STUDY QUESTION Is there an association between infertility diagnosis and long-term adult-onset psychiatric conditions in women?SUMMARY ANSWER Infertility diagnosis in women is linked to higher risks of mood disorders, anxiety- and stress-related disorders, and behavioral syndromes with physical components, but not schizophrenia or other psychotic disorders, particularly notable from 9 years after the first infertility diagnosis.WHAT IS KNOWN ALREADY Infertility, especially in women, is associated with major mental health challenges around the time of diagnosis. However, the long-term connection with a wide range of psychiatric disorders is largely unknown.STUDY DESIGN, SIZE, DURATION This study employed a matched-pair design within the UK Biobank (UKB) cohort, including 3893 females with a diagnosis of infertility and 15 603 matched female controls, totaling 19 496 participants.PARTICIPANTS/MATERIALS, SETTING, METHODS Female UKB participants with a diagnosis of infertility were matched to females without the diagnosis in a 1:4 ratio based on year of birth, index of deprivation of their residency area, and primary care data linkage status. The diagnosis of female infertility was identified by the first occurrence of a primary or secondary diagnosis in either primary care or hospital records. Additional analyses explored interactions between infertility diagnosis and both miscarriage and childbearing status on psychiatric conditions.MAIN RESULTS AND THE ROLE OF CHANCE Diagnosis of infertility was associated with higher risks of mood disorders, anxiety- and stress-related disorders, and behavioral syndromes with physical components, but not with schizophrenia or other psychotic disorders. The most notable increases in the risk of psychiatric diagnoses were observed 9 years after the first infertility diagnosis. No significant interactions were found between infertility diagnosis and either miscarriage or childbearing status on psychiatric conditions. Sensitivity analysis confirmed the robustness of these associations across different data sources for infertility diagnosis and psychiatric condition ascertainment.LIMITATIONS, REASONS FOR CAUTION The study's limitations include the racial homogeneity and the overall healthier status of the UKB cohort compared to the general UK population and the potential underestimation of associations due to misclassification of subfecund women.WIDER IMPLICATIONS OF THE FINDINGS These results emphasize the need for integrated mental health support in infertility care and long-term monitoring of infertility patients for psychiatric risks.STUDY FUNDING/COMPETING INTEREST(S) None. No competing interests were declared.TRIAL REGISTRATION NUMBER n/a.

Few studies have examined the increased risk for pregnancy complications in women with autism spectrum disorder (ASD) diagnosis. The autism genetic propensity in relation to the complications of pregnancy and birth remains unknown, and is an area critical for informing maternal health and reproductive guidance. Here, we assessed whether maternal genetic liability to ASD is associated with pregnancy complications. The study comprised 28,985 females with at least one pregnancy-related record from the UK Biobank (UKB) cohort. Individual polygenic risk scores (PRS) for ASD were calculated, and pregnancy complications were defined using ICD-10 diagnostic codes. Associations between ASD PRS and pregnancy outcomes were evaluated using logistic regression models adjusted for maternal age at first conception. In the secondary analyses, we used schizophrenia (SCZ) PRS, and analyzed broader, ICD-based clusters of pregnancy outcomes. Maternal ASD PRS showed no nominally significant associations with pregnancy outcomes. Maternal SCZ PRS was nominally associated with a reduced risk of spontaneous delivery (O80) and forceps/vacuum delivery (O81); however, no associations remained significant after FDR correction. Higher genetic liability to ASD was not significantly associated with an increased risk of pregnancy complications in the UKB sample. Findings should be interpreted with caution, given the limitations of PRS, potential selection bias in UKB, and the relatively small sample size of females with pregnancy outcomes in the UKB. Autism PRS enables better understanding of aspects of autism that are otherwise limited by the small sizes of the clinical samples. The genetic liability captured by ASD PRS does not appear to predispose mothers to obstetric complications. The observed increase in obstetric diagnoses among autistic females may instead reflect other genetic influences that are not captured through PRS and/or environmental factors.

Despite autism's prominent genetic etiology and early-life origins, parsing genetic effects contributing to the condition into those that operate directly (via allelic transmission to offspring) vs. indirectly (via influencing prenatal environment) remains challenging. We examined this using a novel design leveraging 3-generation family linkage in Danish national registers. The cohort included all children born in Denmark from 1998-2015 and their relatives identified through 3-generation family linkage. The analytic sample comprised full maternal cousin pairs, including parallel (children of mother's sister) and cross cousins (children of mother's brother). Exposures were diagnoses in the index mother previously associated with offspring autism; the outcome was autism diagnosis in cousins of the index child. We used Cox proportional hazards models to estimate associations separately in parallel and cross cousins, followed by comparisons of these hazard ratios to infer mechanisms. Several maternal diagnoses (e.g., postpartum hemorrhage, personality disorders, epilepsy) were associated with autism in both parallel and cross cousins, consistent with shared direct genetic effects. Other conditions (e.g., false labor, recurrent major depressive disorder, other anxiety disorders, systemic connective tissue involvement) showed stronger associations in parallel than cross cousins, supporting additional indirect genetic effects operating through the prenatal environment. Adjustment for the same diagnosis in the cousin's own mother did not substantially change estimates, providing no evidence for an additional role of non-genetic mechanisms associated with the diagnosis. These findings suggest that both direct and indirect genetic effects contribute to observed links between maternal health and offspring autism, highlighting etiologic heterogeneity and highlighting a registry-based family design to separate these pathways without genetic data.

The etiology of autism is influenced by genetic and non-genetic factors, with observational studies suggesting associations between early maternal health diagnoses and offspring autism. However, these associations may partly reflect shared familial genetic liability rather than direct causal effects. Using comprehensive national health registers and individual-level genetic data from the iPSYCH cohort (N=117,542), we examined whether maternal health diagnoses are associated with offspring polygenic scores (PGS) for autism. Such associations between maternal health and offspring autism would indicate shared genetic factors and the possibility of genetic confounding in the observational associations. We also tested such associations with PGSs for other neuropsychiatric and neurodevelopmental conditions that are genetically correlated with autism, but with better-powered PGS (due to larger GWAS sample sizes and likely more polygenic genetic architecture), as well as height, a negative control. Several maternal diagnoses were nominally associated with autism PGS in the child, including, e.g., certain obstetric complications, asthma, and obesity. After adjustment for multiple testing, the only statistically significant results included those between maternal diagnoses, predominantly psychiatric, and other neuropsychiatric and neurodevelopmental PGSs in the child. Sensitivity analyses confirmed the robustness of our results across exposure windows, diagnostic settings, and socioeconomic adjustments. These findings indicate that maternal diagnoses associated with autism partially reflect shared genetic liabilities between mothers and their children. However, such genetic effects, as captured by child PGS do not fully explain the observed associations, suggesting additional factors, including e.g., non-genetic familial factors, rare variants, and indirect effects.

BACKGROUND:Autism spectrum disorder (ASD) has a complex inheritance pattern and is more common in males. Etiologic models suggest that most ASD risk is transmitted through common and rare de novo genetic variation. It has been hypothesized that rare variation could be inherited and therefore contribute to the overall risk burden in subsequent generations, especially through female lineage in disorders with male-skewed sex ratios. Here, we tested this hypothesis using multigeneration information on paternal age, because burden of de novo mutations has been linked to paternal age, and there is a well-established association between older age of fathers and ASD. METHODS:We analyzed combined data from Sweden's, Denmark's, and Finland's national registers, totaling 12.6 million family members, including information about parental ages at the time of birth of offspring in 2 generations and ASD diagnosis in the third generation. RESULTS:Among the 1,808,892 children in the third generation, 23,397 (1.29%) were diagnosed with ASD. Increased paternal age at the time of birth of a daughter was associated with increased risk of ASD in the daughter's own offspring. Increased paternal age at the time of birth of a son was not associated with increased ASD risk in the son's offspring, nor was older maternal age in the first or second generations. We observed that young maternal age at birth of a son or a daughter was associated with ASD risk in their offspring. CONCLUSIONS:Collectively, our results suggest that etiologic risk factors for ASD could extend over multiple generations through different underlying mechanisms, suggesting new directions for research on genetic and nongenetic risk factors.

BACKGROUND:Certain prescription drugs used during pregnancy are associated with offspring autism spectrum disorder (ASD). Nonetheless, ASD risk following prenatal exposure to most drugs remains unknown. Furthermore, methodological challenges and ethical concerns hinder the scope for causal inference. METHODS:We used a case-cohort study design of a nationally representative sample from Israel to examine the associations between maternal prescription drug use during pregnancy and offspring ASD. To scrutinize these associations, the analyses were (a) adjusted for indication proxy (level 2 Anatomical Therapeutic Chemical (ATC) codes), (b) repeated using shared pharmacological targets as exposures, and (c) inspected further through target-enrichment analysis. RESULTS:The sample included 1,400 individuals with and 94,713 without an ASD diagnosis. Among all drugs prescribed during pregnancy, five were statistically significantly associated with increased offspring ASD risk after adjustment for indication proxy (e.g., hazard ratio [95% confidence interval] cyproterone = 2.71 [1.17-6.25] and prednisolone = 2.10 [1.27-3.49]), and two with decreased risk (ferrous sulfate = 0.82 [0.68, 0.99] and lynestrenol = 0.43 [0.2, 0.93]). Further analysis revealed four pharmacological targets shared by these drugs, which were themselves associated with ASD (e.g., neuronal acetylcholine receptor α4β4 = 1.45 [1.05-1.99] and serotonin 2b receptor = 1.31 [1.04-1.61]). Enrichment analysis suggested the association between ASD and medications affecting cholinergic and serotonergic signaling. CONCLUSIONS:Increased ASD risk followed prenatal exposure to five prescription drugs, and decreased risk followed exposure to two. Subsequent analyses suggested no confounding by indication in these associations, but further studies are warranted.

Background: Autism spectrum disorder (ASD) shows significant clinical variability, likely due to a combination of genetic and environmental factors. Preterm birth is a known risk factor for ASD, occurring in approximately 13% of diagnosed individuals. While genetic factors contribute to preterm birth in the general population, the relationship between genetic variation, preterm birth, and ASD heterogeneity remains unclear. Methods: We investigated the genetic factors associated with preterm birth in 31,947 autistic individuals using data from the SPARK (Simons Foundation Powering Autism Research for Knowledge) sample. We conducted 3 ancestry-specific genome-wide association studies for African/African American, admixed American, and non-Finnish European ancestries, followed by a meta-analysis of 3308 preterm cases and 28,639 controls using METAL. Functional mapping and gene-based analyses were performed using FUMA, and genetic correlations were estimated using LDSC and Popcorn. Polygenic risk scores (PRSs) were computed with BridgePRS, using PRS of preterm birth in the general population. Results: Our study identified ancestry-specific genetic loci associated with preterm birth in ASD cases. Although the meta-analysis results were not statistically significant, the estimated single nucleotide polymorphism heritability was 14%, indicating a meaningful contribution of common genetic variants. Across ancestry groups, preterm birth status was not significantly associated with PRSs for any psychiatric or medical conditions analyzed. However, polygenic liability to preterm birth in the general population was linked to several congenital anomalies after multiple testing adjustments. Conclusions: These findings highlight the importance of diverse ancestries and early-life exposures in understanding ASD heterogeneity. Future research should replicate these findings in larger samples and explore rare variants associated with preterm birth to better understand the relationship between gestational duration and clinical and genetic differences in ASD.

Evidence suggests that maternal health in pregnancy is associated with autism in the offspring. However, most diagnoses in pregnant women have not been examined, and the role of familial confounding remains unknown. Our cohort included all children born in Denmark between 1998 and 2015 (n = 1,131,899) and their parents. We fitted Cox proportional hazard regression models to estimate the likelihood of autism associated with each maternal prenatal ICD-10 diagnosis, accounting for disease chronicity and comorbidity, familial correlations and sociodemographic factors. We examined the evidence for familial confounding using discordant sibling and paternal negative control designs. Among the 1,131,899 individuals in our sample, 18,374 (1.6

OBJECTIVE:Autism spectrum disorder (ASD) is a neurodevelopmental condition with early-life origins. Maternal health conditions during pregnancy have been linked to autism risk, but most studies have focused on single populations, thus limiting generalizability. We examined whether associations previously reported in a Danish registry-based study were similar in a US cohort. METHOD:We analyzed electronic health records of children born between 2010 and 2017 at Kaiser Permanente Northern California (KPNC), along with their mothers. Maternal diagnoses were classified as chronic or non-chronic. Associations with ASD in the child were assessed using Cox models, adjusting for sociodemographic factors, health care use, and comorbid maternal diagnoses. Methods were aligned with the Danish study for comparability. RESULTS:Among 224,353 children in the KPNC cohort, 5,448 (2.4%) were diagnosed with autism. Of the 42 maternal diagnoses significantly associated with autism in Denmark, 38 were evaluable in KPNC, and 18 remained statistically significant after adjustment. Most associations had point estimates consistent with the Danish study, particularly psychiatric and cardiometabolic conditions. CONCLUSION:Despite demographic and health care differences, 35 of the 38 associations found in the Danish study replicated qualitatively (direction of effect) in the US cohort, suggesting robust cross-setting relevance. Further research is needed to explore underlying mechanisms and effect modifiers. PLAIN LANGUAGE SUMMARY:Research suggests certain maternal health problems during pregnancy may be linked to autism, but differing study methods makes it hard to know if results are consistent across different populations. This study analyzed electronic health records of 224,353 children born between 2010 and 2017 (2.4% of whom received an autism diagnosis) at Kaiser Permanente Northern California. The authors compared these results with a study done in Denmark using similar methods. Results showed that a number of maternal conditions, particularly psychiatric and cardiometabolic conditions, were associated with autism in their children in both studies, suggesting these links are not due to location-specific factors.

Numerous studies have highlighted the complex connections between various environmental factors and the short- and long-term psychiatric and neurodevelopmental outcomes in children (below, collectively referred to as "neuropsychiatric conditions"). For example, research has explored the impact of maternal nutrition and prenatal care, maternal mental health, and environmental exposures on child development and mental health. These studies have highlighted multiple environmental factors associated with childhood-onset neuropsychiatric conditions, facilitating the formulation of new etiological hypotheses regarding these outcomes.

Background Depression rates are higher in women, especially during periods of hormonal fluctuation. Reproductive system disorders (RSDs), which often disrupt hormonal balance, may contribute to this mental health burden. Despite their prevalence and significant health implications, the link between RSDs and depression remains underexplored, leaving a gap in understanding these women's mental health risks.Methods Using Danish nationwide health registers (2005-2018), we conducted a cohort study of 2,295,824 women aged 15-49, examining depression outcomes in 265,891 women diagnosed with 24 RSDs, including endometriosis, polycystic ovary syndrome, and pain-related diagnoses. For each RSD, age-matched controls were selected. We calculated incidence rates, incidence rate ratios, and prevalence proportions of depression diagnoses or antidepressant use around RSD diagnosis.Results Across all RSD subtypes, women demonstrated higher rates of depression both before and after diagnosis, with a peak within the year following diagnosis. Incidence rate ratios within 1 year of RSD diagnosis ranged from 1.15 (95% confidence interval [CI] 1.06-1.25) to 2.09 (95% CI 1.98-2.21), depending on RSD subtype. Elevated depression prevalence was observed 3 years before diagnosis, suggesting mental health impacts may have preceded clinical RSD identification.Conclusions This study reveals a striking association between RSDs and depression. Women with RSDs are more likely to suffer from depression, before and after RSD diagnosis, highlighting the need for integrated mental health screening and intervention. With over 10% of women affected by RSDs, addressing this overlooked mental health burden is imperative for improving well-being in a significant portion of the population.

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Importance General trauma is the leading cause of nonobstetric maternal morbidity and mortality, affecting approximately 8% of all pregnancies. Pregnant women with traumatic brain injury (TBI) face high morbidity and mortality rates, requiring complex management due to physiological changes, teratogenic risks of treatments, and the need for fetal monitoring. Objectives To assess the consequences of TBI during pregnancy on maternal and fetal outcomes and to evaluate management strategies to inform clinical decision-making. Evidence Review A systematic literature search was conducted on January 12, 2024, in PubMed, Web of Science, and PsycInfo to identify articles published in English, German, or Spanish between January 1, 1990, and December 31, 2023, that included at least 1 pregnant individual with TBI. Peer-reviewed, human-based studies with original data on maternal and fetal outcomes were included. Reviews, meta-analyses, and nonhuman studies were excluded. Two independent reviewers screened abstracts and full-text articles. Study characteristics, pregnancy outcomes (maternal and fetal), management methods, and authors' conclusions were extracted. Risk of bias was assessed by 2 reviewers, with interrater agreement measured using Cohen kappa. Disagreements were resolved through discussion. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline was followed. Findings This systematic review included 16 articles involving a total of 4112 individuals (mean maternal age, 26.9 years; range, 16-47 years) who experienced TBI during pregnancy (mean gestational age at injury, 24 weeks; range, 3-38 weeks). The articles comprised 10 case reports, 2 case series, and 4 cohort studies. Motor vehicle crashes were the most common cause of injury, reported in 12 articles. The average Glasgow Coma Scale score ranged from 3 to 15 across all individuals. Conservative management was reported in 7 case patients, whereas surgery was performed in 6 case patients. Maternal outcomes ranged from functional recovery to severe cognitive impairment, and fetal outcomes varied from stable to severe adverse outcomes, including stillbirth and death. Risk of bias assessment indicated moderate to good methodological validity overall, but most articles demonstrated poor quality of evidence. Conclusions and Relevance In this review, no definitive association between TBI during pregnancy and maternal or fetal outcomes was found owing to conflicting findings, poor to moderate study quality, and limited evidence. Although some articles suggested increased risks such as placental abruption and cesarean delivery, the findings remained inconclusive. The findings of this review underscore the need for high-quality research, standardized reporting, and rigorous methodology to improve data reliability. Future research should focus on developing consensus-driven, multidisciplinary management strategies to improve maternal and fetal outcomes.

Introduction:Comorbidity between disorders is pervasive, and its relationship to the main conditions under investigation needs to be addressed for robust causal inference. However, many clinical etiologic studies still fail to capitalize on the theoretical advancements and improved recommendations regarding covariate adjustment in this context. Specifically, studies often lack explicit causal assumptions about the role of comorbidity in exposure-outcome relationships, potentially leading to inappropriate accounting for comorbid conditions and resulting in biased effect estimates. This study aims to explore common causal structures involving comorbidity and provide guidance for handling it in etiologic research. Methods:We use Directed Acyclic Graphs (DAGs) to depict six causal scenarios involving comorbidity as a confounder, mediator, collider, or consequence of the exposure or outcome, illustrated with real-world clinical examples. Simulations were conducted across 5,000 iterations for each scenario, assessing the impact of conditioning on comorbidity under four effect measures (risk difference, odds ratio, risk ratio, and mean difference). Bias was evaluated by comparing adjusted and unadjusted effect estimates to the true values. Results:The impact of conditioning on comorbidity varied by its causal role. Adjusting for comorbidity mitigated bias when it acted as a confounder but introduced bias when it was a mediator or collider. In instances where comorbidity was a consequence of either the exposure or outcome, the decision to adjust depended on the research objectives and could vary across effect measures. Discussion:Explicit causal assumptions are essential for selecting appropriate analytical strategies in etiologic research. This study provides practical guidance on analytical handling of the measures of comorbidity, highlighting the need for study design and analysis to align with research objectives. Future work should address more complex causal structures and other methodological challenges.

Introduction Despite the theoretical advancements and recommendations regarding covariate adjustment in causal inference, clinical studies often fail to explicitly state the underlying assumptions related to causal structure among the study variables. Specifically, despite the pervasive nature of comorbidity, explicit causal assumptions about the role of comorbidity in exposure-outcome relationships are often lacking, potentially leading to inappropriate accounting for comorbid conditions and resulting in biased effect estimates. This study aims to explore common causal structures involving comorbidity and provide guidance for handling it in etiologic research. Methods We use Directed Acyclic Graphs (DAGs) to depict six causal scenarios involving comorbidity as a confounder, mediator, collider, or consequence of the exposure or outcome. Simulations were conducted across 5,000 iterations for each scenario, assessing the impact of conditioning on comorbidity under three effect measures (mean difference, odds ratio, risk ratio). Bias was evaluated by comparing adjusted and unadjusted effect estimates to the true values. Results The impact of conditioning on comorbidity varied by its causal role. Adjusting for comorbidity mitigated bias when it acted as a confounder, but introduced bias when it was a mediator or collider. In instances where comorbidity was a consequence of either the exposure or outcome, the decision to adjust depended on the research objectives. Nonlinear models revealed differences in marginal and conditional effects due to non-collapsibility. Discussion Explicit causal assumptions are essential for selecting appropriate analytical strategies in etiologic research. This study provides practical guidance on handling comorbidity-related challenges, highlighting the need for study design and analysis to align with research objectives. Future work should address more complex causal structures and other methodological challenges. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.

Background Autism Spectrum Disorder (ASD) shows significant clinical variability, likely due to a combination of genetic and environmental factors. Preterm birth is a known risk factor for ASD, occurring in approximately 13% of diagnosed individuals. While genetic factors contribute to preterm birth in the general population, the relationship between genetic variation, preterm birth, and ASD heterogeneity remains unclear. Methods We investigated the genetic factors associated with preterm birth in 31,947 autistic individuals using data from the SPARK sample. We conducted three ancestry-specific, genome-wide association studies for African/African American, Admixed American, and Non-Finnish European ancestries, followed by a meta-analysis of 3,308 preterm cases and 28,639 controls using METAL. Functional mapping and gene-based analyses were performed using FUMA, and genetic correlations were estimated using LDSC and Popcorn. Polygenic risk scores (PRS) were computed with BridgePRS, using PRS of preterm birth in the general population. Results Our study identified ancestry-specific genetic loci associated with preterm birth in ASD cases. Although the meta-analysis results were not statistically significant, the estimated SNP heritability was 14%, indicating a meaningful contribution of common genetic variants. Across ancestry groups, preterm birth status was not significantly associated with PRS for any psychiatric or medical conditions analyzed. However, polygenic liability to preterm birth in the general population was linked to several congenital anomalies after multiple testing adjustments. Conclusions These findings highlight the importance of diverse ancestries and early-life exposures in understanding ASD heterogeneity. Future research should replicate these findings in larger samples and explore rare variants associated with preterm birth to better understand the relationship between gestational duration and clinical and genetic differences in ASD.

ImportanceGeneral trauma is the leading cause of nonobstetric maternal morbidity and mortality, affecting approximately 8% of all pregnancies. Pregnant women with traumatic brain injury (TBI) face high morbidity and mortality rates, requiring complex management due to physiological changes, teratogenic risks of treatments, and the need for fetal monitoring.ObjectivesTo assess the consequences of TBI during pregnancy on maternal and fetal outcomes and to evaluate management strategies to inform clinical decision-making.Evidence ReviewA systematic literature search was conducted on January 12, 2024, in PubMed, Web of Science, and PsycInfo to identify articles published in English, German, or Spanish between January 1, 1990, and December 31, 2023, that included at least 1 pregnant individual with TBI. Peer-reviewed, human-based studies with original data on maternal and fetal outcomes were included. Reviews, meta-analyses, and nonhuman studies were excluded. Two independent reviewers screened abstracts and full-text articles. Study characteristics, pregnancy outcomes (maternal and fetal), management methods, and authors’ conclusions were extracted. Risk of bias was assessed by 2 reviewers, with interrater agreement measured using Cohen κ. Disagreements were resolved through discussion. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline was followed.FindingsThis systematic review included 16 articles involving a total of 4112 individuals (mean maternal age, 26.9 years; range, 16-47 years) who experienced TBI during pregnancy (mean gestational age at injury, 24 weeks; range, 3-38 weeks). The articles comprised 10 case reports, 2 case series, and 4 cohort studies. Motor vehicle crashes were the most common cause of injury, reported in 12 articles. The average Glasgow Coma Scale score ranged from 3 to 15 across all individuals. Conservative management was reported in 7 case patients, whereas surgery was performed in 6 case patients. Maternal outcomes ranged from functional recovery to severe cognitive impairment, and fetal outcomes varied from stable to severe adverse outcomes, including stillbirth and death. Risk of bias assessment indicated moderate to good methodological validity overall, but most articles demonstrated poor quality of evidence.Conclusions and RelevanceIn this review, no definitive association between TBI during pregnancy and maternal or fetal outcomes was found owing to conflicting findings, poor to moderate study quality, and limited evidence. Although some articles suggested increased risks such as placental abruption and cesarean delivery, the findings remained inconclusive. The findings of this review underscore the need for high-quality research, standardized reporting, and rigorous methodology to improve data reliability. Future research should focus on developing consensus-driven, multidisciplinary management strategies to improve maternal and fetal outcomes.