Maternal diabetes as a prenatal risk factor for multiple sclerosis in offspring: a systematic review and meta-analysis.
Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system with a complex etiology involving genetic and environmental factors. Maternal diabetes during pregnancy has been hypothesized to influence offspring MS risk through intrauterine metabolic programming, yet the evidence remains inconclusive.
To systematically review and meta-analyze the association between maternal diabetes and the risk of MS in offspring.
A systematic literature search was conducted across PubMed, Scopus, Web of Science, and Embase, identifying 427 records. After removing 188 duplicates, 239 records were screened, 38 full-text reports were assessed for eligibility, and 4 studies met the inclusion criteria. Pooled risk ratios (RR) were calculated using both common-effect and random-effects models. Heterogeneity was assessed using the I² statistic, and publication bias was evaluated using Egger's and Begg's tests.
The studies, published between 2009 and 2026, were conducted in Denmark, the USA (two studies), and Norway, utilizing diverse designs including nationwide register-based cohorts and a case-control study. The common-effect model yielded a pooled RR of 1.42 (95% CI: 1.09-1.85), while the random-effects model produced a non-significant pooled RR of 3.13 (95% CI: 0.68-14.30). Substantial heterogeneity was observed across studies (I² = 95.2%, τ² = 2.2357, p < 0.0001). Individual study risk ratios ranged from 0.91 (95% CI: 0.60-1.38) to 28.35 (95% CI: 13.33-60.29). Neither Egger's test (p = 0.4364) nor Begg's test (p = 0.1742) indicated significant publication bias, though these tests have limited power with fewer than ten studies.
This meta-analysis did not demonstrate a statistically significant association between maternal diabetes and MS risk in offspring, likely owing to substantial between-study heterogeneity and the limited number of included studies. Large, well-characterized prospective cohorts are needed to clarify this relationship, elucidate underlying mechanisms, and inform preventive strategies.
To systematically review and meta-analyze the association between maternal diabetes and the risk of MS in offspring.
A systematic literature search was conducted across PubMed, Scopus, Web of Science, and Embase, identifying 427 records. After removing 188 duplicates, 239 records were screened, 38 full-text reports were assessed for eligibility, and 4 studies met the inclusion criteria. Pooled risk ratios (RR) were calculated using both common-effect and random-effects models. Heterogeneity was assessed using the I² statistic, and publication bias was evaluated using Egger's and Begg's tests.
The studies, published between 2009 and 2026, were conducted in Denmark, the USA (two studies), and Norway, utilizing diverse designs including nationwide register-based cohorts and a case-control study. The common-effect model yielded a pooled RR of 1.42 (95% CI: 1.09-1.85), while the random-effects model produced a non-significant pooled RR of 3.13 (95% CI: 0.68-14.30). Substantial heterogeneity was observed across studies (I² = 95.2%, τ² = 2.2357, p < 0.0001). Individual study risk ratios ranged from 0.91 (95% CI: 0.60-1.38) to 28.35 (95% CI: 13.33-60.29). Neither Egger's test (p = 0.4364) nor Begg's test (p = 0.1742) indicated significant publication bias, though these tests have limited power with fewer than ten studies.
This meta-analysis did not demonstrate a statistically significant association between maternal diabetes and MS risk in offspring, likely owing to substantial between-study heterogeneity and the limited number of included studies. Large, well-characterized prospective cohorts are needed to clarify this relationship, elucidate underlying mechanisms, and inform preventive strategies.