In this study, 92 individuals with gene-confirmed HD were recruited between March 2009 and November 2023 in the Department of Neurology at West China Hospital of Sichuan University (Chengdu, China). The participants in this study were from the same cohort as the previous study (3, 26). The study received approval from the Institutional Ethics Committee of West China Hospital, Sichuan University, China. Each participant diagnosed with HD in the study had a CAG repeat length more than 39, which was confirmed through genetic testing, and exhibited motor disturbances as defined by a diagnostic confidence score of 4 on the Unified Huntington’s Disease Rating Scale (UHDRS) total motor score (TMS) (27, 28). Exclusion criteria included individuals with chronic inflammatory disease, infectious illness within 3 days prior to the blood test, chronic heart disease, liver cirrhosis, autoimmune diseases, and the use of vitamin or antioxidant supplements. Ninety two HC were recruited and matched for age, sex, and body mass index (BMI). Neurologists (JQX, YFC, and SRZ) through telephone or in-person interviews until November 2023. One patient was lost to follow-up.

All participants underwent face-to-face interviews with experienced neurologists to collect demographic characteristics, including age, gender, height, weight, education, family history, smoking and alcohol consumption habits, as well as age and symptom onset, disease duration, CAG repeat length, comorbidities, and treatments at the baseline. BMI was computed by dividing body weight (kg) by the squared of the height (m²). The age of onset refers to the point at which symptoms related to movement, cognitive, or psychiatric impairments first begin to appear. The age of motor symptom onset (AAO) is defined as when movement disorder begins to manifest. The age at diagnosis is determined by subtracting the date of birth from the date when the gene test was conducted. Clinical severity was assessed by UHDRS (29). Motor function was assessed by TMS. Daily functional performance was assessed by UHDRS-total functional capacity (TFC). Cognitive function was evaluated using the mini-mental state examination (MMSE), Symbol Digit Modality Test (SDMT), Stroop word reading test (SWR), Stroop color naming test (SCN), Stroop interference test (SI), and Trail Making Test (TMT) A and B. Psychiatric symptoms were assessed by the Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Beck Depression Inventory (BDI), and the short version of Problem-Behavior Assessment (PBA-s). Furthermore, the rate of disease progression was presented as TFC score decline rate [TFC progression rate = (Baseline (TFC)-last following-up (TFC))/Time of following-up]. This was determined by calculating the number of points lost annually from diagnosis to last follow-up. Stages of HD were classified based on UHDRS-TFC score: early (Stage I, TFC 11–13), early-mid (Stage II, TFC 7–10), and advanced disease states (Stage III-V, TFC 0–6) (30). Based on the long survival time of patients with HD, we defined the loss-of-function state as death or TFC score of 0–2. The loss-of-function state was defined as the period from the date of disease diagnosis to death for a deceased patient, or from disease diagnosis in surviving patients to the time when TFC score reached 0–2 at the last follow-up. Death information was collected from family reports.

All participants in the study underwent routine blood tests upon admission to measure the count of white blood cells (WBC), including neutrophils, lymphocytes, monocytes, eosinophils, and basophils, as well as the count of red blood cells (RBC), hemoglobin levels, and platelets. Inflammatory markers (including NLR, PLR, LMR, and SII) were calculated. The NLR was calculated as the neutrophil count/lymphocyte count. PLR was calculated as the platelet count/lymphocyte count. LMR was calculated as the lymphocyte count/monocyte count. SII was calculated as the (neutrophil count*platelet count)/lymphocyte count (11). The increased levels of neutrophils, monocytes, NLR, PLR, and SII indicate higher innate immunity, while increased levels of lymphocytes and LMR indicate higher adaptive immunity (31).

Demographic and clinical data were analyzed with SPSS (version 20.0, IBM, United States), R studio, and Prism GraphPad version 9. p values < 0.05 were considered statistically significant. The data was presented using the following conventions: mean ± standard deviation (SD) for continuous data and frequency and percentage for categorical variables. To compare continuous variables between the HD and HC groups, either the Mann–Whitney U test or the Student’s t-test was utilized. Conversely, the chi-square test was employed to compare categorical variables. The age groups (<40, 40–50, and >50) were chosen based on the distribution of our study sample, which primarily included adults, with fewer adolescents and older individuals. There were less than five participants with a BMI < 18 or a BMI > 25. Therefore, participants were stratified based on their mean BMI and age of onset (<40, 40–50, >50 years) to ensure equal representation across different groups. Next, analyses were performed between groups of different genders (male and female patients), age of onset, disease stages, and mean BMI at recruitment (<20.73 and ≥20.73). To ensure a robust statistical approach, we have employed Analysis of Covariance (ANCOVA) to adjust for potential confounders such as sex, BMI, age of onset, as well as age and disease severity or CAG repeat length. These adjustments allow for a more accurate interpretation of the influence of age on the disease parameters studied. Either Pearson’s correlation test or Spearman’s correlation test was performed to assess the association between inflammatory markers and clinical characteristics, as well as disease progression. We employed a two-step regression analysis to evaluate the correlation between clinical characteristics and inflammatory indicators. Our first step involved conducting Pearson’s or Spearman’s correlation analysis for each inflammatory indicator. In the second step, we performed multivariate linear regression analyses by adjusting for age, sex, and CAG repeat length and the variables with a p-value < 0.05 from the previous step. We provided standardized β coefficients for the variables associated with each inflammatory indicator. The patients were categorized into three subgroups based on LMR, NLR, PLR, and SII tertiles. Similarly, patients were divided into three groups according to WBC and monocyte tertiles as follows: high WBC group (Group 1) [WBC counts ≥ 6.07*10⁹/L (n = 31)], medium WBC group (Group 2) [WBC counts > 4.84*10⁹/L but < 6.07*10⁹/L (n = 30)], and low WBC group (Group 3) [WBC counts ≤ 4.84*10⁹/L (n = 31)]; high monocyte group (Group1) [monocyte counts ≥0.39*10⁹/L (n = 31)], medium monocyte group (Group 2)[monocyte counts > 0.39*10⁹/L but <0.28*10⁹/L (n = 30)], and low monocyte group (Group 3) [monocyte counts ≤0.28*10⁹/L (n = 31)] We employed the Kaplan–Meier survival analysis and Breslow test to assess the prognostic significance of inflammatory indicators for the occurrence of loss-of-function. Furthermore, we executed univariate and multivariate survival analyses using the Cox proportional hazards regression model, adjusting for age, sex, and CAG repeat length with the multivariate Cox proportional hazards regression model.

Total of 92 HD patients with 38.04% males and 92 age, sex-matched HCs were enrolled in the study based on the inclusion and exclusion criteria. Baseline characteristics of the subjects are summarized in Table 1. The lack of TFC score at enrollment was excluded when analyzed by disease stage (n = 3). The participants were classified into 3 groups: Stage I (early HD, n = 21), Stage II (early-mid HD, n = 39), and Stage III-V (advanced HD, n = 29). The mean age of patients and age of onset were 54.27 ± 11.36 and 42.67 ± 10.04 years, respectively. The mean disease duration at baseline was 5.41 ± 3.93 years. The average length of CAG repeats was 44 (42–46). No significant differences were found in the age, sex, smoking, drinking, and BMI values between the HD patients and HCs (all p > 0.05).

The hematological data for patients with HD and HCs are presented in Table 2. HD patients exhibited lower levels of RBC count (4.50 ± 0.48 vs. 4.68 ± 0.40 10¹²/L, p = 0.007), hemoglobin (134.0 ± 17.20 vs.142.50 ± 14.86 g/L, p = 0.001), lymphocyte (1.67 ± 0.47 vs.1.90 ± 0.58 10⁹/L, p = 0.005), basophilia (0.02 ± 0.01 vs.0.03 ± 0.02 10⁹/L, p = 0.002), and LMR (5.13 ± 1.68 vs. 5.80 ± 2.11, p = 0.018) when compared to those of HCs. On the other hand, these patients had higher NLR (2.15 ± 0.90 vs. 1.71 ± 0.58, p = 0.0002), PLR (127.20 ± 51.59 vs. 111.0 ± 44.39, p = 0.024) and SII (420.40 ± 195.00 vs. 345.8 ± 1 61.8, p = 0.006) than those of HCs. The absolute leukocyte count, neutrophils, monocytes, and platelets were not significantly different between HD patients and HCs.

Next, we performed subgroup analyses based on sex, age of onset, disease stages, and mean BMI to explore the differences in inflammatory indicators in HD patients. When HD patients were stratified by sex, we found that the levels of RBCs, hemoglobin, WBCs, neutrophils and monocytes were higher in males than in females (all p < 0.05) (Figures 1A–E). Compared with females, NLR in males tends to increase (p = 0.056). Male patients with HD were found to have lower hemoglobin levels (146.60 ± 18.17 vs. 154.9 ± 12.24 g/L, p = 0.047) and higher NLR (2.37 ± 1.16 vs. 1.84 ± 0.61, p = 0.020) when compared to healthy male individuals. On the other hand, female HD patients had lower levels of RBC count (4.30 ± 0.33 vs. 4.48 ± 0.26 10¹²/L, p = 0.002), hemoglobin (126.40 ± 11.04 vs. 135.20 ± 8.52 g/L, p < 0.0001), lymphocyte (1.61 ± 0.46 vs. 1.89 ± 0.59 10⁹/L, p = 0.005), higher NLR (2.01 ± 0.67 vs. 1.67 ± 0.61, p = 0.007), and SII (399.30 ± 147.50 vs. 327.40 ± 143.10, p = 0.011) than healthy female individuals. There were no significant differences in inflammatory indicators stratified by TFC stage. Platelet levels were higher in patients with age of onset <40 years old than those between 40 and 50 years and those with age of onset >50 years (Figure 2A). The level of monocytes in patients with age of onset <40 and 40–50 years old were higher than that in patients with age of onset >50 years (Figure 2B). The NLR level of patients with age of onset of aged 40–50 years was higher than that of patients with age of onset of younger than 40 (Figure 2C). Patients with high BMI had significantly higher WBC counts than those with low BMI (Figure 1F). In the HD group, no significant differences in the PLR, LMR, and SII were found according to sex, age of onset, disease severity (based on TFC score) and BMI. More details are shown in Supplementary Tables S1–S3.

We further studied the correlation between the levels of inflammation indicators and clinical features using Pearson’s or Spearman’s correlation analysis. The detailed clinical characteristics of HD patients are shown in Supplementary Table S4. There was a significant correlation between NLR and age of onset (r = 0.225, p = 0.033), age of diagnosis (r = 0.209, p = 0.047), age of motor symptom onset (AAO) (r = 0.223, p = 0.035), SDMT (r = −0.278, p = 0.022). Lymphocytes negatively correlated with the age of onset (r = −0.274, p = 0.009) and AAO (r = −0.227, p = 0.032). PLR negatively correlated with age of onset (r = −0.219, p = 0.038) and AAO (r = −0.216, p = 0.041). Neutrophil was negatively correlated with HAMA scores (r = −0.526, p = 0.046). Monocyte was negatively correlated with UHDRS-TFC (r = −0.262, p = 0.014). LMR positively was correlated with HAMD scores (r = 0.334, p = 0.025) (Table 3). In addition, Pearson’s correlation analysis revealed that lymphocyte count (r = −0.286, p = 0.013), NLR (r = 0.295, p = 0.011), PLR (r = 0.231, p = 0.038), SII (r = 0.251, p = 0.027) were associated with a progression rate of HD (TFC progression rate) (Table 3). However, no associations were found between all the clinical features and the WBC count.

In the multivariate linear regression analysis, lymphocyte was negatively correlated with the age of onset (β = −0.114, p = 0.038). Monocyte negatively correlated with UHDRS-TFC (β = −0.281, p = 0.012). Additionally, progression rate of HD (TFC progression rate) was found to be significantly associated with lymphocyte count (β = −0.278, p = 0.027), NLR (β = 0.365, p = 0.005), PLR (β = 0.315, p = 0.012), and SII (β = 0.405, p = 0.002) (Table 4).

Total of 35 patients including 11 (11.96%) died HD patients and 24 patients (26.09%) with TFC scores of 0–2 at the end of the follow-up period were considered to have an outcome occurring. Our analysis using Kaplan–Meier analysis did not reveal significant differences when categorizing HD patients based on LMR, NLR, PLR, and SII subgroups. As detailed in Supplementary Table S5. Kaplan–Meier analysis presented in Figure 3A showed that the duration of the loss-of-function state was significantly different among the three WBC subgroups (Breslow p = 0.010). The duration of loss-of-function state in high WBC subgroup patients was shorter than those in medium WBC subgroup (Breslow p = 0.012) and low WBC subgroup (Breslow p = 0.034). There was no statistically significant difference in the duration of loss-of-function state between the medium WBC subgroup and the low WBC subgroup (Breslow p = 0.232). Furthermore, Figure 3B showed that the duration of loss-of-function state was significantly different among the three monocyte subgroups (Breslow p = 0.043). The duration of loss-of-function state in high monocyte subgroup patients was shorter than those in medium monocyte subgroup (Breslow p = 0.043) and low monocyte subgroup (Breslow p = 0.053). There was no statistically significant difference in the duration of loss-of-function state between the medium monocyte subgroup and the low monocyte subgroup (Breslow p = 0.570).

We further performed a multivariable Cox proportional hazards regression analysis to demonstrate the predictive significance of WBCs and monocytes on the occurrence of loss of function. Higher levels of WBCs (HR = 0.66, 95% CI, 0.42–1.05; p = 0.080) and monocytes (HR = 0.63, 95% CI, 0.39–1.01; p = 0.056) tend to increase the risk of disability and mortality in HD patients. Univariate Cox proportional hazards regression analysis for survival is shown in Supplementary Table S6. When WBCs and monocytes were stratified into three levels according to their tertiles, after adjusting for age, sex, and CAG repeat length, the hazard ratio for the medium WBC group compared with the high WBC group was 0.35 (HR = 0.35, 95% CI, 0.135–0.912; p = 0.032), the hazard ratio for low WBC group compared with high WBC group was 0.469 (HR = 0.469, 95% CI, 0.199–1.104; p = 0.083); the hazard ratio for medium monocyte group compared with high monocyte group was 2.506 (HR = 2.506, 95% CI, 1.037–6.053; p = 0.041), the hazard ratio for low monocyte group compared with high monocyte group was 0.867 (HR = 0.867, 95% CI, 0.324–2.316; p = 0.775). The highest WBCs and monocytes increased the risk of disability and mortality in patients with HD.