Both cross-sectional and longitudinal neuroimaging studies have confirmed that, compared with normal controls, ALS patients exhibit changes primarily in the CST and CC in the early stages of the disease, with a notable prevalence of UMN involvement26,37. Similar findings have also been reported in asymptomatic individuals carrying pathogenic gene variants38. However, whether the baseline condition of white matter fiber tracts contributes to the onset of clinical events in individuals with ALS and whether ALS can cause damage to specific fiber tracts remain unclear. Currently, dMRI is the optimal noninvasive method for detecting in vivo changes in white matter fiber tracts13,39.Both FA and RD are valuable indices in DTI studies because they provide insights into the structural integrity of white matter tracts40. Higher FA values indicate greater directionality and organization of fibers, suggesting healthier and more intact white matter tracts. Increased RD values suggest increased diffusion in directions perpendicular to the fibers, which can be indicative of myelin degradation or loss. FA and RD can be used to detect subtle changes or abnormalities in patients with various neurological conditions, including ALS41,42. Additionally, MD is commonly used to assess and study the microstructure and integrity of the brain and neural tissues43. Higher MD values are often associated with pathological changes in the tissue. In DTI models, the FPCA is utilized to capture the most prominent variations in components of FA within each tract. This approach is designed to provide a deeper understanding of axonal organization and myelination, which are often overlooked when tract-averaged values are used44. These principal components (PCs) may represent FA changes that are more relevant to specific clinical outcomes. In summary, in previous ALS neuroimaging studies, higher FA and PC values and lower MD and RD values were associated with better fiber tract integrity, whereas the opposite results indicated poorer integrity.Using data from large-scale neuroimaging phenotype GWASs and an ALS GWAS, we conducted a bidirectional two-sample MR study and reported an association between GCC PC1 and the risk of ALS. Additionally, although CST MD, CST RD, GCC FA, GCC PC1, BCC PC1, and GCC RD did not pass the corrected P value threshold in the IVW method, they still showed some genetically predicted significance. Overall, these findings elucidate the importance of the CST and commissural fibers in the mid-anterior region in ALS pathogenesis.Since multiple parameters are available to reflect the integrity of fiber tracts, our results of the forward MR analysis indicate that, in the uncorrected P value situation, changes in the integrity of each fiber tract (CST, GCC, and BCC), as measured by different DTI metrics, are consistent with the risk of ALS. For example, as depicted in Fig. 2, higher RD and MD in the CST or lower FA indicate poorer CST integrity, potentially increasing the risk of ALS. Conversely, for the CC fiber tract, the relationship is the opposite. Higher FA and PC1 in the GCC, higher PC1 in the BCC, or lower RD in the GCC suggest better integrity in the mid-anterior CC, potentially increasing the risk of ALS.The forward MR analysis suggested that as the integrity of the GCC increases, the risk of ALS increases. The current understanding suggests that when the integrity of commissural fibers (mainly the CC) is better, the functional connectivity between the two cerebral hemispheres is stronger and more reliable45,46,47,48. Since ALS affects these white matter fibers, we hypothesize that damage to these fibers leads to decreased integrity, resulting in a loss of the structural basis for functional connections and promoting ALS development. In ALS patients, the possibility of pathological protein propagation, such as TDP-43 proteinopathy (which is currently the most significant), is important to consider49,50. However, pathological studies of ALS have not revealed TDP-43 protein deposits in the CC51. Instead, they mainly show reduced silver-stained fibers, along with GFAP-positive glial cells and CD68-positive cell infiltrates52,53. The following question remains: How does the integrity of the GCC affect the risk of ALS? ALS patients initially present with focal symptoms, and pathological changes in ALS patients are related to the onset site, resulting in focal characteristics. More importantly, the excitotoxicity of glutamate in the motor cortex plays a particularly important role in ALS pathogenesis54. Based on the results of this study, we speculate that the better integrity of the GCC may facilitate the spread of pathogenic proteins to both brain hemispheres. Therefore, in the presymptomatic state, when excitotoxic damage occurs on one side of the motor cortex (assumed to be M1), the information of excitability is transmitted along the CC fibers to the homologous cortex on the opposite side (assumed to be M1′). Since the CC has mutual homotopic callosal inhibition55, M1′ receives inhibitory information, leading to a decrease in the excitability of the M1′ cortex. However, the amount of excitatory information transmitted from M1′ to M1 via the CC increases (due to mutual homotopic callosal inhibition), enhancing the excitotoxic effect on the M1 cortex. After repeated cycles, when the excitotoxic effect of the M1 cortex reaches the pathogenicity threshold, clinical symptoms appear. The integrity of the CC plays a key role in this information transmission process. The increased integrity of the CC facilitates efficient interhemispheric information transmission, thereby accelerating the spread of pathological information and increasing the risk of ALS. Conversely, the compromised integrity of the CC slows the transmission of pathological information, thus reducing the risk of ALS (Fig. 6). Nevertheless, further research that combines analyses of brain functional connectivity with DTI is essential for confirmation. As part of the commissural fibers, although the DTI parameters associated with the BCC did not pass multiple corrections, their potential research significance suggested by the MR results is consistent with that of the GCC. Therefore, the effects of the GCC and BCC on ALS should be taken seriously.Figure 6Speculated mechanism of the ALS risk related to the CC. (A) The pathway of excitotoxic information transmission from the M1 cortex through the CC to the M1′ cortex and the feedback loop. This pathway may be influenced by the integrity of the CC, potentially affecting the risk of ALS. (B) corresponds to a–c in (A), where red represents excitatory stimuli or information and blue represents inhibitory stimuli or information. (C) corresponds to b–d in (A), and the color representation is the same as that in (B). CC, corpus callosum.On the other hand, we also need to pay attention to the potential significance of the CST. When the integrity of the CST is better, the risk of ALS is somewhat reduced. We believe that the CST is the primary affected fiber tract in ALS patients and is closely associated with the pathology of cortical motor neurons56,57,58. When its integrity is compromised to a specific threshold, the onset of ALS occurs; therefore, fiber tracts with better integrity result in a slower onset of the disease59. This finding is supported by existing research3 indicating that the integrity of the CST decreases as the severity of ALS pathology increases, for clearer expression.Our study included an assessment of the global average values of 21 fiber tracts for 5 neuroimaging phenotypes to avoid excessive subjectivity in our exposure selection. The results confirmed that the exposures had no impact on ALS. Microstructural differences and changes may not exhibit a consistent pattern across all fiber tracts, and ALS may affect specific fiber tracts, which could be neutralized when subjected to a comprehensive average assessment60.Conversely, in the reverse MR analysis, we failed to find strong evidence that a genetic predisposition for ALS was associated with specific fiber tracts. This result does not support the abovementioned research background. This discrepancy may be because ALS primarily affects motor neurons (Betz cells in the motor cortex and motor neurons in the anterior horn of the spinal cord), while white matter fibers are secondary damaged structures, which cannot directly show that ALS could genetically predict the integrity of fiber tracts. Additionally, DTI is not the only imaging technique used to describe white matter fiber structures; other methods, such as neurite orientation dispersion and density imaging (NODDI)61, can also be used to evaluate fiber structures from different perspectives.Some SNPs overlapped among the IVs for selected neuroimaging phenotypes, which may affect the results; therefore, the MVMR approach, sensitivity analyses, and horizontal pleiotropy tests were adopted to assess the true relationship and detect the robustness of the estimates. However, according to the MVMR analysis, no significant positive results were found for either specific fiber tracts or the average values across all brain fiber tracts. This result may be due to a mutual constraint relationship among the DTI metrics within specific fiber tracts62, making pinpointing risk factors further by controlling a single parameter challenging.The exact underlying mechanism linking neuroimaging phenotypes to ALS remains elusive. Therefore, in conjunction with the results of our data analysis, we included pathogenic genes related to ALS–FTLD to determine whether any overlap occurred with SNPs showing positive results. However, no overlap was found. In the future, the impact of genes on neuroimaging phenotypes should be further explored.Our study is the first to investigate the effects of neuroimaging phenotypes on ALS patients. All the analyses were performed using data from the largest European-based GWASs. Nevertheless, some shortcomings still exist in this study. The data from the MR analysis indicate heterogeneity and horizontal pleiotropy in some exposures, particularly in the GCC tract. Therefore, we switched from the IVW method to a random effects model for analysis. Additionally, using MR-PRESSO, we found that after removing outliers, the significance remained unchanged, confirming the reliability of the results. Furthermore, because each neuroimaging phenotype for each fiber tract was treated as a separate IV, this MR analysis included many IVs. After FDR correction, only GCC PC1 still showed significant differences, suggesting the involvement of other tracts, such as the BCC and CST, in the risk of ALS. Additionally, the FDR assumes that all the statistical tests have a similar ability to detect potential discoveries. However, FDR estimation is subject to variability due to differences in the underlying biology, signal-to-noise ratio, or features of the trait, which can lead to greater power than other methods in certain tests. Although we included 45 neuroimaging phenotypes as instrumental variables, this number is still far from sufficient. The study investigated only specific fiber tracts via DTI and did not maximize the expansion to all brain fiber tracts. Our failure to identify specific neuroimaging phenotypes associated with ALS in the reversed MR analysis, suggesting the need for larger datasets or additional assessment methods to characterize such associations.More clinical studies and animal experiments are needed to verify the preliminary results of this study. The ‘gold standard’ for empirically alleviating the concerns of residual confounding and reverse causation in clinical research is an RCT. However, RCTs testing the associations between neuroimaging phenotypes and the risk of ALS have not been performed, mainly because of the challenges of implementation and the time-consuming nature of these studies. The presymptomatic stage of ALS can persist for years, and cohort studies may provide more credible evidence with a diminished interference of reverse causation than other observational studies. A large-scale population-based prospective cohort can be established, and baseline information can be collected through head magnetic resonance imaging (MRI) scans and neurological examinations. With long-term follow-up, the relationships between the observed neuroimaging phenotypes and ALS can be revealed using various association analyses. Combining these data and the results generated with the MR framework may yield convincing conclusions in the future. Although our MR analysis cannot fully substitute for randomized controlled trials evaluating intervention effects, it provides a guide for the design of future costly experiments.
