Abstract
Emerging evidence suggests that amyotrophic lateral sclerosis (ALS) mortality is elevated following traumatic brain injury (TBI), reflecting a consequence of potential prodromal ALS, though the temporal patterns and underlying mechanisms remain unclear. We aimed to evaluate ALS mortality among individuals with TBI and examine temporal patterns. This study leveraged a retrospective cohort study of 20,250 individuals with complicated mild-to-severe TBI enrolled in the TBI Model Systems (TBIMS) from 1987 to 2024, with a cumulative 198,662 person-years (mean [standard deviation] = 9.8 [7.1] years) of follow-up. Standardized mortality ratios (SMRs) were calculated using the National Institute for Occupational Safety and Health Life Table Analysis System R package, adjusting for age, sex, race, and calendar year. Secondary analyses evaluated temporal patterns and injury severity differences in ALS mortality. Among 4,313 decedents in TBIMS, 11 died of ALS, representing significantly elevated mortality from ALS (SMR = 2.39; 95% confidence interval [CI]: 1.19–4.27) compared with the general population. Time-stratified analyses showed elevated ALS mortality within 2 years post-injury (SMR = 4.30; 95% CI: 1.17–11.01), but not after 2 years (SMR = 1.90; 95% CI: 0.76–3.92). Elevated ALS mortality was also observed within 2 years post-injury among those with severe TBI (SMR = 5.00; 95% CI: 1.03–14.61) and when including individuals with ALS at admission (SMR = 6.45; 95% CI: 2.37–14.04). ALS mortality was higher in the TBIMS cohort than in the general population, and this association was confined to within 2 years of injury. This pattern suggests potential reverse causality, whereby some TBIs in the cohort may have occurred in the setting of prodromal or pre-symptomatic ALS. Further investigation into TBI as a sign of subclinical ALS is warranted.
Introduction
Amyotrophic lateral sclerosis (ALS) is a fatal and often rapidly progressive neurodegenerative disorder, with a median survival period of 20–36 months after diagnosis. 1 –3 Formal ALS diagnosis occurs, on average, 12 months after symptom onset. This delay is largely attributed to nonspecific and heterogenous early disease presentation, the absence of biomarker-based diagnostic fidelity, and difficulty accessing specialists. 4–6 This delay promotes unnecessary testing, reduces clinical trial eligibility, and limits the opportunity to slow the progression of ALS via disease-modifying therapies and multidisciplinary management strategies. 7 Identifying early clinical indicators is essential for supporting a timely diagnosis.
Several population-based studies have assessed the relationship between traumatic brain injury (TBI) and subsequent ALS diagnosis by reporting time-dependent associations. A recent population-based study reported that a history of TBI was associated with a 2.6-fold increased likelihood of ALS diagnosis, with this association confined to within 2 years post-injury (hazard ratio ∼6). 8 Other population-based studies have demonstrated a time-dependent fourfold rate of ALS incidence among those with a history of TBI within the preceding 12 and 6 months, respectively.9,10 A meta-analysis investigating TBI and ALS reported a time-dependent association between ALS diagnosis following TBI within 12 months (odds ratio = 4.05; 95% confidence interval [CI]: 2.79–5.89); however, this association did not hold at 1–5, 5–10, and >10 years post-injury. 11 Given that ALS incidence largely approximates mortality due to its uniform fatality, 12 studies demonstrating reverse causality evaluating ALS diagnosis are relevant when evaluating the potential prodromal link between TBI and ALS mortality.
While these studies highlight a potential time-dependent relationship, findings are mixed, and the role of injury severity remains unclear. Recent work demonstrated that head injuries were associated with increased risk of ALS before 60-years-old, with elevated risk in those with multiple head injuries and head injury in childhood. 13 In a small cohort, there was no association between TBI and ALS. 14 Although not restricted to TBI, Pupillo and colleagues reported an elevated ALS risk among those with traumatic injuries, particularly among those with severe injuries and those who sustained three or more traumatic injuries. 15 Notably, this association remained when restricting analyses to injury dates >5 and 10 years prior to ALS diagnosis. 15
The present study sought to compare ALS mortality in Traumatic Brain Injury Model Systems (TBIMS) participants with those of the general population, examine potential reverse causation by assessing whether injury–mortality timing influenced this association, and evaluate ALS mortality risk differences by injury severity. We hypothesized that ALS mortality would be higher in the TBIMS cohort, with the greatest risk occurring within 2 years post-injury and among individuals with severe injuries.
Methods
Study design and participants
Data were extracted from the TBIMS national database (NDB), a longitudinal dataset of individuals with complicated mild-to-severe TBI who received inpatient rehabilitation at one of 20 participating centers. 16 Each participating center received institutional review board approval. Details on inclusion criteria, data collection, data sources, and study procedures have been previously described. 16 Primary or secondary cause-of-death International Classification of Diseases, Ninth Revision (ICD-9) codes 335.2, 335.20, 335.21, 335.24, and 335.29 were used to identify ALS decedents. Severity of TBI was classified as mild (Glasgow coma scale [GCS] 13–15 or post-traumatic amnesia [PTA] duration <24 h), moderate (GCS 9–12 or PTA 1–7 days), or severe (GCS <9 or PTA >7 days). 17
The TBIMS NDB included 20,426 participants from 1987 to 2024, followed for a cumulative 198,662 person-years (mean = 9.8 years, standard deviation = 7.1 years). Entries with incomplete baseline information or unresolvable errors were excluded (n = 173). Participants with an ALS diagnosis at the time of acute hospital admission were identified through extraction of ICD codes recorded in the inpatient medical record and were excluded from the primary analysis (n = 3). A total of 15,937 participants did not have recorded death dates; of these, 13,005 were alive and 2,932 were lost to follow-up. Cause of death for decedents was obtained from death certificates collected by TBIMS coordinators. Among the 4,313 decedents in the cohort, 1,444 had an unknown cause of death. A flowchart illustrating study inclusion is shown in Supplementary Figure S1.
Statistical analysis
All analyses were conducted using R Statistical Software, v4.4.2 (Vienna, Austria). Differences between decedents with and without ALS were examined by two-sample t test and Welch two-sample t test for continuous variables, and chi-square or Fisher’s exact test for categorical variables. The Life Table Analysis System R (LTASR) package, 18 which implements the National Institute for Occupational Safety and Health Life Table Analysis System, was used to calculate standardized mortality ratios (SMRs) and 95% CIs to compare mortality from ALS in the study cohort to that of the U.S. general population. Analyses were adjusted for age (5-year groups starting at ages 15–19), race (White and non-White), sex (male and female), and calendar year (5-year intervals starting in 1960). Person-years for each subject accrued from the date of injury until the date of death or loss to follow-up. Individuals who were known deceased with unknown cause of death were mapped to “other causes” in LTASR, contributing person-time without being classified as ALS or non-ALS deaths. Results were considered statistically significant if the 95% CI did not include 1.0. Secondary analyses calculated SMRs for those who died within and after 2 years of TBI to evaluate potential reverse causation, following prior studies demonstrating ALS as a prodromal indicator and using the lower estimate of median survival of ALS.1–3 Additional analyses evaluated differences in ALS mortality by injury severity and included those with ALS at admission to investigate TBI as a prodromal indicator. Sensitivity analyses evaluated SMR results excluding those with unknown causes of death; these findings are reported in Supplementary Data.
Results
Among the 4313 decedents in the study cohort, 11 died of ALS. Supplementary Table S1 details individual clinical profiles for the ALS cases. All individuals in the ALS group were White, 9 of 11 were male, and all sustained their injuries at age 58 or older. Most individuals with ALS in the cohort had GCS scores and PTA durations consistent with greater injury severity at admission (n = 8; 72.7%), sustained their TBI from a fall (n = 9; 81.8%), and had documented radiographical evidence of intracranial hemorrhage on computed tomography (n = 10; 90.9%). Table 1 compares pre- and post-injury characteristics for those with and without ALS. Although the proportion of TBI from falls was notably high in those with ALS, injury mechanism did not differ significantly between groups (p = 0.910). Individuals with and without ALS had similar years of education (13.9 vs. 12.6 years) and pre-injury alcohol use (45.5% vs. 45.2%); however, body mass index (BMI) (9.1% complete), smoking (9.1% complete), prior TBI history (27.3% complete), and military service data (18.2% complete) in the ALS cohort were largely missing or not collected at time of enrollment. Decedents with ALS sustained injuries later in life than those without ALS (p = 0.025) and had a trend toward a shorter interval between initial injury and death compared to decedents without ALS when adjusting for age at injury, admission GCS, and PTA duration (p = 0.051). Time from injury to follow commands was shorter among decedents with ALS (p < 0.001); however, there was no significant difference in admission GCS (p = 0.610) or PTA duration (p = 0.110) between those with and without ALS.
Traumatic Brain Injury Model Systems Participant Characteristics by Amyotrophic Lateral Sclerosis Diagnosis
Percentages represent the number divided by all decedents within diagnostic category.
ALS, amyotrophic lateral sclerosis; CT, computed tomography; GCS, Glasgow Coma Scale; mm, millimeter; SD, standard deviation; TBI, traumatic brain injury; TBIMS, Traumatic Brain Injury Model Systems; – = not applicable.
TBIMS participants demonstrated significantly elevated mortality from ALS (SMR = 2.39; 95% CI: 1.19–4.27) compared to the general population, adjusted for age, race, sex, and calendar year (Table 2). Notably, four individuals (36.4%) in the ALS cohort died within 2 years of sustaining a TBI. ALS mortality was significantly elevated among those who died within 2 years post-injury (SMR = 4.30; 95% CI: 1.17–11.01), but not after 2 years post-injury (SMR = 1.90; 95% CI: 0.76–3.92). When those with an ALS diagnosis listed at acute hospital admission were not excluded from the cohort, the risk of mortality from ALS within 2 years of TBI was 6.45 (95% CI: 2.37–14.04) times greater than the general population. Elevated ALS mortality was also observed within 2 years post-injury among those with severe TBI (SMR = 5.00; 95% CI: 1.03–14.61) but not moderate TBI (SMR = 6.67; 95% CI: 0.17–37.14). The SMR for complicated mild TBI could not be reliably estimated due to insufficient events.
Amyotrophic Lateral Sclerosis Mortality by Time of Death in Traumatic Brain Injury Model Systems Participants
SMR adjusted for age at death, calendar year of death, sex, and race. – = could not be calculated. Significant SMRs are bolded.
ALS, amyotrophic lateral sclerosis; CI, confidence interval; SMR, standardized mortality ratio; TBI, traumatic brain injury.
Discussion
Participants in TBIMS had a 2.4-fold increased risk of ALS mortality compared to the general population, and this risk was time-and sample-dependent, with a 4.3-fold increased risk of ALS mortality within 2 years of TBI, a fivefold increased risk within 2 years of severe TBI, and a 6.5-fold increased risk when including those who had an ALS diagnosis at the time of injury. Together, these findings align with our hypotheses of elevated risk of ALS mortality among those with TBI and suggest that this risk may reflect potential reverse causation or unrecognized disease progression within 2 years of TBI, supporting TBI as a time- and sample-based indicator of ALS mortality.
Our results align with numerous recent studies indicating a time-dependent association between TBI and ALS risk, where TBI may reflect early manifestations of undiagnosed disease,8–11 a mechanism first proposed as early as 1996. 19 The greater prevalence of fall etiology among those with ALS (81.8% vs. 50.2%) and the trend toward a shorter time between injury and death compared to those who died of other causes further supports a potential mechanism whereby prodromal motor and cognitive impairment from ALS increases the risk of TBI.20–22 Previous work contradicting this relationship has relied on self-reported head injury, 13 small sample size (n = 1) without time-stratified analysis, 14 and a cohort in which only 6% had non-concussion TBIs within 5 years of injury and 4% after 5 years of injury. 15 The time-dependent elevation in ALS mortality risk does not exclude the possibility that TBI accelerates motor neuron pathology, as demonstrated in animal models.23,24 However, other studies have demonstrated no association between TBI and accelerated ALS disease progression or a unique tau and TDP-43 proteinopathy phenotype. 25 Hence, the relationship between TBI and ALS described in the present and prior studies likely represents reverse causation, whereby undiagnosed or prodromal ALS increases the risk of trauma, particularly TBI. 26 Given the rarity of ALS and the small number of cases in this study, the clinical utility of TBI as a prodromal marker remains limited and ill-defined. Further research into early indicators is essential to enable timely recognition and improve access to disease-modifying therapies and multidisciplinary care that may slow ALS progression.7,27
This study was the first to examine the impact of TBI severity on ALS mortality using standard TBI classification guidelines that rely on GCS and PTA, 28 and to further conduct a time-stratified analysis by severity level. Our findings suggest that severe TBI may arise with early ALS progression, potentially driven by gait variability, cognitive impairment, fall risk, and muscle weakness characteristic of ALS progression.20–22 Severe TBI may occur more frequently among those with greater motor and cognitive impairment and may serve as a proxy marker for disease severity and rapid progression.20,22 Future studies incorporating longitudinal functional assessments and progression evaluation are needed to fully characterize the relationship between TBI severity and ALS mortality.
This study had several limitations. First, the small number of ALS cases (n = 11) limits the precision of SMR estimates and detection of modest associations. 29 The retrospective nature of the study, coupled with a significant portion of the cohort lost to follow-up or with unknown cause of death, may contribute to underestimation of true mortality from ALS following TBI, as unascertained ALS cases within this group would be classified under “other causes” or excluded due to loss to follow-up. The complete-case strategy where those with unknown vitality were excluded from analysis may introduce bias if those lost to follow-up systematically differ from those included in the cohort. However, TBIMS utilizes comprehensive tracing procedures to ascertain vitality among those lost to follow-up, including obituary searches, directory searches, and location services. Decedents with ALS in this cohort may have been missed due to reliance on death certificates, which frequently report mortality from respiratory failure, cardiovascular disease, and pneumonia instead of underlying ALS. 26 However, this would also occur and be reflected in general population ALS rates. Neurological consequences of TBI could mask ALS diagnosis, potentially leading to misattribution of cause of death solely to TBI. On the other hand, increased health supervision through participation in the TBIMS could enhance detection of ALS, thereby inflating rates in this cohort. Although premorbid ALS cases were excluded in primary analysis, we lacked data on the exact timing of ALS diagnosis and relied solely on whether ALS was listed as a diagnosis at acute admission through medical record abstraction, which could bias underreporting premorbid conditions. The lack of complete clinical data in the ALS cohort prevented analysis of other pertinent risk factors, including BMI, military experience, and smoking.12,30–33 Finally, these results from TBIMS participants may not be generalizable to the broader population of individuals with ALS or TBI, who may differ in health status, injury characteristics, access to care, and mortality risk. 16
Conclusion
Individuals with TBI demonstrate a 2.4-fold increased likelihood of ALS mortality, with time- and sample-dependent variations, including a fourfold increased risk of ALS mortality within 2 years of injury, a fivefold increased risk within 2 years of severe injury, and nearly a sevenfold increased risk when including individuals with an ALS diagnosis at the time of injury. Time-dependent patterns suggest reverse causation, whereby TBI may result from undiagnosed ALS. Given the fatal nature of ALS and its public health impact, further research evaluating the role of diagnostic timing and changes in longitudinal functional assessments are needed to clarify the relationship between TBI and ALS.
Transparency, Rigor, and Reproducibility Statement
This study is part of the TBIMS project funded by NIDILRR and was not formally registered before implementation; however, coauthors (Y.Z., C.B.L., and D.H.D.) affirm that the analysis plan was prespecified. A sample of 20,426 with a cumulative 198,662 person-years was utilized for this study from the TBIMS database. An a priori power analysis was conducted to determine the required person-years to detect an elevated ALS mortality rate in the TBI cohort relative to the general population. Using an SMR framework involving a one-sample comparison to a fixed reference rate, power was approximated using an exact one-sample binomial test in G*Power (version 3.1.9.7), treating person-years of follow-up as independent trials and ALS mortality as a rare event. The ALS mortality rate in the general population was specified as 22 deaths per 100,000 person-years, and the alternative hypothesis assumed a 2.6-fold increased risk of mortality (SMR = 2.6), 8 corresponding to a proportion of 0.000572. Using a one-sided test with α = 0.05 and 80% power, a total of 17,888 person-years of follow-up were required to detect a statistically significant increase in ALS mortality relative to the general population. Assuming an average follow-up of 10 years per participant, this corresponded to ∼1,789 participants. All individuals enrolled in TBIMS from 1987 to 2024 were included in the original study cohort, and 173 individuals were removed due to missing key data (e.g., dates of birth). Primary analyses excluded three individuals with ALS diagnoses codes listed and collected at admission. Research staff collected data while blinded to participant characteristics relevant to the study. Investigators conducted analyses using de-identified data but were aware of relevant participant characteristics. Inclusion criteria have been detailed previously and follow established standards in the field using validated clinical tools. Data were analyzed using SMRs calculated with the LTASR package, which leverages CDC mortality data for the U.S. population. A neurodegenerative disease rate file was obtained from the creator of LTASR at the National Institute of Occupational Safety and Health to calculate SMRs for ALS. Future analyses by the study group will evaluate study validation. The TBIMS Public Use Data Set is available for download at https://www.tbindsc.org/. A limited dataset available upon appropriate request. Analytic code used for data analyses in the study is not publicly available, but the code may be available by emailing the corresponding author (D.H.D.).
Authors’ Contributions
Y.Z. and C.B.L.: Conception or design of the work; acquisition, analysis, or interpretation of data for the work; drafting the work; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy. S.M.P., E.D.F., S.P., S.I., R.D.Z., J.T.G., and F.M.H.: Acquisition, analysis, or interpretation of data for the work; reviewing it critically for important intellectual content; final approval of the version to be published; and integrity of any part of the work are appropriately investigated and resolved. . D.H.D.: Conception or design of the work; acquisition, analysis, or interpretation of data for the work; reviewing it critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy.
Footnotes
Author Disclosure Statement
C.B.L. reports receiving clinical funding from the Brain and Body Program funded by the NFLPA outside the submitted work. S.P. reported receiving grants from Amylyx, Eledon, Alector, Seelos, Calico, Denali, NIH, CDC, and DoD; institutional consulting agreements from Amylyx, Revalesio, Bristol Myers Squibb, Eikonizo, Clene Nanomedicine, Sola, PharmAust, and Prilenia Therapeutics; personal fees from Arrowhead, Cytokinetics, Merck, Biogen, and Johnson & Johnson; and speaking fees from PeerView, Medscape, and i3 Health, all outside the submitted work. R.D.Z. reported serving on the scientific advisory boards of Myomo and NanoDx and as a member of the Mackey White Committee of the NFL Players Association outside the submitted work. In addition, R.D.Z. reported receiving funding from the
Funding Information
The current investigation was conducted under no formal funding resource. However, the contents of this report were developed under a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant numbers: 90DPTB0027 [J.T.G.]; 90DPTB0022, [F.M.H.]; and 90DPTB0023 [S.M.P.]). NIDILRR is a Center within the Administration for Community Living, Department of Health and Human Services. The contents of this report do not necessarily represent the policy of NIDILRR, ACL, HHS, and you should not assume endorsement by the Federal Government.
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References
Supplementary Material
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