s admittance records and the patient files.

We used two common statistical tools [16]:

1. The Pearson’s Product Moment Correlation Coefficient,stripin: si1.gif: It gives an indication on the strength of the linear relationship between two random variables X(t) and Y(t):


stripin: si2.gif

wherestripin: si3.gif, stripin: si4.gif, and stripin: si5.gif are the standard score, sample mean, and sample standard deviation for the random variable X; the same holds forstripin: si6.gif, stripin: si7.gif, and stripin: si8.gif respectively. If r(X,Y) = 0, then X and Y are said to be uncorrelated (or linearly independent as a special case). The closer the value of r(X,Y) is to 1, the stronger the correlation between the two variables.

2. The cross-correlation stripin: si9.gif: It is similar to the Pearson’s Correlation Coefficient but, in this case, a time-lag (τ) is expected between the X(t) and Y(t):


stripin: si10.gif

In this case the cross correlation expresses the correlation coefficient between the random variables X(t) and Y(t + τ), where the latter is shifted in time by the time-lag τ, as a function of lag.

3. Results

Among the 1318 total admittances (Table 1), 753 were female and 565 male patients (ratio 1.33). We calculated the Pearson Correlation Coefficient of the MS admittances per year with the solar wind speed annual maximum, the annual CME and Earth-bound Halo CME number, separately, and with the annual flare and intense flare numbers (Table 2).

Table 1

Monthly distribution of MS patients. Distribution per Month and Year of 1318 Multiple Sclerosis patient admittances (565 male and 753 female) for the 1996–2006 period; each table entry, except for the last row, is written as the sum of male and female patient admission within each month.


1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Total
January 1 + 1 5 + 3 1 + 2 2 + 7 1 + 0 6 + 7 4 + 09 5 + 12 11 + 7 8 + 10 7 + 8 51 + 66
February 0 + 5 1 + 3 0 + 3 2 + 3 1 + 0 3 + 4 8 + 8 9 + 8 4 + 11 12 + 9 8 + 8 48 + 62
March 0 + 2 3 + 1 0 + 3 7 + 3 1 + 4 2 + 8 2 + 5 5 + 6 9 + 8 5 + 11 6 + 3 40 + 54
April 1 + 7 3 + 1 0 + 3 4 + 7 1 + 2 6 + 4 3 + 11 7 + 8 7 + 7 2 + 8 3 + 6 37 + 64
May 4 + 2 1 + 2 2 + 2 2 + 8 3 + 10 3 + 9 6 + 8 6 + 9 6 + 14 13 + 10 4 + 9 50 + 83
June 1 + 3 1 + 3 2 + 3 6 + 4 7 + 10 5 + 7 8 + 7 7 + 12 13 + 14 9 + 10 4 + 8 63 + 81
July 1 + 5 2 + 4 1 + 4 4 + 6 3 + 12 4 + 5 3 + 6 6 + 10 7 + 14 8 + 10 4 + 5 43 + 81
August 3 + 0 2 + 0 2 + 2 3 + 8 3 + 5 5 + 3 3 + 4 2 + 8 4 + 10 10 + 7 3 + 4 40 + 51
September 4 + 1 0 + 3 3 + 2 5 + 3 3 + 7 7 + 5 7 + 1 7 + 8 10 + 9 10 + 9 8 + 3 64 + 51
October 1 + 2 1 + 2 4 + 1 1 + 5 2 + 4 4 + 11 4 + 3 5 + 8 4 + 9 7 + 7 4 + 10 37 + 62
November 5 + 4 2 + 3 5 + 5 2 + 5 5 + 5 4 + 2 1 + 5 6 + 7 10 + 10 8 + 7 4 + 4 52 + 57
December 2 + 2 3 + 5 4 + 2 0 + 6 5 + 2 2 + 1 4 + 3 2 + 5 4 + 5 6 + 5 8 + 5 40 + 41
Total 57 54 56 103 96 117 123 168 207 201 136 1318

Table 2

Correlation of MS Cases to Solar & Solar–Wind Parameters. Pearson Product-Moment Correlation Coeffcient of the annual number of admitted patients with the solar wind speed (Vsw) annual maximum, the annual number of CMEs and the Halo CMEs separately, the annual number of flares and the intense flares (X-type).


Vsw Flares X Flares CME Halo CME
Total 0.77 ± 0.01 0.67 ± 0.03 0.58 ± 0.06 0.50 ± 0.12 0.49 ± 0.13
Males 0.69 ± 0.02 0.63 ± 0.04 0.54 ± 0.09 0.45 ± 0.17 0.49 ± 0.13
Females 0.82 ± 0.00 0.68 ± 0.02 0.59 ± 0.05 0.53 ± 0.10 0.49 ± 0.14

Figs. 1, 2, 3 and 4 show the number of MS patients per month; we present separately the three solar cycle 23 phases, the Rise phase (January 1996–February 2000), the Solar Maximum (March 2000–December 2002) and the Decline Phase (January 2003–December 2006).

The increase of cases (>10 on average per month) during the decline phase coincides with unexpected extreme solar events and intense geomagnetic storms in October–November 2003 [17] and November 2004–January 2005 [18] and [19].

We compared the monthly number of admittances with the geomagnetic index DST values of the 23rd solar cycle. We used the daily DST index values so that the powerful storms would not be smoothed out. By examining the pattern of time variation in Fig 1, Fig 2, Fig 3, and Fig 4 we identified, as significant increases in the admission rate, those that exceed the mean plus standard deviation of the sample in order to minimize the effect of random fluctuations. Throughout the Solar Cycle the variability of the sample was systematically increasing from the rise towards the decline phase. Therefore the mean plus standard deviation confidence level, adopted for each phase, was different as noted at the figure captions.

Fig. 1

Fig. 1

Geomagnetic activity plots for the Rise Phase. Upper panel: The daily values of the geomagnetic index DST during 1996–1999 (Rise Phase). Middle panel: The admittances per month of MS patients during 1996–1999 (Rise Phase); the confidence level marked by the horizontal line was set at 5 + 2.7 (mean plus standard deviation of the sample). Bottom panel: Monthly distribution of males (blue line) and females (red line) MS patients during 1996–1999 (Rise Phase). In the upper and middle panels the significant peaks in the patient admissions were annotated with Greek letters (see text for details). DST: Disturbance Storm Index; MS: multiple sclerosis. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


Fig. 2

Fig. 2

Geomagnetic activity plots for the Maximum Phase. Upper panel: The daily values of the geomagnetic index DST during 2000–2002 (Maximum Phase). Middle panel: The admittances per month of MS patients during 2000–2002 (Maximum Phase).; the confidence level marked by the horizontal line was set at 9.8 + 3.8 (mean plus standard deviation of the sample). Bottom panel: Monthly distribution of males (blue line) and females (red line) MS patients during 2000–2002 (Maximum Phase). In the upper and middle panels the significant peaks in the patient admissions were annotated with Greek letters (see text for details). DST: Disturbance Storm Index; MS: multiple sclerosis. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


Fig. 3

Fig. 3

Geomagnetic activity plots for the Decline Phase (1st Part). Upper panel: The daily values of the geomagnetic index DST during 2002–2003 (beginning of the Decline Phase). Middle panel: The admittances per month of MS patients during 2002–2003 (Beginning of the Decline Phase); the confidence level marked by the horizontal line was set at 14.8 + 4.4 (mean plus standard deviation of the sample). Bottom panel: Monthly distribution of males (blue line) and females (red line) MS patients during 2002–2003 (beginning of the Decline Phase). In the upper and middle panels the significant peaks in the patient admissions were annotated with Greek letters (see text for details). DST: Disturbance Storm Index; MS: multiple sclerosis. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


Fig. 4

Fig. 4

Geomagnetic activity plots for the Decline Phase (2nd Part). Upper panel: Daily values of the geomagnetic index DST during 2004–2006 (Decline Phase). Middle panel: The admittances per month of MS patients during 2004–2006 (Decline Phase); the confidence level marked by the horizontal line was set at 14.8 + 4.4 (mean plus standard deviation of the sample). Bottom panel: Monthly distribution of males (blue line) and females (red line) MS patients during 2004–2006 (Decline Phase). In the upper and middle panels the significant peaks in the patient admissions were annotated with Greek letters (see text for details). DST: Disturbance Storm Index; MS: multiple sclerosis. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


During the Rise phase (1996–1999) three periods of geomagnetic storms (DST <−100 nT) were recorded: in May 1998 (label α in Fig. 1), in August–September and November 1998 (label β in Fig. 1), and in October 1999 (label γ in Fig. 1 and 2).

Seven to eight months after each storm- in November 1998, March 1999 and May 2000- the admittance rate was increased (≥10 cases/month). Moreover, several substorms occurred until April 1999 that may explain the persistence of the increased admission rates (10–11 cases/month) from March to August 1999.

During the Solar maximum (2000–2002), increased admittance rates were recorded six to seven months after the intense geomagnetic activity periods (Fig. 2). These storms occurred in April-May 2000 with DST <−150 nT (Fig. 2, label δ), in July-October 2000 with DST <−150 nT, (Fig. 2, label ε) and in March-April (label στ in Fig. 2) and October-November 2001 with DST <−200 nT (label ζ in Fig. 2). There was also a peak of admittances immediately after storms with DST <−150 nT: 17 and 15 admittances for June and July 2000, 10 in November 2000, 12 from March to June 2001, and 13 in January and 16 in February 2002.

The solar eruptive phenomena maximum during August-October 2002 is marked by intense flares and Halo CMEs which trigger a sequence of storms and substorms during the August-December 2002 period (label η, Fig. 3). Contrary to the intense periods mentioned above, an immediate rise in the MS patients' admission rate was not recorded. This extended activity period was followed by a high MS case rate 7–8 months later, in January-July 2003 (15–19 case with a small dip of 11 cases in March).

The maximum values of admittances (17 and 19) appeared in 2000 and 2003. The former coincides with the sunspot solar maximum (2000) and the latter with maximum solar eruptive events (2002).

During October–November 2003 (label θ, Fig. 4) of the decline phase many CMEs powerful flares- some with high energy proton fluxes near earth- and the cycle solar wind speed peak (≈1000 km/sec) were recorded. These phenomena were associated with intense geomagnetic activity (DST <−200 nT). MS admittance rates increased immediately in October-November 2003 (13), but also between January 2004 and August 2004 (18, 15, 17, 14, 20, 27, 21, and 14 for these eight months). In July 2004 (label ι, Fig. 4) an isolated storm might be related to an extension of the increased MS admittances during September and October 2004 (19, 13).

In November 2004 a double storm (DST peaks at −213 nT and −190 nT) introduced a very active helio-geomagnetic period (label ια, Fig. 4). The most intense proton event of all times (20 January 2005) was recorded in this period. Multiple flares, CMEs, substorms and storms were recorded in January 2005. The admittance rate increased immediately in November 2004 (20) and again during January-May 2005 (18, 21, 16, 10, and 23 for the five months). The peak in May 2005 (23) was seven months after the active period described above. A storm in May 2005 might be associated with the persistence of high admittance rates in June and July 2005 (19 and 18).

From April to September 2005 (label ιβ, Fig. 4) many substorms followed the May 2005 storm. We note an immediate increase in admittance rates during August-December 2005 (17, 19, 14, 15 and 11) and a late increase in January and February 2006 (15 and 16). During 2006 (solar minimum), only one storm, in December 2006, was recorded. We observed a decrease in the number of admittances.

For the entire cycle, we recorded the maximum admittance rate (27) in June 2004, eight months after the extreme helio-geomagnetic activity period, in October and November 2003. The second peak of admittances (23) for the entire cycle is recorded seven months (May 2005) after the second most intense period of helio-geomagnetic activity.

From the daily DST record, we derived three time series: (a) the monthly DST peak, (b) the DST mean value for each month and (c) the σDST (the DST mean absolute deviation). The DST peak retains information on short intense storms lost in the monthly average. The results indicate a time lag of 7–8 months between increased patient admissions per month and the DST time series (Fig. 5).

Fig. 5

Fig. 5

Cross Correlation of MS cases with the DST index. Cross correlation of the monthly admittance rates (upper panel) with the mean DST and the peak DST (monthly values) (middle panel), and with the σDST (standard deviation of DST) (bottom panel) between 1996 and 2006. The x-axis is Time (T) in months. DST: Disturbance Storm Index; MS: multiple sclerosis.


An additional verification to the time series examination, mentioned above, was performed based on the cross correlation diagram peak, at the eight months time-lag. We calculated the Pearson product-moment correlation coefficient between the monthly MS admittance rates and the σDST, time-shifted by 8 months lag, and the result was found ≈55% which is quite acceptable.

A fourth index, labeled Sum (DST), was introduced. This sums every value under −50 nT for every month in order to combine storm intensity and duration effects. The results for the 8 month time lag gave cross correlation equal to 0.30 (p < 0.001) (Table 3). This result is statistically significant as it represents an environmental risk factor and not the main cause of the MS relapse.

Table 3

Cross Correlation between MS cases and Sum(DST) index. Cross correlation between the number of admitted patients and the SumDST index. We note good correlations after a period of 6–8 months with the best correlation at 8 months (p-value < 0.001).


Time Lag Cross Correlation P-Value
−3 0.103 0.247
−2 0.129 0.145
−1 0.086 0.326
0 0.160 0.067
1 0.006 0.943
2 0.108 0.220
3 0.205 0.019
4 0.198 0.024
5 0.100 0.264
6 0.278 0.002
7 0.274 0.002
8 0.300 0.001
9 0.187 0.039
10 0.197 0.029
11 0.090 0.324
12 0.121 0.188

4. Discussion

To summarize the above analysis, we observed an increase in the admittances of patients suffering from acute MS relapses 7–8 months after intense geomagnetic activity events. When the duration of the helio-geomagnetic events was prolonged, this increase in the number of admittances seems to extend in a wider period of time. When the intensity of the storms was in the area where the DST index was under −150 nT we observed, not only a rise 7–8 months later, but also an instant rise in the admittances during the following month. In the rare occasions where the DST index was under −200 nT we noted the highest numbers of admissions 7–8 months after the storms.

The pathogenesis of MS is probably multifactorial and involves both genetic and environmental causes [20]. There is an increasing body of evidence supporting a link between late Epstein Barr infection and MS through a possible mechanism of molecular mimicry [21]. Numerous studies support a link between Vitamin D deficiency and onset, relapses and progression of MS, although the results of Vitamin D supplementation have been conflicting [22], [23], and [24]. More recently, specific polymorphisms of the Vitamin D receptor are shown to increase the risk of MS [25]. The incidence of MS is also associated with the month of birth, due to decreased sunlight exposure during pregnancy and vitamin D deficiency in prenatal life for births in spring [26]. Moreover, with the exception of certain areas such as Italy and northern Scandinavia, MS prevalence follows a latitude gradient [27].

On the other hand there is little information concerning the effect of the geomagnetic disturbances on MS. A meta-analysis by Sajedi and Abdollahi [28] showed that MS prevalence variations and distribution could be explained by the angular distance of each region to the geomagnetic 60° latitude, implicating cosmic radiation to MS pathogenesis. A possible explanation for the mechanism that drives the effects of geomagnetic energy on human disease and in particular MS is largely unknown. A recent paper argues that the generation of a hypothetical melanoma-like neuromelanin might be a key element in the pathogenesis of the disease. It is postulated that an oxidatively charged form of an altered melanin, triggered by cosmic radiation, is incapable of eliminating the reactive oxygen species and the free radicals which in turn might promote demyelination [29].

Several investigators have tried to identify the possible mechanisms that geomagnetic energy influences human body. Geomagnetic activity alters melatonin production and might also influence the expression of several genes such as the transcription factor NF-kappaB [30] and [31]. Another study reports that geomagnetic storms are provoking changes in the autoimmune marker levels of patients with antiphospholipid syndrome, whereas others propose a possible inhibitory effect of the geomagnetic fields on the hypothalamic Na(+)-K(+) ATPase leading to increased calcium influx and neuronal cell apoptosis and degeneration [32] and [33]. Changes in the geomagnetic storms affect, through the cryptochrome system that acts as magnetosensor in the retina, the hypothalamic-pituitary-adrenal stress responses, and may also affect the cell membrane permeability and calcium channel activity that in turn influence serotonergic and adrenegic systems in patients with depression [34], [35], and [36]. Moreover, increased cosmic radiation favours electrical instability and promotes damage of the heart muscle in patients with ischemic cardiopathy [37].

Based on the currently available literature we could only speculate the possible mechanisms underlying the hypothesis of MS activation by cosmic radiation disturbances. Overproduction and reduced elimination of free radicals may trigger tissue damage and inflammation, possibly in association with hypothalamic and pituitary hormonal deregulations. Future studies could investigate whether geomagnetic disturbances alter immune cell functions and cytokine production. Neuronal cell membrane electrical instability might promote acute exacerbations of symptoms following periods of intense geomagnetic activity.

Our study presents novel data concerning the possible MS environmental risk factors. More research is needed to verify our preliminary results and probably to investigate the geomagnetic-MS association in different geological latitudes. However, our study has some important limitations. The patient population derives from a limited geographic area in Greece so we cannot further support our findings with data representing different geographical regions. Moreover, the variations in the admittance rate after the intense geomagnetic phenomena, is not significantly consistent throughout the entire study, most possibly because of the relatively small patient population number. In addition, our data are not supported by more detailed clinical information about severity of relapses or disease progression. The possible association of our clinical observation with biological, immunological and imaging data would strengthen our hypothesis and perhaps point towards molecular alterations and mechanisms that could, theoretically, promote MS activation by cosmic radiation. For instance and since Vitamin D insufficiency might be linked to MS, its blood levels might be influenced by alterations in cosmic radiation and such blood measurements are not included in our study.

In conclusion, the present study provides with observational data regarding a possible implication of the geomagnetic disturbances in MS pathogenesis. More research is needed to confirm this novel information and in turn, to investigate the possible molecular alterations, under the influence of the geomagnetic activity, that is related to immune system functions. Such information might provide with new strategies on MS prevention and treatment.

Conflicts of interest



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a Department of Neurology, Medical School, University of Patras, Greece

b Department of Astronomy, Astrophysics and Mechanics, University of Athens, Athens, Greece

c Department of Theoretical and Mathematical Physics, Astronomy and Astrophysics, University of Patras, Patra, Greece

d Department of Neurology, University of Athens, Athens, Greece

Corresponding author at: Department of Neurology,University of Patras, Patra 26504, Greece.

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  • Prof Timothy Vartanian

    dsc_0787_400x400.jpg Timothy Vartanian, Professor at the Brain and Mind Research Institute and the Department of Neurology, Weill Cornell Medical College,...
  • Dr Claire S. Riley

    headshotcsr1_185x250.jpg Claire S. Riley, MD is an assistant attending neurologist and assistant professor of neurology in the Neurological Institute, Columbia...
  • Dr Rebecca Farber

    picforelsevier.jpg Rebecca Farber, MD is an attending neurologist and assistant professor of neurology at the Neurological Institute, Columbia University, in...

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