Инфекционные кишечные заболевания повышают риск нейродегенеративных заболеваний на основе общенационального исследования групп населения.

Introduction

Infectious intestinal disease (IID), characterized by the abrupt onset of diarrhoea and/or vomiting caused by microorganisms, is one of the most prevalent diseases worldwide 1 . IIDs are disseminated through faecal-oral transmission, with numerous risk factors, including the ingestion of microbe-contaminated food, inadequate access to clean water, and high levels of poverty 2 – 5 . Although the symptoms of most IIDs are mild or self-limiting, they constitute a leading cause of death in certain developing countries and incur significant economic costs in developed nations as well 6 , 7 . The immune system plays a crucial role in the clearance of these infectious agents. In the human body, 70–80% of immune cells are present in the gut, where they participate in intricate interactions with the gut microbiota and the intestinal epithelial layer 8 . This interaction forms a delicate balance that significantly affects and regulates host fitness, phenotype, and overall health 9 . This balance can be influenced by various factors, including genetics, dietary choices, lifestyle habits, infections, antibiotic therapies, and geographical region 10 , 11 . Dysbiosis, recognized as an imbalance within this intricate ecosystem, contributes to a range of human illnesses, including inflammatory bowel disease, metabolic disorders, musculoskeletal diseases, and psychiatric disorders 11 – 14 .

Recently, an unexpected trend was noted at the Tri-Service General Hospital in Taiwan, where patients diagnosed with IIDs frequently exhibited symptoms of neurodegenerative diseases. A previous study also indicated that patients with neurodegenerative diseases, such as Parkinson's disease (PD), report a higher incidence of intestinal disorders and digestive issues compared to healthy individuals 15 . This has prompted investigations into the potential association between IIDs and neurodegenerative diseases. Thus, we conducted a population-based cohort study to identify the interaction between IIDs and neurodegenerative diseases in a large general population of Taiwan using a longitudinal health insurance dataset selected from the National Health Insurance Research Database (NHIRD).

Materials and methods

Data source

This study conducted a population-based retrospective cohort analysis using a medical claims dataset from Taiwan’s National Health Insurance Research Database (NHIRD). Established in 1995, the National Health Insurance (NHI) program of Taiwan is a government-run mandatory enrolment initiative that covers approximately 99% of the country's population, totalling approximately 23 million individuals. The NHIRD offers comprehensive and high-quality data encompassing epidemiological research, diagnoses, prescription utilization, and healthcare information, such as inpatient and ambulatory claims, prescription claims, demographic details, and hospitalization records. It has been used extensively in academic research. The dataset used in this study was derived from the NHIRD, which serves as a robust research tool with diverse dimensions and provides valuable real-world evidence of medical practices in Taiwan. Pursuant to the Personal Information Protection Act, individual identifiers are encrypted before release for research. Diseases in the database were categorized according to the International Classification of Diseases, 9th Revision (ICD-9) codes.

In this study, we used data from the NHIRD to investigate the association between IIDs and neurodegenerative diseases over a 15-year period, from the total outpatient and inpatient Longitudinal Health Insurance Database (LHID) in Taiwan (2000–2015).

Study design and population

The study group comprised patients diagnosed with IID-related diagnosis between January 1, 2000, and December 31, 2015, identified through specific ICD-9-CM codes, including cholera (ICD-9-CM 001), typhoid and paratyphoid fever (ICD-9-CM 002), other salmonella infections (ICD-9-CM 003), shigellosis (ICD-9-CM 004), other bacterial food poisoning (ICD-9-CM 005), amoebiasis (ICD-9-CM 006), other protozoal intestinal diseases (ICD-9-CM 007), intestinal infections due to other organisms (ICD-9-CM 008), and ill-defined intestinal infections (ICD-9-CM 009). Each enrolled IIDs patient was required to receive a diagnosis in an inpatient setting or at three or more outpatient visits within the one-year study period for symptomatic IIDs according to these ICD-9-CM codes. The date of the IIDs diagnosis was defined as the index date. Detailed information regarding the specific ICD-9-CM codes used in this study is provided in the Supplemental Digital Content (Table S1).

The exclusion criteria included patients with a history of IIDs before the index date, individuals diagnosed with neurodegenerative diseases before the start of tracking, patients lacking tracking data, and those of unknown age or sex. Consequently, 99,146 patients with IIDs were identified and included in the study group. For each IID patient, two controls without a history of IIDs, which were frequency-matched for the exact age, sex, and index year in the control group (N = 198,292), were enrolled in this study.

Covariates

The covariates include sociodemographic and comorbidities. The sociodemographic characteristics considered in this study included sex, age, low income (in New Taiwan Dollars (NT$): < 18,000), season, location (north, middle, south, and east of Taiwan), degree of urbanization (levels 1 to 4), and level of care (medical center, regional, local hospital, and clinic). The level of urbanization was determined by population size and various indicators reflecting the city's development status. Urbanization level 1 was characterized by cities with populations exceeding 1,250,000 and a high degree of political, economic, cultural, and metropolitan development. Urbanization level 2 included cities with populations between 500,000 and 1,250,000, playing significant roles in Taiwan's political, economic, and cultural spheres. Urbanization levels 3 and 4 were defined by populations ranging from 150,000 to 500,000 and less than 150,000, respectively.

The comorbidities of patients that may developed neurodegenerative disease were gathered and studied as the predictor, and they included diabetes mellitus (DM) (ICD-9-CM code: 250), hypertension (HTN, ICD-9-CM codes:401, 404, and 405), depression (ICD-9-CM code: 296.2–296.3, 296.82, 300.4, 311), chronic kidney disease (CKD, ICD-9-CM code: 585), congestive heart failure (CHF, ICD-9-CM code: 428), chronic obstructive pulmonary disease (COPD, ICD-9-CM code: 490–496), hyperlipidaemia (ICD-9-CM code: 272), and systemic lupus erythematosus (SLE, ICD-9-CM code: 710).

Main outcome measures

All the study participants were followed-up from the index date until the onset of all recorded neurodegenerative diseases in the NHIRD. The incidence and risk of neurodegenerative diseases, including Alzheimer’s disease, Parkinson's disease, Huntington’s chorea, amyotrophic lateral sclerosis, multiple sclerosis (MS), and other neurodegeneration associated disorders, were compared between the study and control groups.

Statistical analysis

All statistical analyses were performed using SPSS software (version 22.0; SPSS, Chicago, IL, USA). The distribution of sociodemographic data and comorbidities was compared between the study group (with IID) and the control group (without IID) using the chi-square test to examine the categorical variables and the t-test to examine the continuous variables. Differences in the risk of neurodegenerative diseases in the study and control groups were evaluated using the Kaplan–Meier method with a log-rank test and presented as the cumulative risk. A Cox proportional hazards regression analysis was used to determine the risk of psychiatric disorders, and the data were expressed as adjusted hazard ratios (aHR) with 95% confidence intervals (CI). Detailed information on the ICD-9-CM codes used in this study is provided in Supplemental Digital Content (Table S1).

Ethics statement

This study was approved by the Institutional Review Board of the Tri-Service General Hospital (TSGHIRB No. E202416008), complied with the ethical standards of the institutional and/or national research committee and the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Results

Demographic characteristics of the study population at the baseline and the endpoint

In total, 297,438 patients were enrolled in this study, including 99,146 patients with IID and 198,292 patients without IID (Fig. 1 ). The demographic characteristics of the study and control groups at the beginning of the study are presented in Table 1 . There were no significant differences in age between the groups. The majority of the patients were aged 20–39 years. The lower limit in the first age group (age < 20), the maximum age in the last age group (age ≧65), and the years of follow-up are presented in Table S2. Fig. 1 Flowchart of participant selection (nested case–control study) from the National Health Insurance Research Database in Taiwan. Table 1 Characteristics of study in the baseline. IID Total With Without P Variables n % n % n % Total 297,438 99,146 33.33 198,292 66.67 Gender 0.999 Male 139,407 46.87 46,469 46.87 92,938 46.87 Female 158,031 53.13 52,677 53.13 105,354 53.13 Age (years) 36.99 ± 19.94 36.68 ± 20.42 37.14 ± 19.69 < 0.001 Age groups (yrs)* < 0.001 10–20 63,412 21.32 23,020 23.22 40,392 20.37 20–39 106,427 35.78 34,819 35.12 71,608 36.11 40–64 95,230 32.02 29,980 30.24 65,250 32.91 65–90 32,369 10.88 11,327 11.42 21,042 10.61 Low-income < 0.001 Without 296,439 99.66 98,700 99.55 197,739 99.72 With 999 0.34 446 0.45 553 0.28 DM < 0.001 Without 250,109 84.09 79,031 79.71 171,078 86.28 With 47,329 15.91 20,115 20.29 27,214 13.72 HTN < 0.001 Without 220,503 74.13 68,644 69.24 151,859 76.58 With 76,935 25.87 30,502 30.76 46,433 23.42 Depression < 0.001 Without 269,858 90.73 86,063 86.80 183,795 92.69 With 27,580 9.27 13,083 13.20 14,497 7.31 CKD < 0.001 Without 287,213 96.56 94,123 94.93 193,090 97.38 With 10,225 3.44 5,023 5.07 5,202 2.62 CHF < 0.001 Without 283,839 95.43 92,832 93.63 191,007 96.33 With 13,599 4.57 6,314 6.37 7,285 3.67 COPD < 0.001 Without 188,808 63.48 53,422 53.88 135,386 68.28 With 108,630 6.52 45,724 46.12 62,906 31.72 Hyperlipidemia < 0.001 Without 220,975 74.29 67,715 68.30 153,260 77.29 With 76,463 25.71 31,431 31.70 45,032 22.71 SLE < 0.001 Without 285,320 95.93 93,557 94.36 191,763 96.71 With 12,118 4.07 5,589 5.64 6,529 3.29 Season < 0.001 Spring (Mar-May) 95,607 32.14 25,111 25.33 70,496 35.55 Summer (Jun-Aug) 54,433 18.30 22,283 22.47 32,150 16.21 Autumn (Sep-Nov) 74,329 24.99 22,089 22.28 52,240 26.34 Winter (Dec-Feb) 73,069 24.57 29,663 29.92 43,406 21.89 Location 0.003 Northern Taiwan 80,637 27.11 24,731 24.94 55,906 28.19 Middle Taiwan 30,816 10.36 11,229 11.33 19,587 9.88 Southern Taiwan 47,636 16.02 17,557 17.71 30,079 15.17 Eastern Taiwan 3,457 1.16 1,096 1.11 2,361 1.19 Missing 134,892 45.35 44,533 44.92 90,359 45.57 Urbanization level 0.002 1 (The highest) 44,081 14.82 13,573 13.69 30,508 15.39 2 52,214 17.55 18,197 18.35 34,017 17.16 3 50,870 17.10 17,528 17.68 33,342 16.81 4 (The lowest) 15,214 5.12 5,255 5.30 9,959 5.02 Missing 135,059 45.41 44,593 44.98 90,466 45.62 Level of care < 0.001 Hospital center 14,058 4.73 3,454 3.48 10,604 5.35 Regional hospital 22,966 7.72 6,915 6.97 16,051 8.09 Local hospital 25,872 8.70 9,737 9.82 16,135 8.14 Clinic 234,542 78.85 79,040 79.72 155,502 78.42 P: Chi-square/Fisher exact test on category variables and t-test on continue variables. *The minimum age with IID is 10.65, the maximum age is 89.72. The minimum age without IID is 10.89, the maximum age is 89.63.

The study group had a higher prevalence of DM, HTN, depression, CKD, CHF, COPD, hyperlipidaemia, and SLE. Furthermore, patients with IID tended to live in the north of Taiwan and seek medical treatment from the clinic. The demographic characteristics of the study and control groups at the tracking endpoint are described in Table S3 and all characteristics of patients with and without IIDs were similar to those observed at baseline.

Association of IIDs with neurodegenerative diseases

The incidence of neurodegenerative diseases was higher in the study group (3664 patients, 3.7%) than in the control group (4973 patients, 2.5%) ( P < 0.001) (Table 2 ). In addition, a Kaplan–Meier analysis for the cumulative risk of neurodegenerative disease during the 16 years of follow-up showed a statistical difference between the study group compared to the control group (log-rank P < 0.001). This difference was observed during the first year of tracking (Fig. 2 ). The median duration from the diagnosis of IIDs to the onset of neurodegenerative disease was 9.39 years (Supplemental Digital Content (Table S4). Furthermore, the incidence of some subgroups of neurodegenerative diseases was significantly higher in the study group than in the control group, including Parkinson's disease (0.97% vs. 0.65%; P < 0.001) and other neurodegeneration-associated disorders (2.92% vs. 1.93%; P < 0.001). Table 2 Characteristics of study in the endpoint. IID Total With Without P Variables n % n % n % Total 297,438 99,146 33.33 198,292 66.67 Neurodegenerative disease < 0.001 Without 288,801 97.10 95,482 96.30 193,319 97.49 With 8,637 2.90 3,664 3.70 4,973 2.51 Alzheimer’s disease (331.0) 0.085 Without 296,948 99.84 98,963 99.82 197,985 99.85 With 490 0.16 183 0.18 307 0.15 Parkinson's disease (332.0–332.1) < 0.001 Without 295,186 99.24 98,181 99.03 197,005 99.35 With 2,252 0.76 965 0.97 1,287 0.65 Huntington’s chorea (333.4) 0.663 Without 297,431 100.00 99,143 100.00 198,288 100.00 With 7 0.00 3 0.00 4 0.00 Amyotrophic Lateral Sclerosis (335.20) 0.782 Without 297,409 99.99 99,137 99.99 198,272 99.99 With 29 0.01 9 0.01 20 0.01 Multiple sclerosis (340) 0.059 Without 297,345 99.97 99,104 99.96 198,241 99.97 With 93 0.03 42 0.04 51 0.03 Other neurodegeneration associated disorders (330–337 excluding listed above) < 0.001 Without 290,718 97.74 96,255 97.08 194,463 98.07 With 6,720 2.26 2,891 2.92 3,829 1.93 Fig. 2 Kaplan–Meier for cumulative risk of neurodegenerative diseases stratified by IID with log-rank test. IID = intestinal infectious diseases.

Table 3 shows the Cox regression analysis of the risk factors for neurodegenerative diseases. A significantly higher risk of developing neurodegenerative diseases was observed in the IIDs cohort. The crude HR was 1.532 (95% CI = 1.466–1.600, P < 0.001), and after adjusting for age, sex, comorbidities, geographical area of residence, urbanization level of residence, and monthly income, the adjusted OR was 1.144 (95% CI = 1.093–1.198, P < 0.001). In addition, age group ≥ 20, patients with HTN, depression, COPD, SLE, and CKD also had an increased risk of developing neurodegenerative diseases. Table 3 Factors of neurodegenerative disease by using Cox regression. Variables Crude HR 95% CI lower limit 95% CI upper limit P Adjusted HR 95% CI lower limit 95% CI upper limit P IID Without Reference Reference With 1.532 1.466 1.600 < .0001 1.144 1.093 1.198 < .0001 Gender Male 0.920 0.880 0.962 < 0.001 0.967 0.925 1.012 0.151 Female Reference Reference Age groups (yrs)* 10–20 Reference Reference 20–39 1.613 1.424 1.826 < .0001 1.520 1.341 1.723 < .0001 40–64 2.772 2.464 3.118 < .0001 1.573 1.392 1.777 < .0001 65–90 11.833 10.544 13.279 < .0001 1.985 1.746 2.256 < .0001 Low-income Without Reference Reference With 2.150 1.619 2.854 < .0001 1.010 0.759 1.344 0.946 DM Without Reference Reference With 3.310 3.165 3.463 < .0001 1.041 0.987 1.098 0.137 HTN Without Reference Reference With 4.302 4.114 4.499 < .0001 1.154 1.085 1.226 < .0001 Depression Without Reference Reference With 3.851 3.669 4.043 < .0001 1.295 1.231 1.363 < .0001 CKD Without eference Reference With 4.197 3.922 4.491 < .0001 1.051 0.978 1.129 0.176 CHF Without Reference Reference With 5.049 4.765 5.350 < .0001 0.949 0.890 1.011 0.106 COPD Without Reference Reference With 2.472 2.365 2.585 < .0001 1.143 1.089 1.199 < .0001 Hyperlipidemia Without Reference Reference With 2.670 2.556 2.789 < .0001 1.006 0.955 1.061 0.810 SLE Without Reference Reference With 1.916 1.765 2.079 < .0001 0.919 0.845 0.999 0.047 Season Spring Reference Reference Summer 0.934 0.879 0.992 0.026 0.958 0.902 1.018 0.171 Autumn 0.935 0.879 0.994 0.032 0.944 0.888 1.004 0.069 Winter 0.014 0.013 0.015 < 0.001 0.019 0.018 0.020 < .0001 Location Multicollinearity with urbanization level Northern Taiwan Reference Multicollinearity with urbanization level Middle Taiwan 1.133 1.047 1.227 0.002 Multicollinearity with urbanization level Southern Taiwan 1.261 1.180 1.348 < .0001 Multicollinearity with urbanization level Eastern Taiwan 1.240 1.027 1.496 0.025 Multicollinearity with urbanization level Urbanization level 1 (The highest) 0.605 0.548 0.668 .0001 0.876 0.792 0.968 0.010 2 0.683 0.621 0.751 < .0001 0.900 0.817 0.990 0.030 3 0.697 0.634 0.767 < .0001 0.930 0.845 1.024 0.138 4 (The lowest) Reference Reference Level of care Hospital center 1.585 1.457 1.724 < .0001 1.055 0.969 1.149 0.218 Regional hospital 1.429 1.330 1.535 < .0001 0.999 0.929 1.074 0.975 Local hospital 1.612 1.510 1.721 < .0001 0.994 0.930 1.061 0.847 Clinic Reference Reference HR, hazard ratio; CI, confidence interval; Adjusted HR, Adjusted variables listed in the table. *The minimum age with IID is 10.65, the maximum age is 89.72. The minimum age without IID is 10.89, the maximum age is 89.63.

Risk of neurodegenerative diseases in the IIDs group stratified by covariates

The risk of neurodegenerative diseases in patients with IIDs was analyzed using Cox regression and presented as aHR with reference to the control group (Table 4 ). The overall incidence of neurodegenerative diseases was 491.58 per 100,000 person-years in the study cohort and 364.86 per 100,000 person-years in the control cohort in subgroup analysis comparing patients with and without IIDs (Table 4 ). All patients with IIDs had a higher risk of developing neurodegenerative diseases irrespective of their stratification by independent variables. IIDs were linked to an elevated risk of neurodegenerative disease in both female and male patients (1.135 in the corresponding age group of women, P < 0.001; 1.151 in the corresponding age group of males, P < 0.001). On age group analysis, the presence of IIDs in all age groups was independently associated with an increased risk of neurodegenerative disease diagnosis relative to the absence of IIDs (aOR = 1.463, P < 0.001 in < 20, aOR = 1.126, P < 0.001 in 20–39, aOR = 1.133, P < 0.001 in 40–64, aOR = 1.130, P < 0.001 in ≥ 65 years), and patients aged < 20 years had the highest risk. In the pre-existing condition group analysis, patients with IIDs showed an increased risk of developing neurodegenerative diseases, regardless of whether they had DM, HTN, depression, CKD, CHF, COPD, or hyperlipidaemia (aOR = 1.108–1.233, all P < 0.001). Table 4 Factors of neurodegenerative disease stratified by variables listed in the table by using Cox regression. IID With Without ( Reference ) With vs. Without ( Reference ) Stratified Events PYs Rate (per 10 5 PYs) Events PYs Rate (per 10 5 PYs) Adjusted HR 95% CI lower limit 95% CI upper limit P Overall 3,664 745,356.05 491.58 4,973 1,363,004.82 364.86 1.144 1.093 1.198 < .0001 Gender Male 1,569 348,390.27 450.36 2,263 633,513.26 357.21 1.151 1.074 1.233 < .0001 Female 2,095 396,965.77 527.75 2,710 729,491.56 371.49 1.135 1.068 1.207 < .0001 Age group (yrs)* 10–20 133 87,794.81 151.49 224 161,420.10 138.77 1.463 1.139 1.880 0.003 20–39 578 261,197.72 221.29 802 462,599.22 173.37 1.126 1.002 1.265 0.046 40–64 1,154 277,572.00 415.75 1,508 532,999.12 282.93 1.133 1.043 1.231 0.003 65–90 1,799 118,791.52 1,514.42 2,439 205,986.38 1,184.06 1.130 1.058 1.207 0.000 Low-income Without 3,635 742,418.25 489.62 4,950 1,359,587.02 364.08 1.142 1.091 1.196 < .0001 With 29 2,937.80 987.13 23 3,417.80 672.95 1.942 0.893 4.224 0.094 DM Without 2,059 597,170.02 344.79 3,298 1,170,489.22 281.76 1.136 1.072 1.205 < .0001 With 1,605 148,186.03 1,083.10 1,675 192,515.61 870.06 1.146 1.065 1.233 0.000 HTN Without 1,365 521,058.75 261.97 2,120 1,033,313.03 205.17 1.156 1.075 1.242 < .0001 With 2,299 224,297.30 1,024.98 2,853 329,691.79 865.35 1.134 1.069 1.203 < .0001 Depression Without 2,398 647,534.32 370.33 3,827 1,262,331.39 303.17 1.141 1.081 1.205 < .0001 With 1,266 97,821.73 1,294.19 1,146 100,673.43 1,138.33 1.136 1.042 1.238 0.004 CKD Without 3,134 711,924.00 440.22 4,513 1,327,580.88 339.94 1.130 1.076 1.186 < .0001 With 530 33,432.04 1,585.31 460 35,423.95 1,298.56 1.233 1.079 1.410 0.002 CHF Without 2,932 703,705.36 416.65 4,232 1,315,333.32 321.74 1.133 1.077 1.191 < .0001 With 732 41,650.68 1,757.47 741 47,671.50 1,554.39 1.180 1.057 1.318 0.003 COPD Without 1,238 398,960.05 310.31 2,370 928,120.34 255.35 1.188 1.104 1.278 < .0001 With 2,426 346,396.00 700.35 2,603 434,884.48 598.55 1.114 1.051 1.181 0.000 Hyperlipidemia Without 1,593 507,496.61 313.89 2,832 1,038,527.16 272.69 1.108 1.039 1.183 0.002 With 2,071 237,859.44 870.68 2,141 324,477.66 659.83 1.186 1.111 1.266 < .0001 SLE Without 3,312 703,042.35 471.10 4,672 1,317,215.81 354.69 1.149 1.095 1.205 < .0001 With 352 42,313.70 831.88 301 45,789.01 657.36 1.070 0.905 1.264 0.428 Season Spring 955 16,924.70 5,642.64 1,325 23,254.39 5,697.85 1.124 1.028 1.229 0.010 Summer 913 17,089.78 5,342.37 1,319 23,182.87 5,689.55 1.090 0.995 1.193 0.063 Autumn 930 17,044.40 5,456.34 1,172 21,681.09 5,405.63 1.071 0.975 1.177 0.154 Winter 866 694,297.17 124.73 1,157 1,294,886.46 89.35 1.264 1.150 1.390 < .0001 Urbanization level 1 (The highest) 471 109,620.66 429.66 739 217,578.41 339.65 1.005 0.887 1.139 0.939 2 661 140,962.10 468.92 840 240,547.23 349.20 1.109 0.992 1.239 0.068 3 693 135,022.31 513.25 811 238,605.62 339.89 1.151 1.031 1.284 0.012 4 (The lowest) 278 40,196.93 691.60 358 73,927.30 484.26 1.199 1.010 1.422 0.038 Level of care Hospital center 183 25,314.36 722.91 419 78,782.34 531.85 1.234 1.027 1.482 0.025 Regional hospital 301 56,217.72 535.42 565 117,693.41 480.06 0.991 0.857 1.147 0.908 Local hospital 465 74,173.13 626.91 606 120,215.12 504.10 0.888 0.781 1.009 0.068 Clinic 2,715 589,650.84 460.44 3,383 1,046,313.96 323.33 1.202 1.138 1.271 < .0001 PYs, Person-years; Adjusted HR, Adjusted Hazard ratio: Adjusted for the variables listed in Table 3 ; CI, confidence interval. *The minimum age with IID is 10.65, the maximum age is 89.72. The minimum age without IID is 10.89, the maximum age is 89.63.

Risk of the subgroups of neurodegenerative diseases in patients with IIDs

The main subgroups of neurodegenerative diseases were also examined in the patients with IIDs (Table 5 ). Compared with the control group, patients with IIDs had a higher risk of Parkinson's disease (aHR = 1.145; 95% CI: 1.046–1.253; P = 0.003), MS (aHR = 1.905; 95% CI: 1.175–3.088; P = 0.009), and other neurodegeneration associated disorders (aHR = 1.167; 95% CI: 1.108–1.229; P < 0.0001). A sensitivity test was used to exclude the first year of onset and a similar result was observed. After excluding the first 5 years of onset, only MS (aHR = 1.832; 95% CI: 1.070–3.137; P = 0.027) and other neurodegeneration associated disorders (aHR = 1.130; 95% CI: 1.066–1.197; P < 0.0001) showed significant results. Table 5 Sensitivity test for factors of neurodegenerative disease subgroup by using Cox regression. Sensitivity test IID With Without (Reference) neurodegenerative disease subgroup Events PYs Rate (per 10 5 PYs) Events PYs Rate (per 10 5 PYs) Adjusted HR 95% CI lower limit 95% CI upper limit P Overall Overall 3,664 745,356.05 491.58 4,973 1,363,004.82 364.86 1.144 1.093 1.198 < 0.0001 Alzheimer’s disease (331.0) 183 747,448.69 24.48 307 1,365,277.08 22.49 0.934 0.766 1.140 0.503 Parkinson's disease (332.0–332.1) 965 746,553.08 129.26 1,287 1,364,485.45 94.32 1.145 1.046 1.253 0.003 Huntington’s chorea (333.4) 3 747,588.07 0.40 4 1,365,577.73 0.29 1.015 0.212 4.854 0.986 Amyotrophic Lateral Sclerosis (335.20) 9 747,592.33 1.20 20 1,365,565.62 1.46 0.854 0.330 2.209 0.744 Multiple sclerosis (340) 42 747,593.14 5.62 51 1,365,560.79 3.73 1.905 1.175 3.088 0.009 Other neurodegeneration associated disorders (330–337 excluding listed above) 2,891 746,191.72 387.43 3,829 746,191.72 513.14 1.167 1.108 1.229 < 0.0001 First 1 year exclude Overall 3,486 741,353.61 470.22 4,200 1,356,245.59 309.68 1.124 1.073 1.178 < 0.0001 Alzheimer’s disease (331.0) 176 743,504.80 23.67 268 1,358,563.60 19.73 0.919 0.751 1.125 0.413 Parkinson's disease (332.0–332.1) 896 742,584.34 120.66 1,099 1,357,754.44 80.94 1.108 1.010 1.216 0.030 Huntington’s chorea (333.4) 3 743,647.06 0.40 4 1,358,866.03 0.29 1.015 0.212 4.854 0.986 Amyotrophic Lateral Sclerosis (335.20) 9 743,651.31 1.21 16 1,358,853.92 1.18 0.887 0.337 2.335 0.808 Multiple sclerosis (340) 41 743,651.94 5.51 41 1,358,848.48 3.02 1.939 1.188 3.165 0.008 Other neurodegeneration associated disorders (330–337 excluding listed above) 2,776 742,213.96 374.02 3,234 1,357,298.80 238.27 1.152 1.093 1.215 < 0.0001 First 5 years exclude Overall 2,798 660,244.49 423.78 3,386 1,211,186.15 279.56 1.108 1.052 1.167 < 0.0001 Alzheimer’s disease (331.0) 137 662,618.12 20.68 188 1,213,869.55 15.49 0.949 0.749 1.203 0.665 Parkinson's disease (332.0–332.1) 676 661,562.37 102.18 845 1,212,957.53 69.66 1.099 0.988 1.222 0.083 Huntington’s chorea (333.4) < 3 662,784.80 ─ 3 1,214,276.44 0.25 0.585 0.052 6.539 0.663 Amyotrophic Lateral Sclerosis (335.20) 7 662,789.55 1.06 9 1,214,264.41 0.74 1.311 0.352 4.890 0.687 Multiple sclerosis (340) 35 662,791.94 5.28 35 1,214,253.22 2.88 1.832 1.070 3.137 0.027 Other neurodegeneration associated disorders (330–337 excluding listed above) 2,275 661,211.10 344.07 2,678 1,212,442.38 220.88 1.130 1.066 1.197 < 0.0001 PYs, Person-years; Adjusted HR, Adjusted Hazard ratio: Adjusted for the variables listed in Table 3 ; CI, confidence interval.

Increased risk of neurodegenerative diseases in patients with refractory IIDs

We evaluated the risk of neurodegenerative diseases in patients with IIDs who sought medical assistance at least once (Table 6 ). Compared to the control group, the study group showed a positive correlation between the overall risk of neurodegenerative diseases and frequency of medical visits. Among these patients, those who sought medical attention 2 times for IIDs had a higher overall risk of neurodegenerative diseases (aHR = 1.258; 95% CI: 1.127–1.403; P < 0.0001) than those who sought medical help only once (aHR = 1.223; 95% CI: 1.146–1.305; P < 0.0001). Table 6 Factors of neurodegenerative disease among different IID visits model by using Cox regression. IID visits Populations Events PYs Rate (per 10 5 PYs) Adjusted HR 95% CI lower limit 95% CI upper limit P Without IID 198,292 4,973 1,363,004.82 364.86 Reference With IID 99,146 3,664 745,356.05 491.58 1.144 1.093 1.198 < .0001 IID 1 visits 64,349 2,092 451,842.61 462.99 1.223 1.146 1.305 < .0001 IID 2 visits 17,319 695 137,780.14 504.43 1.258 1.127 1.403 < .0001 IID 1–2 visits 81,668 2,787 589,622.74 472.68 1.233 1.166 1.303 < .0001 IID ≧3 visits 17,478 877 155,733.30 563.14 1.097 0.995 1.209 0.063 PYs, Person-years; Adjusted HR, Adjusted Hazard ratio: Adjusted for the variables listed in Table 3 . CI, confidence interval.

Impact of IID subtypes on neurodegenerative disease risk

We further evaluated the impact of different subtypes of IIDs on the risk of developing neurodegenerative diseases. The results demonstrated that certain subtypes were significantly associated with an increased risk of neurodegenerative diseases (Table 7 ). Notably, patients with bacterial food poisoning (aHR = 1.096; 95% CI: 1.004–1.145; P = 0.047), amebiasis (aHR = 2.702; 95% CI: 1.291–3.590; P < 0.0001), protozoal intestinal diseases (aHR = 1.257; 95% CI: 1.193–1.318; P < 0.0001), and IID due to other organisms (aHR = 1.194; 95% CI: 1.140–1.247; P < 0.0001) exhibited a significantly higher risk compared to other subtypes. Table 7 Factors of neurodegenerative disease among different IIDs by using Cox regression. IID visits Populations Events PYs Rate (per 10 5 PYs) Adjusted HR 95% CI lower limit 95% CI upper limit P Cholera 1 0 7.18 0.00 –* – – – Typhoid and paratyphoid fevers 7 0 52.67 0.00 –* – – – Salmonella infections 1,797 6 1,367.40 438.79 1.021 0.976 1.071 0.089 Shigellosis 29 1 225.38 443.70 1.033 0.987 1.082 0.074 Bacterial food poisoning 48,972 1,730 368,357.11 469.65 1.096 1.004 1.145 0.047 Amebiasis 5 1 37.86 2,641.31 2.702 1.291 3.590 < 0.0001 Protozoal intestinal diseases 1,235 50 9,287.15 538.38 1.257 1.193 1.318 < 0.0001 IID due to other organisms 47,100 1,876 366,021.30 512.54 1.194 1.140 1.247 < 0.0001 PYs, Person-years; Adjusted HR, Adjusted Hazard ratio: Adjusted for the variables listed in Table 3 ; CI, confidence interval. *For diseases such as Cholera and Typhoid and paratyphoid fevers, there were no recorded events.

Discussion

To the best of our knowledge, this is the first large-scale population-based study of Asian individuals to investigate the interaction between IIDs and neurodegenerative diseases. In this study, patients with IIDs had a higher overall risk of neurodegenerative diseases, with an aHR of 1.144, than those without IIDs. This indicates that patients with IIDs have a 1.144-fold increased risk of developing neurodegenerative diseases.

IIDs are characterized by gastrointestinal tract infections caused by various pathogens, including bacteria, viruses, and parasites. Infectious diseases can induce significant changes in the gut microbiota by influencing the gut function and immunity. Conversely, inflammation resulting from alterations in the gut microbiota may exacerbate infectious diseases 16 . Disruption of the gut microbiota ecosystem has numerous consequences, including disturbances in the gut barrier and imbalances in the immune, metabolic, and central nervous system (CNS) of the host 17 . In recent years, the relationship between the enteric system and the CNS, termed the gut-brain axis or brain-gut-microbiome axis, has attracted significant attention 18 . The gut-brain axis constitutes a bidirectional communication system that facilitates interactions between gut microbes and the brain and intestine. The signalling mechanisms in this system are intricate, encompassing metabolic, immune, neuronal, and endocrine signalling pathways 19 , 20 . Previous studies have reported that the interplay of gut microbiota with the CNS has a crucial impact on the onset and progression of neurodegenerative disorders and CNS tumours in certain cases 21 . Moreover, as there is a symbiotic relationship between the gut microbiota and the host, their dynamic and disrupted interaction can have extensive effects on the host health, potentially resulting in cortical damage 22 , 23 . The potential pathological mechanism may involve microbiota dysbiosis, leading to the release of compounds by intestinal bacteria that activate the triggering receptors expressed on myeloid cells in macrophages 24 . This activation triggers an exaggerated proinflammatory response, ultimately damaging the gut barrier. Subsequently, TREM-positive activated macrophages, along with inflammatory mediators, may transit to the brain through various routes, such as the blood, glymphatic system, circumventricular organs, or the vagus nerve via the gut-brain axis. This process initiates a systemic inflammatory response that compromises the blood–brain barrier, further exacerbating TREM-dependent neuroinflammation, and ultimately resulting in neural injury. Therefore, a correlation between gut dysbiosis and the occurrence of neurodegenerative diseases has been observed. However, it remains unclear whether dysbiosis is induced by neurodegeneration or a consequence of the progression of neurodegenerative conditions 25 .

In this study, we observed a significantly higher risk of Parkinson's disease and MS in patients with IIDs; however, no significant increase was found in the incidence of other neurodegenerative diseases. Parkinson's disease is characterized by the degeneration of dopaminergic neurons located in the substantia nigra of the brain, resulting in reduced dopamine levels. Research studies have inferred that the first signs of PD appear in the form of gastrointestinal abnormalities (constipation), usually several years before the onset of locomotor signs 26 , 27 . This notion is supported by pathophysiologic evidence that α-Synuclein inclusions appear early in the enteric nervous system, and propagates via the vagus nerve to the brain in a prion-like fashion 26 , 28 . MS is characterized by the demyelination of nervous cells, which leads to neurodegeneration. The gut microbiota excrete neurotransmitters, such as GABA, histamine, serotonin, and dopamine; cytokines; and abnormal metabolites, which can potentially trigger inflammation through sympathetic or parasympathetic pathways, leading to demyelination and neurodegeneration. Recent studies have indicated an association between the development of Alzheimer’s disease and alterations in the gut microbiota. However, no significant increase in risk was observed in the present study. The possible reasons for this may be related to pathogenic mechanisms. The pathology of Alzheimer's disease is defined by the intracellular accumulation of neurofibrillary tangles composed of hyper-phosphorylated τ protein and extracellular plaques consisting of amyloid-β peptides 29 . The production and accumulation of these pathological features typically commences at approximately 40 years of age; however, it may take more than 20 years for them to manifest cognitive impairment 30 . It is possible that the relatively short follow-up period may not have been sufficient to demonstrate a significant increase in the risk of Alzheimer's disease (AD) among patients with IIDs.

According to our study findings, we observed a positive correlation between the overall risk of neurodegenerative diseases and the frequency of medical visits among the IIDs group. Specifically, patients who sought medical attention twice had a higher risk of developing neurodegenerative diseases than those who sought medical attention only once. However, no significant differences were observed after three or more medical visits. A possible explanation is that the symptoms gradually improved after the second medical visit, preventing most patients from seeking further medical attention. Consequently, there were fewer events in the data, which may explain the lack of statistical significance beyond two medical visits.

Microbiological testing is considered the gold standard for diagnosing IID. However, causative organisms have only been identified in 37–46% of samples from symptomatic individuals 1 , 31 . Furthermore, a previous article discussed treatment-seeking expectations for IIDs, indicating that only 1 in 50 individuals sought medical consultation, possibly because of the perception that the disease is typically mild and self-limiting 32 . However, we should not underestimate the importance of early treatment for IIDs, even if symptom improvement is quickly anticipated. Early treatment not only allows for an understanding of the underlying causes of symptoms, but also facilitates epidemic management, thereby potentially enabling the early mitigation of the risk of neurodegenerative diseases.

There are several limitations to this study. First, although we identified patients with IIDs using insurance claims data, this dataset lacks information on the severity, progression, or daily impact of these conditions. Due to the study’s reliance on claims data, we could only estimate disease severity by counting the number of medical visits, without being able to distinguish specific clinical presentations. Additionally, the NHIRD does not contain data on specific IID pathogens, limiting our ability to examine how different pathogens may influence the risk of neurodegenerative diseases. Second, other residual confounding factors, such as genetic background, dietary habits, smoking, alcohol and coffee consumption, and pesticide exposure, which could affect neurodegenerative disease risk, are also not included in the NHIRD. As the NHIRD lacks imaging and laboratory data, we relied on board-certified psychiatrists and neurologists for diagnoses of neurodegenerative conditions without confirming specific pathological characteristics. Third, our study included an age group of patients under 20, with the youngest enrolled patient being 10 years old. Although the 13-year follow-up period allows for extensive observation, childhood neurodegenerative diseases—such as Huntington’s disease, amyotrophic lateral sclerosis (ALS), and neuronal ceroid lipofuscinosis—are often influenced by genetic factors. Thus, we cannot exclude the potential impact of genetic predispositions in this age group.

Conclusion

This retrospective cohort study conducted in Taiwan highlighted a significant association between infectious intestinal diseases (IIDs) and the risk of neurodegenerative diseases. These findings underscore the importance of early detection and management of IIDs, not only for symptom relief but also for potential long-term neurological health outcomes. Further research is warranted to elucidate the underlying mechanisms linking IIDs and neurodegeneration, thereby paving the way for targeted interventions and preventive strategies.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Abbreviations

Infectious intestinal disease

National Health Insurance Research Database

International Classification of Diseases, 9th Revision

Diabetes mellitus

Hypertension

Chronic kidney disease

Congestive heart failure

Chronic obstructive pulmonary disease

Systemic lupus erythematosus

Multiple sclerosis

Confidence intervals

Central nervous system

Parkinson’s disease

Alzheimer’s disease

The original online version of this Article was revised: In the original version of this Article Fang-Chin Hsu was incorrectly affiliated with ‘Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan’. The correct affiliation is: Division of Colorectal Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

2/21/2025

A Correction to this paper has been published: 10.1038/s41598-025-89294-5

Acknowledgements

We would like to thank the National Defense Medical Center team for support.

Author contributions

Data curation, Tzu-Hsuan Weng; Formal analysis, Ta-Wei Pu; Investigation, Pi-Kai Chang and Tzu-Chiao Lin; Project administration, Shu-Wen Jao; Resources, Chao-Yang Chen; Supervision, Je-Ming Hu; Writing—original draft, Fang-Chin, Hsu; Writing—review & editing, Wu-Chien Chien. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Tri-Service General Hospital Research Foundation (TSGH-B-113025; TSGH-E-113301). The sponsor had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation. We also appreciate the Health and Welfare Data Science Center, Ministry of Health and Welfare (HWDC, MOHW), Taiwan, for providing the National Health Insurance Research Database (NHIRD).

Availability of data and materials

Data are available from the National Health Insurance Research Database (NHIRD) published by the Taiwan NHI Administration. Data cannot be made publicly available due to legal constraints placed by the Taiwanese government in regard to the “Personal Information Protection Act”, but are available from the corresponding author on reasonable request. Data requests can be submitted to the NHIRD as formal proposals.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). The Institutional Review Board of Tri-Service General Hospital approved this study and waived the need for individual written informed consent (TSGHIRB No. E202416008).

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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