Introduction
Multiple Sclerosis (MS) is a chronic autoimmune disease characterized by inflammatory demyelination within the central nervous system (CNS). It is the second leading cause of severe disability and poor quality of life (QoL) in young adults. Due to the diffuse involvement of the spinal cord and brain, MS causes a wide range of symptoms affecting sensory, motor, visual, and cognitive functions [ 1 – 3 ]. In addition to neurological symptoms, a broad spectrum of neuropsychiatric disorders (including depression, anxiety, schizophrenia, and BD) has been reported in people with MS (PwMS) [ 4 , 5 ]. These neuropsychiatric complications can negatively affect QoL, reduce medication adherence, accelerate disability progression, and worsen overall prognosis in PwMS [ 6 – 8 ].
Bipolar disorders (BD) are a spectrum of chronic mood disorders that include two types. BD type 1 (BD I) is defined by the presence of a complete manic episode, while BD type 2 (BD II) involves a hypomanic phase along with a major depressive episode [ 9 , 10 ]. BD can exist across a wide range of neurological diseases, including dementia, MS, autoimmune encephalitis, Alzheimer’s disease, Parkinson’s disease, and epilepsy [ 11 ]. Although the primary cause of BD is not fully understood, numerous factors, such as disruptions in neuronal-glial plasticity, monoaminergic signaling, inflammatory balance, and cellular metabolism, have been implicated in its pathophysiology. Notably, MS and BD exhibit white matter (WM) abnormalities; in BD, diffusion changes are often seen in the right posterior temporoparietal and left cingulate regions [ 12 ]. The neuropathology of the brain in BD varies, including aberrant myelin and axonal packing, as well as neuronal and axonal losses resulting in reduced neuronal populations. This can lead to the loss of synaptic terminals and dendrites, resulting in the dysfunction of neural circuits that regulate mood and behavior [ 13 ].
In PwMS, BD is associated with reduced medication adherence and worse QoL. Moreover, overlapping symptoms and the effects of disease-modifying therapies may complicate the diagnosis of BD [ 14 ]. Previous studies have indicated a considerable variation in the prevalence of BD in PwMS, ranging from 0% to 16.2% [ 12 , 15 ]. Moreover, the overall association between MS and BD remains understudied. However, the comorbidity of BD and MS is highly significant from both psychological and neurological perspectives in terms of selecting appropriate treatments and outcomes [ 16 ]. This systematic review and meta-analysis aimed to provide a pooled estimate of BD prevalence among PwMS and explore the potential association between MS and BD risk.
Methods
Study design
This systematic review and meta-analysis was carried out under the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 17 ]. This study is registered in PROSPERO (Registration ID: CRD420251027938).
Search strategy
PubMed, Scopus, Web of Science, and Embase were systematically searched for relevant articles published up to January 1, 2025. We also searched the reference lists of relevant studies randomly and used Google Scholar to identify any further relevant papers. The search strategy incorporated relevant MeSH terms related to multiple sclerosis and bipolar disorder, which were customized for the specific databases used. Additional relevant article references were manually reviewed for further relevant papers. Supplementary Material 1 , Table S1 presents the details of the search strategy.
Study selection
The title and abstract eligibility were independently evaluated by two reviewers (ASH and SV). References were managed using EndNote software (version X21). We obtained the full text of all studies that appeared to meet the inclusion criteria or had unclear eligibility from the initial screening. Any disagreements were resolved by consultation with a third reviewer (OM) until consensus was reached.
Inclusion and exclusion criteria
Studies meeting predefined criteria were considered for inclusion in this review, needed to be (1) published in English in a peer-reviewed journal; (2) used a cross-sectional, case-control, or cohort design; (3) enrolled adult participants (≥ 18 years old) with a confirmed MS diagnosis (based on established criteria [ 18 – 22 ] or documented in a hospital/registry database); and (4) reported data on the prevalence of BD (or sufficient data to determine it) in the MS sample. Articles in languages other than English, in vitro and animal studies, case reports, case series, letters, conference abstracts, review articles, protocols, and editorials were excluded.
Data extraction
Two reviewers (SV and MYP) extracted the articles’ data separately. The data related to study characteristics (first author, country, publication year, study design, and total number of participants) and demographic details of MS patients (mean age, sex, sample size of PwMS and BD, type of MS, Expanded Disability Status Scale (EDSS) scores, types of BD, duration of disease) and diagnostic details of BD (e.g., DSM criteria) were extracted.
Risk of bias assessment
The risk of bias (ROB) was assessed using the Newcastle–Ottawa Scale (NOS) [ 23 ]. This checklist evaluated the quality of the included articles based on three criteria: comparability, selection, and outcome. Two reviewers (ASH and MYP) independently assessed each study, with any disagreements resolved by a third reviewer (OM). More information about the ROB assessment is presented in Table 1 .
Statistical analysis
We meta-analyzed three types of effect size outcomes: the prevalence of BD in PwMS, the odds ratio (OR) of BD in PwMS, and the hazard ratio (HR) of BD in PwMS, each reported with a 95% confidence interval (CI). In cases where multiple studies appeared to use overlapping populations, the study with the most inclusive data, or the most recent publication was included in the meta-analysis. The remaining overlapping studies were remained in the systematic review for qualitative synthesis. For the meta-analysis, random-effects models were used to synthesize effect sizes, accounting for potential methodological heterogeneity across studies. Forest plots were utilized to present the pooled estimates and to visualize the extent of variability among the included studies. Statistical heterogeneity was evaluated using the Cochran’s Q test and the I² statistic [ 24 ]. Potential sources of heterogeneity were examined through subgroup analysis, meta-regression, and sensitivity analysis. Subgroup analysis and meta-regression were conducted, where applicable. Sensitivity analyses were performed to evaluate the robustness of the pooled effect size and detect studies with a potentially disproportionate effect [ 25 ]. Publication bias was assessed using visual inspection of funnel plots [ 26 ], complemented by Begg’s and Egger’s tests [ 27 , 28 ]. Statistical analyses were performed using R (version 4.4.0) and the “meta” package, considering a significance threshold of p < 0.05.
Results
Study selection
Figure 1 provides a comprehensive overview of the study selection process. The initial search yielded 4900 studies, and after eliminating duplicates, 3059 records were left. A screening of the titles and abstracts resulted in the selection of 106 studies for full-text evaluation. Among these, 41 studies met the inclusion criteria.
Fig. 1 PRISMA 2020 flow diagram of the study process. This diagram summarizes the identification, screening, eligibility, and inclusion stages of the review process
Study characteristics
Table 1 presents the main characteristics and key outcomes of the included studies. In total, 219,886 PwMS (71.7% female), with a mean (SD) age of 46.5 (9.0) years, disease duration of 7.3 (5.3) years, and EDSS score of 2.2 (1.8), as well as 7,523,553 healthy controls (HCs) (50.4% female) with a mean (SD) age of 42.9 (14.1) years, were included. The studies were published between 1986 and 2024, primarily conducted in Canada ( n = 15) [ 29 – 43 ], Italy ( n = 7) [ 44 – 50 ], UK ( n = 4) [ 51 – 54 ], USA ( n = 3) [ 14 – 56 ], Turkey ( n = 3) [ 5 , 57 , 58 ], Sweden ( n = 2) [ 59 , 60 ], Taiwan ( n = 2) [ 61 , 62 ] and one study each from Israel [ 63 ], Spain [ 64 ], Australia [ 65 ], Brazil [ 66 ], and Mexico [ 67 ].
Table 1 The principal characteristics of the included studies First Author/ Year/ Country Study Design PwMS/ F: M/ Age; mean (SD) MS Type ( n ) EDSS; Mean (SD) Disease Duration (years); Mean (SD) Types of BD ( n ) in PwMS Diagnostic Assessment of BD HC/ F: M/ Age; mean (SD) Types of BD ( n ) in HC Major Findings QA L. Pangan Lo 2020 Australia [ 66 ] Cross-sectional 1518 1204:309 55.7 (11.2) RRMS: 1113 PPMS: 150 NR NR BD: 19 Data Registry NR NR BD is common at MS symptom onset and increase with MS duration. 8 A. de Cerqueira 2015 Brazil [ 67 ] Cross-sectional 60 46:14 43 (11.8) RRMS: 49 PMS: 11 2.9 (2.2) 9.6 (6.8) Hipomania: 6 Mania: 2 DSM-4 NR NR NR 5 R. Marrie 2021 Canada [ 29 ] Case-control 6158 4322:1836 42.1 (13.5) NR NR 13.9 (6.2–22.5)** BD: 368 ICD-10 30,690 21564:9126 42.1 (13.5) BD: 1158 The increased incidence of BD in PwMS versus matched HCs was seen. 9 R. Marrie 2020 Canada [ 30 ] Case-control 4748 3399:1349 40.2 (11.9) NR NR NR BD: 65 ICD-10 24,154 17247:6907 40.9 (12.2) BD: 250 Within PwMS, changes in mood disorders activity are associated with changes in health services use. 8 R. Marrie 2018 Canada [ 31 ] Case-control 3514 2544:970 40.8 (12.5) NR NR 10.3 (4.9–16.1)** NR DSM-4 17,526 12697:4829 40.8 (12.5) NR The increased incidence of BD in PwMS versus matched HCs was seen. 9 R. Marrie 2018 Canada [ 32 ] Case-control 5496 3509:1987 42.1 (13.4) NR NR 12.8 (6.1–20.8)** BD:142 ICD-10 27,354 19465:7889 42.1 (13.4) BD: 493 BD is associated with increased risk of MS. 9 K. McKay 2018 Canada [ 33 ] Cohort 2312 1751:561 36.9 (13.6) RRMS: 2133 PPMS: 179 2 (1.5–3)* 2.7 (2.6) BD: 119 Data Registry NR NR BD was common in PwMS. 8 B. Gerber 2017 Canada [ 34 ] Cohort 2864 2114:750 45 (6) NR NR NR BD: 136 NR NR NR A high prevalence of BD was reported in PwMS. 7 R. Marrie 2016 Canada [ 35 ] Case-control 9624 6635:2989 42.9 (13.3) NR NR NR NR NR 41,194 27595:13599 42.8 (13.3) NR The risk of BD was higher in the MS population than the matched population. 9 R. Marrie 2016 Canada [ 36 ] Case-control 23,382 16803:6579 44 (14.1) NR NR NR BD: 736 NR 116,638 77674:38964 44 (14.1) BD: 1973 PwMS had a higher prevalence of BD than HCs. 8 L. Berrigan 2016 Canada [ 37 ] Cohort 949 714:235 48.6 (11.4) RRMS: 687 SPMS: 193 PPMS: 60 CIS: 5 Unknown: 3 2.5 (3.5) 15.4 (10.2) BD: 13 DSM-4 NR NR Increased bipolar symptoms is associated with decreased QoL in PwMS. 8 R. Marrie 2015 Canada [ 38 ] Case-control 5797 4140:1657 41.4 (13.6) NR NR NR BD: 142 ICD-9 28,807 20,566: 8241 41.5 (13.6) BD: 427 Bipolar disorder was associated with an increased hazard of death in in the HCs population but not in PwMS. 8 R. Marrie 2014 Canada [ 39 ] Case-control 4875 3498:1377 40.2 (12) NR NR NR BD: 402 ICD-10 24,533 17570:6963 40.5 (12.2) BD: 1177 BD was associated with higher hospitalization rates in MS populations. 7 R. Marrie 2013 Canada [ 40 ] Case-control 4192 3005:1187 33.2 (11.1) NR NR NR BD: 244 ICD-10 20,940 15013:5927 NR BD: 720 BD was associated with higher hospitalization rates in MS populations. 7 R. Marrie 2009 Canada [ 41 ] Cross-sectional 8983 6809:2174 52.7 (10.4) NR NR NR BD: 213 Data registry NR NR BD in PwMS was more frequent than reported for the HCs. 8 A. Feinstein Canada 2001 [ 42 ] Cross-sectional 100 69:31 44.6 (11.4) RRMS: 40 PMS: 60 4.9 (2.6) 8.8 (6.8) BD: 0 DSM-4 NR NR NR 5 R. Joffe 1986 Canada [ 43 ] Cohort 100 63:37 42.3 (13) NR NR NR BD: 13 RDC NR NR A high prevalence of BD was reported in PwMS. 4 U. Blasbalg 2024 Israel [ 64 ] Case-control 9533 NR NR NR NR BD: 65 ICD-10 28,599 NR BD: 84 BD is more common in PwMS than HCs. 7 L. Lorefice 2018 Italy [ 44 ] Cross-sectional 101 76:25 44 (10) RRMS: 101 3.4 (1.8) 9.5 (6.1) BD: 4 DSM-4 NR NR The prevalence of BD is high in PwMS. 7 A. Laroni 2017 Italy [ 45 ] Cohort 1877 1218:659 35.3 (11.3) NR 2.1 (1.1) NR BD: 11 Data Registry NR NR Comorbidities like BD at diagnosis should be taken into account at the first treatment. 8 L. Lorefice 2015 Italy [ 46 ] Cross-sectional 240 167:73 40.6 (9.7) RRMS: 195 SPMS: 15 PPMS: 30 3.5 (1.7) 10.9 (7.3) Type 1: 5 Type 2: 29 Cyclothymic:6 Other: 6 DSM-4 NR NR NR 7 M. Carta 2014 Italy [ 47 ] Case-control 201 140:61 38.9 (10) NR NR NR Type 1: 2 Type 2: 15 DSM-4 804 560:244 38.8 (10.1) Type 1: 0 Type 2: 2 This study indicated a higher association with BD and MS. 7 M. Carta 2014 Italy [ 48 ] Case-control 201 140:61 38.9 (10) NR NR NR Type 1: 2 Type 2: 15 Cyclothymic: 3 Other: 4 DSM-4 804 560:244 38.9 (10) Type 1: 0 Type 2: 2 Cyclothymic: 0 Other: 0 BD in PwMS was more common than reported for the HCs. 7 S. Lo Fermo 2010 Italy [ 49 ] Cross-sectional 682 NR NR NR NR NR BD: 1 DSM-4 NR NR NR 5 G. Galeazzi 2005 Italy [ 50 ] Case-control 50 26:24 34.9 (9) RRMS: 50 2.3 (0.9) 10 (6) Type 1: 1 Type 2: 1 Cyclothymic: 1 DSM-4 50 27:23 33.7 (8.7) Type 1: 1 The prevalence of BD in PwMS was found to be 13 times higher than in the HCs. 6 M. Nadurille 2010 Mexico [ 68 ] Case-control 37 24:13 36.3 (11.5) RRMS: 28 SPMS: 7 PPMS: 2 4.5 (1.9) 7 (6.4) Type 1: 1 Type 2: 5 DSM-4 37 22:15 39.8 (11.5) BD: 0 BD in PwMS was more common than reported for the HCs. 6 V. Johansson 2014 Sweden [ 59 ] Cohort 16,467 NR NR NR NR NR ICD-10 NR NR The study found a strong positive association between MS and BD. 7 P. Brenner 2014 Sweden [ 61 ] Case-control 10,750 7607:3143 47 (11) NR NR NR BD: 51 ICD-10 5,553,141 2733897:2819244 41 (13.6) BD: 12,072 BD in PwMS was more common than reported for the HCs. 9 Y. Huang 2021 Taiwan [ 62 ] Case-control 1066 856:210 42.1 (13.1) NR NR NR BD: 5 ICD-9 3198 2568:630 40.9 (14.7) NR PwMS were determined to have a higher risk of BD. 7 L. Wang 2017 Taiwan [ 63 ] Case-control 1060 NR NR NR NR BD: 4 DSM-4 261,992 NR NR NR NR 7 V. Kotan 2019 Turkey [ 57 ] Cross-sectional 227 163:64 37 (9.9) RRMS: 158 PPMS: 20 PRMS: 9 SPMS: 7 CIS: 33 NR 6.8 (3.5) BD: 4 DSM-4 NR NR The prevalence of BD is high in PwMS. 6 A. Uca Turkey 2016 [ 5 ] Case-control 55 47:8 34 (8.1) RRMS: 55 2.2 (1.5) 6.2 (4.3) BD: 0 DSM-4 56 49:7 36.1 (10.4) BD: 0 NR 4 F. Uguz 2008 Turkey [ 60 ] Cross-sectional 74 50:24 34.5 (11.9) RRMS: 74 1.4 (1.2) 5.4 (4.8) BD: 1 DSM-4 NR NR PwMS, particularly during exacerbation phase have high prevalence of BD. 5 U. Meier 2020 UK [ 51 ] Cohort 128,194 NR NR NR NR BD: 531 Data Registry NR NR Bipolar disorder may be identified as a potential shared risk factor for MS. 7 R. Simpson 2014 UK [ 52 ] Case-control 3826 2767:1059 53.4 (12.8) NR NR NR NR NR 1,268,859 647836:621023 51.2 (16.6) NR Bipolar had a similar risk in PwMS and HCs. 7 L. Edwards 2004 UK [ 53 ] Case-control 658 454:204 45 (18–80) B NR NR NR BD: 2 Data registry 72,238 NR BD: 10 BD in PwMS was more frequent than reported for the HCs. 8 M. Ron UK 1989 [ 54 ] Case-control 116 79:37 38.8 (23–67) a NR NR NR BD: 6 DSM-3 48 30:18 38.9 (20–68) a BD: 1 BD in PwMS was more frequent than reported for the HCs. 3 A. Connell 2017 USA [ 55 ] Cross-sectional 152 114:38 51.4 (15.7) RRMS: 125 PPMS: 4 SPMS: 24 NR 1 (3)** Type 1: 6 Type 2: 3 Other type: 1 DSM-4 NR NR BD may increase the risk of MS. 8 M. Horton 2010 USA [ 56 ] Cross-sectional 404 307:97 46.5 (11.8) RRMS: 286 SPMS: 65 PPMS: 31 CIS: 10 NR: 12 1 (0–4)** 13.9 (10.1) BD: 3 DSM-4 NR NR NR 5 G. Demakis 2009 USA [ 58 ] Cohort 924 665:259 57.5 (13.5) NR NR NR BD: 21 NR NR NR NR 7 *Median (Range), **Median (IQR), β Mean (Range), z Z-score, BD – Bipolar Disorder, EDSS – Expanded disability status Scale, MS – multiple Sclerosis, PwMS – People with multiple Sclerosis, ICD – International classification of Diseases, DSM – diagnostic and statistical manual of mental Disorders, HCs – Healthy Controls, RRMS – Relapsing-Remitting multiple Sclerosis, PPMS – Primary progressive multiple Sclerosis, SPMS – Secondary progressive multiple Sclerosis, CIS – Clinically isolated Syndrome, RDC – Research diagnostic criteria
Table 1
The principal characteristics of the included studies
*Median (Range), **Median (IQR), β Mean (Range), z Z-score, BD – Bipolar Disorder, EDSS – Expanded disability status Scale, MS – multiple Sclerosis, PwMS – People with multiple Sclerosis, ICD – International classification of Diseases, DSM – diagnostic and statistical manual of mental Disorders, HCs – Healthy Controls, RRMS – Relapsing-Remitting multiple Sclerosis, PPMS – Primary progressive multiple Sclerosis, SPMS – Secondary progressive multiple Sclerosis, CIS – Clinically isolated Syndrome, RDC – Research diagnostic criteria
| First Author/ Year/ Country | Study Design | PwMS/ F: M/ Age; mean (SD) | MS Type ( n ) | EDSS; Mean (SD) | Disease Duration (years); Mean (SD) | Types of BD ( n ) in PwMS | Diagnostic Assessment of BD | HC/ F: M/ Age; mean (SD) | Types of BD ( n ) in HC | Major Findings | QA |
| L. Pangan Lo 2020 Australia [ 66 ] | Cross-sectional | 1518 1204:309 55.7 (11.2) | RRMS: 1113 PPMS: 150 | NR | NR | BD: 19 | Data Registry | NR | NR | BD is common at MS symptom onset and increase with MS duration. | 8 |
| A. de Cerqueira 2015 Brazil [ 67 ] | Cross-sectional | 60 46:14 43 (11.8) | RRMS: 49 PMS: 11 | 2.9 (2.2) | 9.6 (6.8) | Hipomania: 6 Mania: 2 | DSM-4 | NR | NR | NR | 5 |
| R. Marrie 2021 Canada [ 29 ] | Case-control | 6158 4322:1836 42.1 (13.5) | NR | NR | 13.9 (6.2–22.5)** | BD: 368 | ICD-10 | 30,690 21564:9126 42.1 (13.5) | BD: 1158 | The increased incidence of BD in PwMS versus matched HCs was seen. | 9 |
| R. Marrie 2020 Canada [ 30 ] | Case-control | 4748 3399:1349 40.2 (11.9) | NR | NR | NR | BD: 65 | ICD-10 | 24,154 17247:6907 40.9 (12.2) | BD: 250 | Within PwMS, changes in mood disorders activity are associated with changes in health services use. | 8 |
| R. Marrie 2018 Canada [ 31 ] | Case-control | 3514 2544:970 40.8 (12.5) | NR | NR | 10.3 (4.9–16.1)** | NR | DSM-4 | 17,526 12697:4829 40.8 (12.5) | NR | The increased incidence of BD in PwMS versus matched HCs was seen. | 9 |
| R. Marrie 2018 Canada [ 32 ] | Case-control | 5496 3509:1987 42.1 (13.4) | NR | NR | 12.8 (6.1–20.8)** | BD:142 | ICD-10 | 27,354 19465:7889 42.1 (13.4) | BD: 493 | BD is associated with increased risk of MS. | 9 |
| K. McKay 2018 Canada [ 33 ] | Cohort | 2312 1751:561 36.9 (13.6) | RRMS: 2133 PPMS: 179 | 2 (1.5–3)* | 2.7 (2.6) | BD: 119 | Data Registry | NR | NR | BD was common in PwMS. | 8 |
| B. Gerber 2017 Canada [ 34 ] | Cohort | 2864 2114:750 45 (6) | NR | NR | NR | BD: 136 | NR | NR | NR | A high prevalence of BD was reported in PwMS. | 7 |
| R. Marrie 2016 Canada [ 35 ] | Case-control | 9624 6635:2989 42.9 (13.3) | NR | NR | NR | NR | NR | 41,194 27595:13599 42.8 (13.3) | NR | The risk of BD was higher in the MS population than the matched population. | 9 |
| R. Marrie 2016 Canada [ 36 ] | Case-control | 23,382 16803:6579 44 (14.1) | NR | NR | NR | BD: 736 | NR | 116,638 77674:38964 44 (14.1) | BD: 1973 | PwMS had a higher prevalence of BD than HCs. | 8 |
| L. Berrigan 2016 Canada [ 37 ] | Cohort | 949 714:235 48.6 (11.4) | RRMS: 687 SPMS: 193 PPMS: 60 CIS: 5 Unknown: 3 | 2.5 (3.5) | 15.4 (10.2) | BD: 13 | DSM-4 | NR | NR | Increased bipolar symptoms is associated with decreased QoL in PwMS. | 8 |
| R. Marrie 2015 Canada [ 38 ] | Case-control | 5797 4140:1657 41.4 (13.6) | NR | NR | NR | BD: 142 | ICD-9 | 28,807 20,566: 8241 41.5 (13.6) | BD: 427 | Bipolar disorder was associated with an increased hazard of death in in the HCs population but not in PwMS. | 8 |
| R. Marrie 2014 Canada [ 39 ] | Case-control | 4875 3498:1377 40.2 (12) | NR | NR | NR | BD: 402 | ICD-10 | 24,533 17570:6963 40.5 (12.2) | BD: 1177 | BD was associated with higher hospitalization rates in MS populations. | 7 |
| R. Marrie 2013 Canada [ 40 ] | Case-control | 4192 3005:1187 33.2 (11.1) | NR | NR | NR | BD: 244 | ICD-10 | 20,940 15013:5927 NR | BD: 720 | BD was associated with higher hospitalization rates in MS populations. | 7 |
| R. Marrie 2009 Canada [ 41 ] | Cross-sectional | 8983 6809:2174 52.7 (10.4) | NR | NR | NR | BD: 213 | Data registry | NR | NR | BD in PwMS was more frequent than reported for the HCs. | 8 |
| A. Feinstein Canada 2001 [ 42 ] | Cross-sectional | 100 69:31 44.6 (11.4) | RRMS: 40 PMS: 60 | 4.9 (2.6) | 8.8 (6.8) | BD: 0 | DSM-4 | NR | NR | NR | 5 |
| R. Joffe 1986 Canada [ 43 ] | Cohort | 100 63:37 42.3 (13) | NR | NR | NR | BD: 13 | RDC | NR | NR | A high prevalence of BD was reported in PwMS. | 4 |
| U. Blasbalg 2024 Israel [ 64 ] | Case-control | 9533 NR | NR | NR | NR | BD: 65 | ICD-10 | 28,599 NR | BD: 84 | BD is more common in PwMS than HCs. | 7 |
| L. Lorefice 2018 Italy [ 44 ] | Cross-sectional | 101 76:25 44 (10) | RRMS: 101 | 3.4 (1.8) | 9.5 (6.1) | BD: 4 | DSM-4 | NR | NR | The prevalence of BD is high in PwMS. | 7 |
| A. Laroni 2017 Italy [ 45 ] | Cohort | 1877 1218:659 35.3 (11.3) | NR | 2.1 (1.1) | NR | BD: 11 | Data Registry | NR | NR | Comorbidities like BD at diagnosis should be taken into account at the first treatment. | 8 |
| L. Lorefice 2015 Italy [ 46 ] | Cross-sectional | 240 167:73 40.6 (9.7) | RRMS: 195 SPMS: 15 PPMS: 30 | 3.5 (1.7) | 10.9 (7.3) | Type 1: 5 Type 2: 29 Cyclothymic:6 Other: 6 | DSM-4 | NR | NR | NR | 7 |
| M. Carta 2014 Italy [ 47 ] | Case-control | 201 140:61 38.9 (10) | NR | NR | NR | Type 1: 2 Type 2: 15 | DSM-4 | 804 560:244 38.8 (10.1) | Type 1: 0 Type 2: 2 | This study indicated a higher association with BD and MS. | 7 |
| M. Carta 2014 Italy [ 48 ] | Case-control | 201 140:61 38.9 (10) | NR | NR | NR | Type 1: 2 Type 2: 15 Cyclothymic: 3 Other: 4 | DSM-4 | 804 560:244 38.9 (10) | Type 1: 0 Type 2: 2 Cyclothymic: 0 Other: 0 | BD in PwMS was more common than reported for the HCs. | 7 |
| S. Lo Fermo 2010 Italy [ 49 ] | Cross-sectional | 682 NR NR | NR | NR | NR | BD: 1 | DSM-4 | NR | NR | NR | 5 |
| G. Galeazzi 2005 Italy [ 50 ] | Case-control | 50 26:24 34.9 (9) | RRMS: 50 | 2.3 (0.9) | 10 (6) | Type 1: 1 Type 2: 1 Cyclothymic: 1 | DSM-4 | 50 27:23 33.7 (8.7) | Type 1: 1 | The prevalence of BD in PwMS was found to be 13 times higher than in the HCs. | 6 |
| M. Nadurille 2010 Mexico [ 68 ] | Case-control | 37 24:13 36.3 (11.5) | RRMS: 28 SPMS: 7 PPMS: 2 | 4.5 (1.9) | 7 (6.4) | Type 1: 1 Type 2: 5 | DSM-4 | 37 22:15 39.8 (11.5) | BD: 0 | BD in PwMS was more common than reported for the HCs. | 6 |
| V. Johansson 2014 Sweden [ 59 ] | Cohort | 16,467 NR | NR | NR | NR | NR | ICD-10 | NR | NR | The study found a strong positive association between MS and BD. | 7 |
| P. Brenner 2014 Sweden [ 61 ] | Case-control | 10,750 7607:3143 47 (11) | NR | NR | NR | BD: 51 | ICD-10 | 5,553,141 2733897:2819244 41 (13.6) | BD: 12,072 | BD in PwMS was more common than reported for the HCs. | 9 |
| Y. Huang 2021 Taiwan [ 62 ] | Case-control | 1066 856:210 42.1 (13.1) | NR | NR | NR | BD: 5 | ICD-9 | 3198 2568:630 40.9 (14.7) | NR | PwMS were determined to have a higher risk of BD. | 7 |
| L. Wang 2017 Taiwan [ 63 ] | Case-control | 1060 NR | NR | NR | NR | BD: 4 | DSM-4 | 261,992 NR NR | NR | NR | 7 |
| V. Kotan 2019 Turkey [ 57 ] | Cross-sectional | 227 163:64 37 (9.9) | RRMS: 158 PPMS: 20 PRMS: 9 SPMS: 7 CIS: 33 | NR | 6.8 (3.5) | BD: 4 | DSM-4 | NR | NR | The prevalence of BD is high in PwMS. | 6 |
| A. Uca Turkey 2016 [ 5 ] | Case-control | 55 47:8 34 (8.1) | RRMS: 55 | 2.2 (1.5) | 6.2 (4.3) | BD: 0 | DSM-4 | 56 49:7 36.1 (10.4) | BD: 0 | NR | 4 |
| F. Uguz 2008 Turkey [ 60 ] | Cross-sectional | 74 50:24 34.5 (11.9) | RRMS: 74 | 1.4 (1.2) | 5.4 (4.8) | BD: 1 | DSM-4 | NR | NR | PwMS, particularly during exacerbation phase have high prevalence of BD. | 5 |
| U. Meier 2020 UK [ 51 ] | Cohort | 128,194 NR | NR | NR | NR | BD: 531 | Data Registry | NR | NR | Bipolar disorder may be identified as a potential shared risk factor for MS. | 7 |
| R. Simpson 2014 UK [ 52 ] | Case-control | 3826 2767:1059 53.4 (12.8) | NR | NR | NR | NR | NR | 1,268,859 647836:621023 51.2 (16.6) | NR | Bipolar had a similar risk in PwMS and HCs. | 7 |
| L. Edwards 2004 UK [ 53 ] | Case-control | 658 454:204 45 (18–80) B | NR | NR | NR | BD: 2 | Data registry | 72,238 NR | BD: 10 | BD in PwMS was more frequent than reported for the HCs. | 8 |
| M. Ron UK 1989 [ 54 ] | Case-control | 116 79:37 38.8 (23–67) a | NR | NR | NR | BD: 6 | DSM-3 | 48 30:18 38.9 (20–68) a | BD: 1 | BD in PwMS was more frequent than reported for the HCs. | 3 |
| A. Connell 2017 USA [ 55 ] | Cross-sectional | 152 114:38 51.4 (15.7) | RRMS: 125 PPMS: 4 SPMS: 24 | NR | 1 (3)** | Type 1: 6 Type 2: 3 Other type: 1 | DSM-4 | NR | NR | BD may increase the risk of MS. | 8 |
| M. Horton 2010 USA [ 56 ] | Cross-sectional | 404 307:97 46.5 (11.8) | RRMS: 286 SPMS: 65 PPMS: 31 CIS: 10 NR: 12 | 1 (0–4)** | 13.9 (10.1) | BD: 3 | DSM-4 | NR | NR | NR | 5 |
| G. Demakis 2009 USA [ 58 ] | Cohort | 924 665:259 57.5 (13.5) | NR | NR | NR | BD: 21 | NR | NR | NR | NR | 7 |
Risk of bias
Table 1 summarizes the NOS-based quality assessments of the included studies. Of these, one study scored below 4, 10 studies scored between 4 and 6, while 30 studies scored above 6. The mean (SD) quality score was 7 (1.5), reflecting an overall moderate to high study quality.
Data synthesis
Meta-analysis on 27 studies with 187,004 PwMS indicated that the pooled prevalence of BD in PwMS was 3.2% (95% CI: 1.8% to 4.6%, I 2 = 97%, p -heterogeneity < 0.01) (Fig. 2 ).
Fig. 2 Forest plot of meta-analysis of pooled prevalence of BD in PwMS. The overall pooled prevalence of BD in PwMS was 3.2% (95% CI: 1.8% to 4.6%)
Subgroup analysis was conducted on various variables. Considering sample size, the pooled prevalence of BD among PwMS was 1.7% in studies with more than 1,000 participants, compared to 4.8% in studies with fewer than 1,000 participants ( p -value for difference = 0.02). Continent-wise, the pooled prevalence of BD among PwMS was 0.6% in Asia, 4.1% in Europe, and 4.2% in America ( p -value for difference < 0.01). Accounting for BD diagnostic criteria, the pooled prevalence of BD among PwMS was 4.6%, 1.5%, and 0.6% when diagnosed by Document Management Systems (DMS), data registries, and the International Classification of Diseases (ICD), respectively ( p -value for difference < 0.01). The pooled prevalence was 4.8% among a combination of RRMS and PMS patients, while it was 1.8% in RRMS patients ( p -value for difference = 0.11). Based on study design, pooled prevalence was 3.7%, 3.1%, and 3% in cross-sectional, cohort, and case-control studies, respectively ( p -value for difference = 0.93). More details of subgroup analyses are presented in Table 2 .
Table 2 Results of subgroup analysis of pooled prevalence of bipolar disorder among people with multiple sclerosis Variable of Subgroup Analysis Categories of Variable N . of Studies N . of Patients Pooled Prevalence 95% Confidence Interval I 2 P for Heterogeneity P for Difference* Overall - 27 187,004 3.2% 1.8% to 4.6% 97% < 0.01 - Continent Asia 6 12,015 0.6% 0.4% to 0.8% 0 0.42 < 0.01 Europe 10 143,705 4.1% 1% to 7.2% 90% < 0.01 America 11 31,284 4.2% 2.1% to 6.3% 92% < 0.01 Sample Size More than 1000 PwMS 10 182,556 1.7% 0.6% to 2.8% 99% < 0.01 0.02 Less than 1000 PwMS 17 4448 4.8% 2.4% to 7.2% 87% < 0.01 Diagnostic Criteria of BD ICD 3 21,349 0.6% 0.4% to 0.7% 49% 0.14 < 0.01 DSM 15 3826 4.6% 2% to 7.1% 87% < 0.01 Data Registry 5 134,559 1.5% 0 to 3.3% 97% < 0.01 MS Subtype RRMS + PMS 11 8863 4.8% 1.9% to 7.7% 94% < 0.01 0.11 RRMS 4 280 1.8% 0 to 3.9% 38% 0.18 Study Design Cross-sectional 10 2931 3.7% 0.7% to 6.7% 85% < 0.01 0.93 Case-control 10 46,853 3% 0.6% to 5.4% 98% < 0.01 Cohort 7 137,220 3.1% 1% to 5.2% 98% < 0.01 * P -values are according to χ2 tests. Significant p -values are in bold. DMS: Diagnostic and Statistical Manual of Mental Disorders, ICD: International Classification of Diseases, PMS: progressive multiple sclerosis, RRMS: relapsing-remitting multiple sclerosis
Table 2
Results of subgroup analysis of pooled prevalence of bipolar disorder among people with multiple sclerosis
* P -values are according to χ2 tests. Significant p -values are in bold. DMS: Diagnostic and Statistical Manual of Mental Disorders, ICD: International Classification of Diseases, PMS: progressive multiple sclerosis, RRMS: relapsing-remitting multiple sclerosis
| Variable of Subgroup Analysis | Categories of Variable | N . of Studies | N . of Patients | Pooled Prevalence | 95% Confidence Interval | I 2 | P for Heterogeneity | P for Difference* |
| Overall | - | 27 | 187,004 | 3.2% | 1.8% to 4.6% | 97% | < 0.01 | - |
| Continent | Asia | 6 | 12,015 | 0.6% | 0.4% to 0.8% | 0 | 0.42 | < 0.01 |
| Europe | 10 | 143,705 | 4.1% | 1% to 7.2% | 90% | < 0.01 | ||
| America | 11 | 31,284 | 4.2% | 2.1% to 6.3% | 92% | < 0.01 | ||
| Sample Size | More than 1000 PwMS | 10 | 182,556 | 1.7% | 0.6% to 2.8% | 99% | < 0.01 | 0.02 |
| Less than 1000 PwMS | 17 | 4448 | 4.8% | 2.4% to 7.2% | 87% | < 0.01 | ||
| Diagnostic Criteria of BD | ICD | 3 | 21,349 | 0.6% | 0.4% to 0.7% | 49% | 0.14 | < 0.01 |
| DSM | 15 | 3826 | 4.6% | 2% to 7.1% | 87% | < 0.01 | ||
| Data Registry | 5 | 134,559 | 1.5% | 0 to 3.3% | 97% | < 0.01 | ||
| MS Subtype | RRMS + PMS | 11 | 8863 | 4.8% | 1.9% to 7.7% | 94% | < 0.01 | 0.11 |
| RRMS | 4 | 280 | 1.8% | 0 to 3.9% | 38% | 0.18 | ||
| Study Design | Cross-sectional | 10 | 2931 | 3.7% | 0.7% to 6.7% | 85% | < 0.01 | 0.93 |
| Case-control | 10 | 46,853 | 3% | 0.6% to 5.4% | 98% | < 0.01 | ||
| Cohort | 7 | 137,220 | 3.1% | 1% to 5.2% | 98% | < 0.01 |
In addition to subgroup analysis, meta-regressions were conducted to examine the effect of numerical variables, including age, EDSS, and disease duration, on the results. Univariate meta-regression indicated that mean age (k = 24, β = -0.001, p -value = 0.41), EDSS (k = 12, β = 0.016, p -value = 0.26), disease duration (k = 12, β = 0.0001, p -value = 0.99), and female to male ration (k = 24, β = -0.008, p -value = 0.66) of PwMS and year of publication (k = 27, β = -0.001, p -value = 0.18) did not have a significant effect on the pooled prevalence.
Meta-analysis of five studies indicated that the pooled OR of BD among PwMS was 1.5 (95% CI: 1.1 to 2, p -value < 0.01, I 2 = 40%, p -heterogeneity = 0.15) (Fig. 3 ).
Fig. 3 Forest plot of meta-analysis of pooled OR of BD in PwMS. The pooled OR was 1.5 (95% CI: 1.1 to 2, p < 0.01), suggesting that PwMS have a moderately increased likelihood of developing BD relative to HCs
Based on the meta-analysis of four studies, the pooled HR of BD in PwMS was 2.5 (95% CI: 1.2 to 5.3, p -value = 0.02, I 2 = 99%, p -heterogeneity < 0.01) (Fig. 4 ).
Fig. 4 Forest plot of meta-analysis of pooled HR of BD in PwMS. The pooled HR was 2.5 (95% CI: 1.2 to 5.3, p = 0.02), indicating that PwMS have a two- to three-fold higher risk of developing BD than HCs
Publication bias
Begg’s and Egger’s tests, along with funnel plots, indicated no publication bias across the meta-analyses, except for the pooled prevalence of BD in PwMS (Begg’s p -value = 0.039, Egger’s p -value = 0.003 with a mild asymmetry observed in the funnel plot (Supplementary Material 2 , Figure S6 )). Detailed statistical findings are provided in Supplementary Material 2 .
Sensitivity analysis
Due to heterogeneity among the included studies, we conducted a sensitivity analysis to assess the robustness and reliability of the findings. The results revealed the exclusion of two studies in each of the pooled OR [ 59 , 64 ] and HR [ 35 , 60 ] altered the statistical significance of effect sizes. More details are provided in Supplementary Material 2.
Discussion
In this systematic review and meta-analysis, we estimated the pooled prevalence, risk, and odds of BD in PwMS. The analysis of 31 studies from three different continents on 219,886 PwMS showed that the overall prevalence of BD was 3.2% in PwMS, which is higher than the general population (between 1 and 2%) [ 68 ]. Furthermore, the HR and OR results supported each other, suggesting that PwMS likely have a higher risk and odds of developing bipolar disorder. However, due to the limited number of studies included in the OR and HR analyses, further population-based studies are warranted to verify these findings.
Another systematic review by Joseph et al. 2021 reported the prevalence of BD as 2.95% in PwMS. The slight difference with the current study is quite plausible, considering their smaller population of included patients compared to our study. Additionally, subgroup analysis based on continent and the population size of studies was performed to obtain a more accurate percentage and to examine existing differences [ 69 ]. More detailed analyses indicated that BD is more prevalent among PwMS in America and Europe than in Asia. However, the overall prevalence of BD in the general population of America and Europe also indicates higher rates than in Asia [ 70 ]. Both genetic factors and possibly more accurate diagnostic methods and screening tools have been reported as the possible reasons for the higher prevalence of BD in developed countries [ 71 ]. Moreover, environmental factors such as lower sunlight exposure at higher altitudes and lifestyle preferences in developed countries may explain the higher prevalence of BD in American communities [ 72 ]. In addition, the results of other studies confirm that genetic predisposition factors and psychological stressors make Americans and Europeans more susceptible to developing BD [ 73 , 74 ].
Neurological disability and psychological problems in PwMS have been linked with a lower QoL and more frequent flare-ups of MS [ 75 ]. Various factors, including the medications used for MS, the location of demyelinating lesions in the brain, genetics, and psychosocial factors, can influence the psychiatric comorbidities in PwMS [ 76 ]. These comorbidities can be associated with delayed diagnosis of MS, increased mortality risk, faster progression of MS, and an increased risk of MS-related disabilities [ 77 ].
Recent findings indicate that comparable mechanisms, including pro-inflammatory cytokines, microglial activation, anti-neuronal antibodies, molecular mimicry between brain antigens and pathogens, and disruptions to the blood-brain barrier, also play a role in the progression of psychiatric disorders like BD in PwMS [ 78 ]. Additionally, shared inflammatory cytokines, including IL-6, IL-1β, and TNF-α, pathological overactivation of microglia, and alterations in regulatory T cells have been reported as common contributing factors in the pathogenesis of both MS and BD [ 79 ]. A significant association between the family history of BD and the prevalence of BD in PwMS is also reported [ 80 ]. Although a single specific gene hadn’t been identified, HLA-DR2 is linked with both MS and BD. The reduction of HLA-DR1/DR4 also plays a role in the pathogenesis of BD in PwMS who have a positive family history of mood disorders [ 81 ].
The co-occurrence of MS and BD poses several clinical challenges. Since brain lesions in MS may lead to neuropsychiatric symptoms that can mimic primary mood disorders, distinguishing MS-related mood disturbances from primary BD is challenging. Although both conditions can result in mood instability, MS-related mood disorder is associated with neurological deficits, disease activity, or treatment failure. Additionally, the absence of new demyelinating lesions in the presence of mood symptoms may indicate the emergence of BD in PwMS [ 81 , 82 ]. Moreover, depressive episodes in patients with BD, especially bipolar type II, are often misdiagnosed as major depressive disorder (MDD). This can cause the recorded prevalence of BD to be underestimated, leading to mistreatment and its associated negative outcomes [ 83 ].
Although MRI findings cannot definitively distinguish MS lesions from those of BD, there are differences in the MRI lesions of these two diseases that can be practically helpful. MRI findings of MS include multiple confluent T2 hyperintense lesions in the white matter, corpus callosum, and oblongata-cervical spine transition, as well as in periventricular and subcortical regions. Additionally, during MS exacerbations, new demyelination lesions may be seen. In BD, imaging findings are more complex. Several studies have reported increased white matter and periventricular hyperintensities, while other studies have not reported significant changes in white matter [ 84 ]. Furthermore, a smaller volume of the putamen and nucleus has been reported in PwMS with BD compared to those without BD [ 85 , 86 ].
The treatment of BD in PwMS has several complications. Treatment with lithium (a mood stabilizer) may interact with MS medications, particularly corticosteroids, potentially triggering or worsening manic episodes. Furthermore, BD symptoms often reduce patient adherence to MS treatments, which can accelerate disease progression and exacerbate MS symptoms [ 14 , 81 ]. Therefore, careful monitoring of BD in PwMS during steroid therapy is necessary [ 81 ]. It is also recommended that the management of PwMS with BD should be individualized, considering each patient’s neurological status, psychiatric symptoms, and overall disease severity and disability burden.
Limitation
The strength of this study lies in the analysis of data from various countries across three continents, which highlights the factors influencing the significant variability of BD in PwMS. However, several limitations should be acknowledged, including a limited number of studies included in the analysis and the heterogeneity among the reported results. Although subgroup analyses and meta-regressions were performed to find the source of the heterogeneity, the statistical heterogeneity in pooled effect sizes remained high, which limits the generalizability of our findings. Therefore, the pooled estimates should be viewed as indicative of general epidemiological trends rather than precise summary measures. Additionally, in each of the OR and hazard ratio analyses, few studies were included, and the results can be considered preliminary findings, necessitating further studies to assess and confirm the findings. Visual inspection of the funnel plot and results of Begg’s and Egger’s tests suggested the absence of publication bias for most meta-analyses. However, for the pooled prevalence of BD among PwMS, publication bias was detected. Thus, this pooled prevalence may be slightly biased due to the selective publication of studies with more significant results. Sensitivity analyses demonstrated that the statistical significance of the pooled OR and HR was influenced by the exclusion of a few studies, which highlights the need for cautious interpretation of these findings. Moreover, the medications used in PwMS treatment could be a significant factor in the onset of BD, which was not included in the analysis due to a lack of available results of original studies. Immunomodulatory drugs, disease-modifying therapies, and corticosteroids might influence mood, but we could not examine these effects systematically. Despite evidence of a shared genetic background (including the HLA-DR2 and DQ1 haplotype) that may predispose PwMS to BD [ 80 , 87 ], the specific role of genetic factors and family history has not been defined in existing analyses. Additionally, many studies did not report the location of brain lesions in BD among PwMS. Although BD encompasses two primary clinical subtypes with distinct implications, most of the included studies did not differentiate between BD I and II, which prevented us from estimating these outcomes. Given these limitations, further studies examining the mechanisms of BD in PwMS using diffusion tensor imaging and neuroinflammatory biomarkers are necessary to confirm the results and explore the underlying pathophysiology precisely.
Conclusion
This review revealed a 3.2% overall prevalence of BD among PwMS and identified a possible increased risk of BD in this population. Considering the interplay between MS and BD, greater attention needs to be paid to selecting appropriate supportive and therapeutic measures, as well as to the timely diagnosis and management of BD in PwMS. Although PwMS have a statistically higher risk of BD, the clinical significance needs further studies.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary Material 1
Supplementary Material 2
Publisher’s note
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Acknowledgements
None.
Author contributions
Omid Mirmosayyeb: Conceptualization, Methodology, Investigation, Supervision, Validation, Project administration, Writing – review & editing. Saeed Vaheb: Data Curation, Validation, Writing – review & editing. Aysa Shaygannejad: Data Curation. Elaheh Foroughi: Writing – original draft. Mohammad Yazdan Panah: Conceptualization, Methodology, Investigation, Formal analysis, Visualization, Writing – review & editing. Vahid Shaygannejad: Conceptualization, Investigation, Writing – review & editing.
Funding
The authors received no financial support for the research, authorship, or publication of this article.
Data availability
The data used to support the findings of this study are included in the article.
Declarations
Ethical approval
This study has been conducted in compliance with Declaration of Helsinki.
Consent for publication
All authors have read and agreed to the published version of the manuscript.
Consent to participate
Not applicable.
Generative AI and AI-assisted technologies in the writing process
During the preparation of this work, the authors used Chat-GPT in order to improve the readability and language of the manuscript. After using this service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.
Competing interests
The authors declare no competing interests.
Abbreviations
bipolar disorder
confidence interval
Expanded Disability Status Scale
healthy controls
hazard ratio
multiple sclerosis
Newcastle–Ottawa Scale
odds ratio
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
people with MS
quality of life
risk of bias
standard deviation
white matter
major depressive disorder
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