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. Author manuscript; available in PMC: 2024 Dec 1.
Published in final edited form as: Psychol Health Med. 2023 Mar 28;28(10):3052–3063. doi: 10.1080/13548506.2023.2195670

Health outcomes of sensory hypersensitivities in myalgic encephalomyelitis/chronic fatigue syndrome and multiple sclerosis

Kensei I Maeda a, Mohammed F Islam b, Karl E Conroy a, Leonard Jason a
PMCID: PMC10533743  NIHMSID: NIHMS1885710  PMID: 36977713

Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a poorly understood chronic illness with many case definitions that disagree on key symptoms, including hypersensitivities to noise and lights. The aim of the current study was to understand the prevalence rates and characteristics of these symptoms amongst people with ME/CFS and to compare them to people with another chronic illness, multiple sclerosis (MS). International datasets consisting of 2,240 people with either ME/CFS or MS have completed the DePaul Symptom Questionnaire (DSQ) and the Short Form Health Survey Questionnaire (SF-36). Hypersensitivities to noise and lights were indicated from items on the DSQ, and participants were analyzed against DSQ and SF-36 subscales through a multivariate analysis of covariance. There were significantly higher percentages of people with hypersensitivities in the ME/CFS sample compared to the MS sample. Regardless of illness, participants that exhibited both hypersensitivities reported greater symptomology than those without hypersensitivities. Healthcare providers and researchers should consider these symptoms when developing treatment plans and evaluating ME/CFS case diagnostic criteria.

Keywords: myalgic encephalomyelitis/chronic fatigue syndrome, multiple sclerosis, auditory hypersensitivity, light sensitivity

Introduction

People with the illness known as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) experience significant symptoms including fatigue, post-exertional malaise, and cognitive impairment (Carruthers et al., 2003, 2011; Fukuda et al., 1994; Institute of Medicine, 2015). Patients with ME/CFS report lower qualities of life than those with other conditions and are unlikely to fully recover from this condition (Cairns & Hotopf, 2005).

According to Brurberg and colleagues (2014), there are over 20 case definitions for ME/CFS. While these case definitions have some overlapping criteria with fatigue as the core symptom, there is less consensus regarding which other symptoms should permit a diagnosis of ME/CFS (Conroy et al., 2022). Because of this discrepancy, adults with ME/CFS may struggle to secure adequate treatment and resources such as disability benefits.

The lack of consensus on which symptoms should be included in ME/CFS diagnostic criteria and the exclusionary requirement of the diagnosis places critical importance on identifying differentiating symptoms between ME/CFS and other similar chronic illnesses. One such chronic illness is multiple sclerosis (MS), a debilitating immune-mediated disease that shares several symptoms as ME/CFS, such as pain, trouble with coordination, and neurocognitive dysfunction (Goldenberg, 2012). While ME/CFS and MS each have several known viral triggers, both illnesses have an overlapping viral etiology in the Epstein-Barr virus, making it imperative to identify distinctions between the two illnesses (O’neal & Hanson, 2021; Bjornevik et al., 2022; Shikova et al., 2020). Though ME/CFS and MS share symptomatology, prior studies have found that those with ME/CFS reported greater functional limitations than those with MS (Jason et al., 2017).

To identify differentiating symptomatology between ME/CFS and MS, one may assess lesser studied symptoms, such as hypersensitivities to noise and lights. Few studies have examined the characteristics of noise and lights hypersensitivities in adults with ME/CFS or MS. For instance, studies have found prevalence rates of lights hypersensitivity among people with ME/CFS to vary between 48–90% (De Becker et al., 2001; Hutchinson et al., 2014). No study has determined prevalence rates for noise hypersensitivity among people with ME/CFS or MS.

While often investigated separately, there is evidence to suggest value in investigating the two symptoms together. Analyzing people with both hypersensitivities can reveal potential impacts of simultaneous symptoms that are often studied in disorders such as migraines and fibromyalgia, but not in ME/CFS (Main et al., 1997; Wilbarger & Cook, 2011). In these other disorders, there is greater health dysfunction and distress in people who experience multiple hypersensitivities compared to those who do not. It is worth investigating whether the two symptoms have similar interactions in ME/CFS and MS. The purpose of the current study was to better understand the functional impairment interactions with noise and light hypersensitivities among people with ME/CFS, and secondly to determine whether these symptoms can differentiate those with ME/CFS from those with MS.

Methods

Participants

Participants for the current study were derived from multiple international datasets. Initially, there was a total of 2,402 participants with ME/CFS and 270 participants with MS for the current study. Following exclusionary procedures due to incomplete DSQ, SF-36 and demographic data, the sample sizes were reduced to 2,042 participants with ME/CFS and 198 participants with MS. The individual datasets are described below.

DePaul sample

Researchers at DePaul University collected a convenience sample of adults who self-identified as having ME/CFS. Participants were at least 18 years of age and had either self-reported or a medical diagnosis of ME or CFS. After removing participants with incomplete data, the sample included 210 participants (83.3% female) with a mean age of 52.1 years (SD = 11.2).

Biobank 2016 sample

Solve ME/CFS Initiative collected a sample of adults who were recruited by physicians who specialized in diagnosing ME/CFS. After removing participants with incomplete data, the sample included 481 participants (77.1% female) with a mean age of 54.8 years (SD = 12.1).

Newcastle sample

The Newcastle-upon-Tyne Royal Victoria Infirmary clinic collected data from a sample of adults who were referred to them for a medical assessment due to CFS. After removing participants with incomplete data, the sample included 92 participants (81.5% female) with a mean age of 45.6 years (SD = 12.1).

Norway 1 sample

Participants from southern Norway were contacted via healthcare professionals, ME/CFS patient organizations, and an ME/CFS patient education waiting list. These participants were at least 18 years of age and had received ME/CFS diagnoses from physicians and medical specialists. After removing participants with incomplete data, the sample included 168 participants (85.7% female) with a mean age of 43.5 years (SD = 11.9).

Norway 2 sample

Two separate sites in Norway, an inpatient medical ward for severely ill patients and an outpatient clinic at a multidisciplinary ME/CFS center, collected data from a sample of patients who had undergone a comprehensive medical examination. After removing participants with incomplete data, the sample included 55 participants (81.8% female) with a mean age of 35.9 years (SD = 12.1).

Norway 3 sample

A specialized ME/CFS tertiary care center in Norway collected data from a sample of adults who were determined to meet the CCC (Carruthers et al., 2003) diagnosis for ME/CFS. After removing participants with incomplete data, the sample included 116 participants (80.2% female) with a mean age of 38.4 years (SD = 11.3).

Chronic Illness sample

Researchers at DePaul University collected data from a convenience sample of adults living with various chronic illnesses, including ME/CFS and MS. Participants were recruited online through support groups, research forums, and social media platforms. After removing participants with incomplete data, the sample included 462 participants (84.2% female) with a mean age of 47.7 years (SD = 13.0).

Japan sample

The ME Japan Association collected data from a sample of adults with ME/CFS who were recruited through the organization and affiliated physician clinics. After removing participants with incomplete data, the sample included 113 participants (78.8% female) with a mean age of 46.0 years (SD = 13.6).

Spain sample

An ME/CFS specialist physician at a tertiary referral center in Barcelona collected data from a sample of adults who met the Fukuda et al. (1994) criteria for ME/CFS. After removing participants with incomplete data, the sample included 175 participants (84.6% female) with a mean age of 50.4 years (SD = 8.6).

Amsterdam sample

The CFS Medical Center in Amsterdam collected data from a sample of adults through its outpatient clinic. After removing participants with incomplete data, the sample included 344 participants (77.9% female) with a mean age of 37.0 years (SD = 11.6).

Measures

DePaul Symptom Questionnaire (DSQ)

The DSQ is a 54-item self-report measure of ME/CFS symptoms (Jason & Sunnquist, 2018). Those completing the survey are asked to rate the frequency of each symptom over the past six months on a 5-point Likert scale, with 0 = ‘none of the time’, 1 = ‘a little of the time’, 2 = ‘about half the time’, 3 = ‘most of the time’, and 4 = ‘all of the time’. They are also asked to rate the severity of each symptom over the past six months on a similar scale, with 0 = ‘symptom not present’, 1 = ‘mild’, 2 = ‘moderate’, 3 = ‘severe’, and 4 = ‘very severe’. Frequency and severity scores are standardized to a 100-point scale which are then composited for each symptom, with higher scores indicating worse symptoms. These symptom composites are combined along eight symptom domain scores: sleep dysfunction, post-exertional malaise (PEM), neurocognitive dysfunction, immune dysfunction, neuroendocrine dysfunction, pain, gastrointestinal distress, and orthostatic intolerance. All samples except for the Chronic Illness sample completed the DSQ-1, the first version of the measure with 54 items. The Chronic Illness samples completed the DSQ-2, which was created in 2018 and includes several more items in addition to those in the DSQ-1 (Jason & Sunnquist, 2018).

The DSQ has strong test-retest reliability among people with ME/CFS and healthy controls (Jason et al., 2015), along with valid results (Brown & Jason, 2014). The DSQ-1 is available through Research Electronic Data Capture (REDCap) hosted by DePaul University (Harris et al., 2009). The questionnaire can be found here: https://redcap.is.depaul.edu/surveys/?s=H443P9TPFX

Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36)

The SF-36 is a self-report measure assessing the impact of health outcomes on physical and mental functioning across eight domains which are then composited into physical health and mental health summary scores (Ware & Sherbourne, 1992). The summary scores are measured on 100-point scales with a higher score indicating better health outcomes. The SF-36 has demonstrated strong internal consistency and reliability, and it has been tested across many patient groups, including ME/CFS (McHorney et al., 1993).

Hypersensitivities

Direct clinical assessments of the hypersensitivities were not available for the current study, and so certain DSQ items were utilized instead. The DSQ items 34 and 35 assess people’s frequency and severity of lights and noise sensitivities throughout the past six months. A respondent was considered as having a hypersensitivity if frequency was rated as ‘about half the time’ or more and severity was rated as ‘moderate’ or more, consistent with definitions used in prior studies (Digre & Brennan, 2012; Fackrell et al., 2017). Participants were categorized into four hypersensitivity groups: those with no hypersensitivities (‘None’), those with only a noise hypersensitivity (‘Noise only’), those with only a lights hypersensitivity (‘Lights only’), and those with both hypersensitivities (‘Both’).

Data analysis

IBM SPSS Statistics version 26 was used for statistical analyses (IBM, 2012). A chi-square independence test was conducted between the hypersensitivity groups (‘None’, ‘Noise only’, ‘Lights only’, ‘Both’) and illness types (ME/CFS, MS). Cramer’s V was used to measure the strength of association following the chi-square test which will consider the sample size differences between the ME/CFS and MS samples. A two-way multivariate analysis of covariance (MANCOVA) examined the hypersensitivity groups and the illness types as independent variables and the DSQ and SF-36 subscales as dependent variables. The covariates were determined through chi-squared tests on the categorical demographic variables of gender, marital status, and educational status, and independent samples t-tests for the continuous demographic variable of age. Post-hoc pairwise comparisons between hypersensitivity groups were conducted for each illness type with confidence intervals adjusted using the Bonferroni correction.

Results

Inferential statistics are reported in table 1. A chi-squared test on the hypersensitivity groups and illness types yielded significant results, χ2(3,2240)= 102.89, p < 0.001. Though there is a discrepancy in sample size between the ME/CFS and MS samples, there is a small strength of association between the two variables, φc= 0.214, p < 0.001. The MS sample had a larger proportion of participants with no hypersensitivity than that of the ME/CFS sample, while the ME/CFS sample had a larger proportion with both hypersensitivities than that of the MS sample. When examining both ME/CFS and MS samples, participants with hypersensitivities to noise constituted 62.8% (1,406 out of 2,240) of the total study sample, and participants with hypersensitivities to bright lights constituted 54.9% (1,230 out of 2,240) of the total study sample.

Table 1.

Hypersensitivity prevalence rates across illness types

None Noise only Lights only Both
% (n) % (n) % (n) % (n) p
Illness Type <0.001
 ME/CFS 27.0 (552) 15.3 (313) 7.2 (148) 50.4 (1,029)
 MS 56.6 (112) 16.7 (33) 11.1 (22) 15.7 (31)
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Demographic characteristics of the study sample are reported in table 2. Gender, marital status, and educational status indicated asymptomatic distributions of sample sizes in either illness types or hypersensitivity groups and were included as covariates in the multivariate analysis.

Table 2.

Demographic information of illness type and hypersensitivity group

ME/CFS MS None Noise only Lights only Both
n= 2,042 n= 198 n= 664 n= 346 n= 170 n= 1,060
M (SD) M (SD) p M (SD) M (SD) M (SD) M (SD) p
Age 47.0 (13.7) 45.4 (12.6) <0.1 47.6 (14.9) 48.0 (13.1) 47.5 (14.3) 46.3 (12.9) ns
% (n) % (n) % (n) % (n) % (n) % (n)
Gender ns <0.001
 Male 18.9 (386) 18.7 (37) 25.5 (169) 16.8 (58) 21.8 (37) 15.0 (159)
 Female 81.1 (1,656) 81.3 (161) 74.5 (495) 83.2 (288) 78.2 (133) 85.0 (901)
Marital Status <0.05 ns
 Married 53.9 (1,100) 63.1 (125) 54.7 (363) 54.3 (188) 57.1 (97) 54.4 (577)
 Other 46.1 (942) 36.9 (73) 45.3 (301) 45.7 (158) 42.9 (73) 45.6 (483)
Educational Status <0.01 <0.001
 Less than a college degree 44.4 (907) 34.8 (69) 39.0 (259) 36.4 (126) 34.1 (58) 50.3 (533)
 At least a college degree 55.6 (1,135) 65.2 (129) 61.0 (405) 63.6 (220) 65.9 (112) 49.7 (527)
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Hypersensitivities

Table 3 shows the estimated means of the MANCOVA when split by ME/CFS and MS samples, along with statistically significant post-hoc pairwise comparisons between hypersensitivity groups for each DSQ and SF-36 subscale. There was a statistically significant difference between the hypersensitivity groups and illness types on the combined dependent variables after controlling for gender, educational status, and marital status, F(30,6666) = 1.514, p<0.05, V = 0.02, ηp2= 0.007.

Table 3.

Adjusted means (with 95% CIs) of the relationship between hypersensitivity groups and DSQ and SF-36 subscales, controlled for gender, marital status and educational status

Illness Measure None Noise only Lights only Both
ME/CFS n = 552 n = 313 n = 148 n = 1,029
M (95% CI) M (95% CI) M (95% CI) M (95% CI)
DSQ
 Sleep 50.27abc (48.68 to 51.86) 56.85ae (54.75 to 58.95) 57.89bf (54.83 to 60.95) 65.02cef (63.86 to 66.19)
 PEM 55.31abc (53.77 to 56.85) 65.79ae (63.75 to 67.83) 66.13bf (63.16 to 69.10) 74.88cef (73.75 to 76.01)
 Neurocognitive 44.09abc (42.42 to 45.76) 55.91ae (53.70 to 58.12) 53.89bf (50.68 to 57.10) 66.89cef (65.67 to 68.12)
 Immune 23.89abc (22.40 to 25.39) 30.68ae (28.70 to 32.65) 34.08bf (31.21 to 36.96) 41.24cef (40.14 to 42.33)
 Neuroendocrine 28.71abc (27.00 to 30.43) 36.31ae (34.04 to 38.58) 40.15bf (36.85 to 43.45) 48.60cef (47.35 to 49.86)
 Pain 47.27abc (45.16 to 49.37) 56.22ae (53.43 to 59.01) 58.85bf (54.80 to 62.91) 69.49cef (67.94 to 71.03)
 Gastrointestinal 32.00abc (29.98 to 34.01) 38.96ae (36.29 to 41.63) 40.28bf (36.40 to 44.17) 51.27cef (49.79 to 52.75)
 Orthostatic 23.69abc (22.19 to 25.20) 30.25ae (28.26 to 32.24) 33.50bf (30.61 to 36.40) 42.04cef (40.94 to 43.14)
SF-36
 Physical 27.94abc (27.25 to 28.64) 25.10ae (24.18 to 26.02) 25.25bf (23.91 to 26.58) 22.42cef (21.91 to 22.93)
 Mental 44.92c (44.04 to 45.80) 43.47 (42.30 to 44.64) 42.69 (40.99 to 44.38) 42.01c (41.36 to 42.65)
MS n = 112 N = 33 n = 22 n = 31
M (95% CI) M (95% CI) M (95% CI) M (95% CI)
DSQ
 Sleep 40.08ac (36.56 to 43.61) 53.35a (46.87 to 59.82) 50.59 (42.66 to 58.51) 59.65c (52.97 to 66.33)
 PEM 41.54ac (38.12 to 44.96) 58.00a (51.71 to 64.28) 54.80 (47.10 to 62.50) 63.40c (56.91 to 69.89)
 Neurocognitive 32.43abc (28.73 to 36.12) 55.25a (48.45 to 62.04) 49.03b (40.71 to 57.35) 60.16c (53.14 to 67.17)
 Immune 9.11 (5.80 to 12.42) 15.18 (9.09 to 21.26) 16.04 (8.59 to 23.48) 17.18 (10.90 to 23.46)
 Neuroendocrine 18.87c (15.07 to 22.68) 28.72 (21.73 to 35.70) 29.25 (20.69 to 37.80) 37.90c (30.69 to 45.10)
 Pain 37.67ac (33.00 to 42.34) 55.07a (46.49 to 63.65) 54.20 (43.70 to 64.70) 64.88c (56.03 to 73.74)
 Gastrointestinal 18.28 (13.81 to 22.75) 26.95 (18.73 to 35.17) 35.65 (25.59 to 45.71) 30.48 (22.00 to 38.96)
 Orthostatic 17.92c (14.59 to 21.26) 23.97 (17.85 to 30.09) 28.71 (21.21 to 36.21) 34.86c (28.54 to 41.18)
SF-36
 Physical 35.98bc (34.44 to 37.52) 31.98 (29.16 to 34.81) 30.09b (26.63 to 33.55) 27.92c (25.00 to 30.83)
 Mental 44.56c (42.60 to 46.51) 40.40 (36.81 to 43.98) 44.70 (40.31 to 49.09) 37.30c (33.60 to 41.00)
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Note: Similar letters in rows for each domain indicate significant differences (α=0.01, Bonferroni correction).

Within the ME/CFS sample, there were statistically significant differences between the hypersensitivity groups, F(30,6084) = 21.28, p<0.001, V = 0.29, ηp2= 0.095. Significant pairwise differences were determined between nearly every hypersensitivity group. However, there were no significant pairwise differences between the ‘noise only’ and ‘lights only’ hypersensitivity groups within any of the domains.

Within the MS sample, there were statistically significant differences between hypersensitivity groups, F(30,552) = 2.947, p<0.001, V = 0.414, ηp2= 0.14. Like the ME/CFS sample, there were no significant different pairwise differences between the ‘noise only’ and ‘lights only’ hypersensitivity groups.

Discussion

The current study assessed the prevalence and characteristics of both noise and lights hypersensitivities in adults with ME/CFS and adults with MS. The findings indicate that these symptoms are highly prevalent among people with ME/CFS, with nearly three quarters of the sample reporting at least one of these two symptoms. The results from the current study are consistent with previous studies on the prevalence rates of photophobia in patients with ME/CFS (Wilbarger & Cook, 2011). Additionally, participants with ME/CFS were more likely to experience both hypersensitivities than one alone, which is important for clinicians treating patients with ME/CFS. As symptoms appear together more frequently, it would be beneficial to have treatments that address both simultaneously. The participants with MS were less likely to experience both hypersensitivities, serving as a possible differentiating criterion between ME/CFS and MS.

Moreover, the analyses revealed the impacts noise and lights hypersensitivities have on domains of functioning. Participants of both illnesses who reported both noise and lights hypersensitivities were more impaired from those with none across all DSQ and SF-36 subscales, indicating a greater severity of dysfunction in those experiencing both symptoms. People have reported significant distress due to these symptoms, and the findings from this study suggest that this distress is compounded by experiencing both symptoms (Aazh et al., 2016; Cortez et al., 2019). The manifestation of both hypersensitivities can be a good indicator of overall dysfunction that physicians can use to get an accurate overall sense of a patient’s illness.

There was a notable lack of statistical differences in DSQ and SF-36 subscales between participants with only noise hypersensitivities and those with only lights hypersensitivities. This suggests that regardless of the type of sensory information, these hypersensitivities impact functioning in similar ways, potentially illustrating the biological mechanisms of these symptoms. One possible explanation can be found in the salience network of the brain, which is responsible for directing attention towards sensory stimuli (Menon & Uddin, 2010). As an example of the importance of the salience network, dysfunctions in this insular network have been associated with sensory over-responsivity in hyperacusis, an illness defined by an abnormal auditory intolerance to noise (Baguley, 2003; Han et al., 2018). There are also findings of aberrances in the salience network of people with ME/CFS which can have impacts on other symptoms of ME/CFS, such as fatigue and pain intensity (Wortinger et al., 2016). This may be the source of the functional similarities between those experiencing noise and lights hypersensitivities. Further research can shed light on this correlation and allow for a better understanding of the neuroanatomical mechanisms of ME/CFS.

The current study had several limitations. As described before, the assessments of noise and lights hypersensitivities were derived from self-report measures rather than direct clinical testing. However, the DSQ has shown strong test-retest reliability on both the ‘sensitivity to noise’ item, r=0.88, p<0.001, and the ‘sensitivity to bright lights’ item, r=0.83, p<0.001 (Jason et al., 2015). The DSQ has also shown strong construct validity (Strand et al., 2016), and so classifying responses based on higher scores on hypersensitivity to noise and hypersensitivity to bright lights is a reasonable definition to make. However, further studies of hypersensitivities to noise and lights in ME/CFS and MS should be conducted using clinical assessments.

Another limitation of the study was the wide variability in the samples used for the study. The samples were aggregated from multiple sources with inconsistencies in patient recruitment and assessment methods. Some samples had patients with ME/CFS complete full medical reviews recruited from tertiary care settings (e.g., Spain sample), while other samples had participants self-report their diagnoses (e.g., DePaul sample). However, these recruitment and assessment methods increased the generalizability of the findings. The overall ME/CFS sample is nearly 12 times larger than the MS sample which can lead to overestimated significance results. To account for this, statistical methods such as Cramer’s V and Bonferroni adjustments were used. The findings from the study also prompt further investigation with other chronic diseases that share symptomatology with ME/CFS, such as Long COVID (Wong, 2021). While the current study focused its comparative investigation on MS, future research should compare noise and lights hypersensitivities in Long COVID.

Conclusions

The current study found significant differences between those with noise and lights hypersensitivities and those without in both ME/CFS and MS. Of note are those with ME/CFS who reported experiencing both hypersensitivities as they experienced the strongest impacts across all symptom and functioning domains compared to those experiencing neither hypersensitivity. Based on recent estimates on the number of people living with ME/CFS in the United States alone (Jason & Mirin, 2021), there are approximately 756,000 people with ME/CFS in the United States experiencing both noise and lights hypersensitivities. As these symptoms can reach debilitating intensities, it is critical for healthcare providers to create more targeted treatments and services for those who experience hypersensitivities. Additionally, a more comprehensive understanding of hypersensitivities within ME/CFS may guide the development of a refined case definition for ME/CFS.

Funding Source:

This work was supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Grant R01NS111105.

Footnotes

Declaration of Interest:

The authors disclose no conflicts of interest.

Ethics approval:

All analyses performed with human participants in the current study were in accordance with the ethical standards of DePaul University’s Institutional Review Board. All participants were provided informed consent by their respective sources.

Data availability statement:

The data presented in this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data presented in this study are available from the corresponding author upon reasonable request.

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