Abstract
Background
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a newly defined condition linked to cardiometabolic risk. Its association with psoriasis remains unclear.
Objective
To evaluate the association between MASLD and psoriasis risk in young adults in Korea.
Methods
A retrospective cohort study was conducted using data from 6,400,590 adults aged 20–39 years in the Korean National Health Insurance Service. Participants were classified into seven study-defined, mutually exclusive SLD groups, and incident psoriasis was identified by International Statistical Classification of Diseases and Related Health Problems, 10th Revision codes. Cox proportional hazards models estimated hazard ratios (HRs).
Results
During a median follow-up of 9.1 years, 170,921 individuals developed psoriasis. MASLD was significantly associated with increased psoriasis risk (adjusted HR, 1.13). Risk estimates varied across the study-defined groups.
Conclusion
MASLD and related study-defined groups were associated with psoriasis risk in young adults.
Keywords: Epidemiology, Fatty liver, Non-alcoholic fatty liver disease, Psoriasis, Young adults
INTRODUCTION
Metabolic dysfunction-associated steatotic liver disease (MASLD) has recently emerged as a new diagnostic category for fatty liver disease, reflecting a shift from the previous term, non-alcoholic fatty liver disease (NAFLD). MASLD requires the presence of hepatic steatosis and at least one cardiometabolic risk factor, with alcohol exposure and other liver disease etiologies considered within the broader SLD framework1. This revised framework addresses limitations of NAFLD, which has been criticized for lacking metabolic specificity and carrying stigmatizing terminology2,3,4. Additionally, NAFLD’s strict exclusion criteria limited its applicability to individuals with overlapping metabolic and alcohol-related liver conditions5. Within this more inclusive SLD framework, metabolic criteria inform disease classification1,6, and fibrosis assessment helps characterize liver disease severity in MASLD1,7.
Non-invasive clinical prediction rules and blood-based biomarkers are available for assessing fatty liver disease severity8. NAFLD is also associated with increased cardiovascular risk9. Importantly, the broader SLD framework includes categories such as metabolic-alcohol-associated liver disease (MetALD) and combination etiologies, offering a more comprehensive understanding of steatotic liver disease (SLD)1.
While MASLD’s associations with metabolic and cardiovascular disorders have been well studied, its relationship with dermatologic conditions remains unclear. Psoriasis is a chronic inflammatory skin disease closely tied to systemic inflammation and metabolic dysfunction, including an increased risk of type 2 diabetes mellitus10. Prior literature has described an association between psoriasis and NAFLD11. Given the shared pathogenic mechanisms, it is plausible that MASLD may also confer an elevated risk of psoriasis.
This study investigates the association between MASLD and incident psoriasis in Korean adults aged 20–39 years using a nationwide population-based cohort.
MATERIALS AND METHODS
Data source
We used the Korean National Health Insurance Service (NHIS) database, which provides nationwide health coverage and includes standardized health screening data, such as self-reported lifestyle factors, clinical and laboratory measurements12. The database also contains sociodemographic information, International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10)-coded claims data, and mortality records. Further details on NHIS and screening procedures are available in prior publications13. This study was approved by the Institutional Review Board (IRB) of Yeouido St. Mary’s Hospital, The Catholic University of Korea (IRB No. SC24ZISE0138), and the requirement for informed consent was waived due to the use of anonymized data from a national cohort.
Study population
From 2009 to 2012, 6,891,401 adults aged 20–39 underwent NHIS health screenings, a period consistent with prior nationwide cohort studies that used baseline health-screening data to classify MASLD/SLD14,15. After excluding individuals with missing data, liver cancer (ICD-10: C22 with RID code V193), or liver transplants (Z944), 6,560,445 participants remained for cross-sectional analysis. For longitudinal analysis, individuals with a prior diagnosis of psoriasis (ICD-10: L40.0) were excluded to ensure incident case identification, applying a washout period consistent with a previous nationwide cohort study, along with those with less than one year of follow-up16. This resulted in a final cohort of 6,400,590 participants (Supplementary Fig. 1).
Key variables
Baseline data on lifestyle factors and clinical parameters were obtained through standardized health examinations. Hepatic steatosis was assessed using the fatty liver index (FLI), with a threshold of ≥30 used as a proxy for hepatic steatosis17,18. The FLI is a validated, non-invasive tool endorsed in clinical guidelines, particularly suitable for large-scale studies. Weekly alcohol consumption was estimated from self-reported drinking frequency and quantity, assuming one standard drink contains 8 g of ethanol19.
Participants with FLI <30 were classified as the “No steatosis” group. Those with FLI ≥30 were subdivided into six mutually exclusive, study-defined groups (Table 1). Participants were assigned to the first matching group in the following order: no steatosis, cryptogenic SLD, specific-etiology SLD, MASLD, MASLD with other combined etiologies, MetALD, and ALD with metabolic factor. In these definitions, ALD (+/−) denotes the presence or absence of a claims-defined alcohol-related liver disease diagnosis flag and is distinct from the study-defined “ALD with metabolic factor” group. The groups were defined as follows:
Table 1. Study-defined SLD groups.
| Groups | Definition |
|---|---|
| No steatosis | FLI <30 |
| MASLD | (1) FLI ≥30 and (2) Cardiometabolic (+) and (3) Alcohol <30/20 g/day and (4) CLD (−) and ALD (−) |
| MASLD with other combined etiologies | (1) FLI ≥30 and (2) Cardiometabolic (+) and (3) Alcohol <30/20 g/day and (4) [CLD (+) or ALD (+)] |
| MetALD | (1) FLI ≥30 and (2) Cardiometabolic (+) and (3) Alcohol 30–60/20–50 g/day |
| ALD with metabolic factor | (1) FLI ≥30 and (2) Cardiometabolic (+) and (3) Alcohol ≥60/50 g/day |
| Specific-etiology SLD | (1) FLI ≥30 and (2) Cardiometabolic (−) and [(3) Alcohol ≥30/20 g/day or (4) CLD (+) or ALD (+)] |
| Cryptogenic SLD | (1) FLI ≥30 and (2) Cardiometabolic (−) and (3) Alcohol <30/20 g/day and (4) CLD (−) and ALD (−) |
In Table 1, ALD (+/−) denotes a claims-defined alcohol-related liver disease diagnosis flag and is distinct from the study-defined “ALD with metabolic factor” group. Group assignment followed the first-matching priority specified in the Methods.
SLD: steatotic liver disease, FLI: fatty liver index, MASLD: metabolic dysfunction-associated steatotic liver disease, CLD: chronic liver disease, ALD: alcohol-related liver disease, MetALD: metabolic-alcohol-associated liver disease.
1. MASLD: FLI ≥30, at least one cardiometabolic risk factor, alcohol intake <30 g/day (men) or <20 g/day (women), and no chronic liver disease (CLD) or claims-defined alcohol-related liver disease (ALD) diagnosis flag.
-
Cardiometabolic risk factors included:
• Body mass index (BMI) ≥23 kg/m2 or high waist circumference (≥90 cm men, ≥80 cm women)
• Fasting glucose ≥100 mg/dL, type 2 diabetes, or use of antidiabetic medications
• Blood pressure ≥130/85 mmHg or antihypertensive medication use
• Triglycerides ≥150 mg/dL or lipid-lowering therapy
• Low high-density lipoprotein cholesterol (≤40 mg/dL men, ≤50 mg/dL women) or lipid-lowering therapy
2. MASLD with other combined etiologies: FLI ≥30, at least one cardiometabolic risk factor, alcohol intake <30 g/day in men or <20 g/day in women, and concurrent CLD or a claims-defined ALD diagnosis flag. CLD included drug-induced liver injury, viral hepatitis, autoimmune or cholestatic liver diseases, metabolic liver diseases (e.g., Wilson’s disease, hemochromatosis), and others based on ICD-10 codes (e.g., K71, B15–B19, K75.4, E83.0, etc.).
3. MetALD: FLI ≥30, at least one cardiometabolic risk factor, and alcohol intake of 30–60 g/day in men or 20–50 g/day in women.
4. ALD with metabolic factor: FLI ≥30, at least one cardiometabolic risk factor, and alcohol intake ≥60 g/day in men or ≥50 g/day in women.
5. Specific-etiology SLD: FLI ≥30, no cardiometabolic risk factors, and either alcohol intake ≥30 g/day in men or ≥20 g/day in women, or the presence of CLD or a claims-defined ALD diagnosis flag.
6. Cryptogenic SLD: FLI ≥30, no cardiometabolic risk factors, alcohol intake <30 g/day in men or <20 g/day in women, and no CLD or claims-defined ALD diagnosis flag.
Psoriasis was identified via ICD-10 code L40.0 from inpatient or outpatient claims data. Individuals with at least one claim were classified as having psoriasis. The primary outcome was incident psoriasis, and participants were followed from the date of baseline health screening until the first psoriasis diagnosis or the study end date (December 31, 2021). The definitions of the ICD-10 codes used for the study variables are provided in Supplementary Table 1, which enhances the reproducibility and clarity of the study.
Statistical analysis
Baseline characteristics were summarized as mean ± standard deviation for normally distributed variables and geometric mean (95% confidence interval [CI]) for skewed variables after log transformation. Categorical variables were expressed as percentages. Psoriasis incidence was calculated per 1,000 person-years. Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) and 95% CIs, controlling for age, sex, smoking, exercise, total cholesterol, fasting glucose, systolic blood pressure, and estimated glomerular filtration rate (eGFR). Covariates were selected a priori based on known associations with psoriasis risk.
RESULTS
Baseline characteristics
Table 2 presents the baseline demographic and clinical features of the study population. Of the 6,400,590 participants, 4,607,737 (71.99%) had no steatosis, 1,417,363 (22.14%) had MASLD, 59,054 (0.92%) had MASLD with other combined etiologies, 244,984 (3.83%) had MetALD, 61,044 (0.95%) had ALD with metabolic factor, 3,102 (0.05%) had specific-etiology SLD, and 7,306 (0.11%) had cryptogenic SLD. Age distributions differed across the groups. In contrast, the no steatosis group exhibited a lower proportion of older adults. The male percentage was consistently above 90% in all steatotic groups, whereas it was lower in those without steatosis. BMI distributions also differed across the groups.
Table 2. Baseline characteristics.
| Characteristics | Group | p-value | |||||||
|---|---|---|---|---|---|---|---|---|---|
| No steatosis | MASLD | MASLD with other combined etiologies | MetALD | ALD with metabolic factor | Specific-etiology SLD | Cryptogenic SLD | |||
| No. of patients | 4,607,737 | 1,417,363 | 59,054 | 244,984 | 61,044 | 3,102 | 7,306 | ||
| Age (yr) | <0.01 | ||||||||
| <30 | 2,226,610 (48.32) | 366,890 (25.89) | 12,411 (21.02) | 69,175 (28.24) | 19,707 (32.28) | 896 (28.88) | 1,729 (23.67) | ||
| ≥30 | 2,381,127 (51.68) | 1,050,473 (74.11) | 46,643 (78.98) | 175,809 (71.76) | 41,337 (67.72) | 2,206 (71.12) | 5,577 (76.33) | ||
| Sex | <0.01 | ||||||||
| Male | 2,174,945 (47.2) | 1,282,693 (90.5) | 54,351 (92.04) | 233,740 (95.41) | 58,933 (96.54) | 2,986 (96.26) | 7,061 (96.65) | ||
| Female | 2,432,792 (52.8) | 134,670 (9.5) | 4,703 (7.96) | 11,244 (4.59) | 2,111 (3.46) | 116 (3.74) | 245 (3.35) | ||
| Income, lowest* | 1,078,098 (23.4) | 228,453 (16.12) | 8,384 (14.2) | 35,709 (14.58) | 10,538 (17.26) | 479 (15.44) | 1,096 (15) | <0.01 | |
| BMI level (kg/m2) | <0.01 | ||||||||
| <18.5 | 483,847 (10.5) | 421 (0.03) | 53 (0.09) | 218 (0.09) | 67 (0.11) | 17 (0.55) | 22 (0.3) | ||
| <23 | 2,864,440 (62.17) | 84,996 (6) | 3,602 (6.1) | 20,917 (8.54) | 5,464 (8.95) | 3,085 (99.45) | 7,284 (99.7) | ||
| <25 | 859,193 (18.65) | 291,941 (20.6) | 11,408 (19.32) | 55,697 (22.73) | 13,009 (21.31) | N/A | N/A | ||
| <30 | 394,285 (8.56) | 824,569 (58.18) | 34,256 (58.01) | 136,818 (55.85) | 33,319 (54.58) | N/A | N/A | ||
| ≥30 | 5,972 (0.13) | 215,436 (15.2) | 9,735 (16.48) | 31,334 (12.79) | 9,185 (15.05) | N/A | N/A | ||
| Smoking | <0.01 | ||||||||
| Non-smoker | 2,973,701 (64.54) | 472,130 (33.31) | 19,030 (32.22) | 32,391 (13.22) | 6,327 (10.36) | 340 (10.96) | 1,937 (26.51) | ||
| Ex-smoker | 396,157 (8.6) | 205,451 (14.5) | 10,662 (18.05) | 39,873 (16.28) | 9,303 (15.24) | 409 (13.19) | 953 (13.04) | ||
| Current smoker | 1,237,879 (26.87) | 739,782 (52.19) | 29,362 (49.72) | 172,720 (70.5) | 45,414 (74.4) | 2,353 (75.85) | 4,416 (60.44) | ||
| Drinking | <0.01 | ||||||||
| Non | 1,972,043 (42.8) | 420,214 (29.65) | 19,280 (32.65) | N/A | N/A | 125 (4.03) | 1,377 (18.85) | ||
| Mild | 2,312,864 (50.2) | 997,149 (70.35) | 39,774 (67.35) | N/A | N/A | 310 (9.99) | 5,929 (81.15) | ||
| Heavy | 274,908 (5.97) | N/A | N/A | 244,984 (100) | N/A | 2,121 (68.38) | N/A | ||
| Alcoholic | 47,922 (1.04) | N/A | N/A | N/A | 61,044 (100.00) | 546 (17.6) | N/A | ||
| Regular exercise | 574,123 (12.46) | 191,867 (13.54) | 8,774 (14.86) | 35,939 (14.67) | 9,992 (16.37) | 336 (10.83) | 747 (10.22) | <0.01 | |
| DM | 41,414 (0.9) | 63,067 (4.45) | 4,587 (7.77) | 11,642 (4.75) | 3,309 (5.42) | N/A | N/A | <0.01 | |
| Hypertension | 158,197 (3.43) | 234,427 (16.54) | 12,552 (21.26) | 51,797 (21.14) | 14,218 (23.29) | N/A | N/A | <0.01 | |
| Dyslipidemia | 146,217 (3.17) | 226,875 (16.01) | 13,692 (23.19) | 38,916 (15.89) | 9,762 (15.99) | 218 (7.03) | 635 (8.69) | <0.01 | |
| CKD | 126,914 (2.75) | 37,713 (2.66) | 1,743 (2.95) | 5,939 (2.42) | 1,297 (2.12) | 58 (1.87) | 169 (2.31) | <0.01 | |
| WC (cm) | 73.27±7.32 | 88.54±7.28 | 89.11±7.58 | 88.09±7.35 | 88.62±7.86 | 80.49±4.07 | 81.06±4.08 | <0.01 | |
| SBP (mmHg) | 114.71±12 | 125.18±12.8 | 125.14±12.76 | 127.35±13.13 | 128.26±13.28 | 115.93±7.39 | 115.36±7.54 | <0.01 | |
| DBP (mmHg) | 71.76±8.62 | 78.72±9.42 | 78.78±9.46 | 80.38±9.73 | 80.92±9.84 | 73.29±6.34 | 72.84±6.47 | <0.01 | |
| Fasting glucose (mg/dL) | 88.79±12.82 | 96.03±22.76 | 97.95±25.96 | 97.32±22.97 | 98.21±25.33 | 87.46±7.64 | 87.47±7.76 | <0.01 | |
| TC (mg/dL) | 177.28±30.08 | 203.52±35.58 | 202.46±36.82 | 202.92±35.79 | 202.39±36.46 | 190.57±31.51 | 195.83±31.71 | <0.01 | |
| HDL (mg/dL) | 59.97±20.69 | 49.75±24.05 | 49.48±22.84 | 53.11±20.56 | 54.21±21.78 | 62.62±18.71 | 58.6±15.08 | <0.01 | |
| LDL (mg/dL) | 100.86±31.27 | 116.01±39.95 | 115.41±41.02 | 108.62±39.52 | 105.42±40.66 | 104.38±34.76 | 113.07±32.14 | <0.01 | |
| eGFR (mL/min/1.73 m2) | 96.89±47.9 | 93.75±53.43 | 94.16±53.97 | 94.57±51.04 | 95.15±43.84 | 98.05±54.29 | 97.4±69.66 | <0.01 | |
| Triglyceride (mg/dL) | 76.66 (76.63–76.69) | 174.96 (174.82–175.1) | 172.35 (171.65–173.06) | 185.73 (185.35–186.11) | 191.34 (190.52–192.17) | 117.57 (116.75–118.39) | 119.08 (118.55–119.61) | <0.01 | |
| AST (IU/L) | 19.64 (19.64–19.65) | 26.72 (26.7–26.74) | 30.48 (30.37–30.6) | 28.75 (28.71–28.8) | 30.12 (30.02–30.22) | 32.78 (32.19–33.37) | 30.45 (30.12–30.79) | <0.01 | |
| ALT (IU/L) | 15.69 (15.68–15.7) | 34.18 (34.14–34.21) | 40.41 (40.2–40.62) | 34.42 (34.34–34.49) | 35.43 (35.28–35.59) | 38.42 (37.57–39.29) | 38.43 (37.9–38.98) | <0.01 | |
| γ-GTP (IU/L) | 17.62 (17.61–17.63) | 44.84 (44.79–44.89) | 52.69 (52.4–52.99) | 65.1 (64.93–65.27) | 72.64 (72.25–73.03) | 107.12 (104.95–109.33) | 93.94 (92.71–95.19) | <0.01 | |
Continuous variables are presented as mean ± standard deviation or geometric mean (95% confidence interval) for triglycerides and liver enzymes.
MASLD: metabolic dysfunction-associated steatotic liver disease, MetALD: metabolic-alcohol-associated liver disease, ALD: alcohol-related liver disease, SLD: steatotic liver disease, BMI: body mass index, DM: diabetes mellitus, CKD: chronic kidney disease, WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, TC: total cholesterol, HDL: high-density lipoprotein, LDL: low-density lipoprotein, eGFR: estimated glomerular filtration rate, AST: aspartate aminotransferase, ALT: alanine aminotransferase, γ-GTP: gamma-glutamyl transferase.
*Lowest income: lowest quartile (25%) of household income.
Marked differences were also observed in smoking status: among the no steatosis group, 64.54% were nonsmokers, whereas the corresponding proportions in MASLD, MASLD with other combined etiologies, MetALD, ALD with metabolic factor, specific-etiology SLD, and cryptogenic SLD groups were 33.31%, 32.22%, 13.22%, 10.36%, 10.96%, and 26.51%, respectively (p<0.01). Additionally, the proportion of individuals engaging in regular exercise differed among groups, with 12.46% in the no steatosis, 13.54% in the MASLD, 14.86% in the MASLD with other combined etiologies, 14.67% in the MetALD, 16.37% in the ALD with metabolic factor group, 10.83% in the specific-etiology SLD, and 10.22% in the cryptogenic SLD (p<0.01). The prevalence of cardiometabolic comorbidities differed across groups, partly reflecting the group definitions. Laboratory-based measurements, including total cholesterol, fasting glucose, systolic blood pressure, and eGFR, also differed significantly across groups (all p<0.01).
Risk of psoriasis
During the follow-up period, a total of 170,921 individuals (2.67% of the entire cohort) developed new-onset psoriasis. As shown in Table 3, the incidence rate (IR) per 1,000 person-years varied considerably among the 7 groups, ranging from 2.53 in the cryptogenic SLD group to 3.52 in the specific-etiology SLD group. Specifically, the IRs increased in the following order: cryptogenic SLD (2.53), no steatosis (2.54), MASLD (2.76), MetALD (2.94), ALD with metabolic factor (2.96), MASLD with other combined etiologies (3.33), and specific-etiology SLD (3.52).
Table 3. Incidence and risk of psoriasis.
| Variables | Total number | Psoriasis | Duration (PY) | Incidence rate* (1,000 PY) | Hazard ratio (95% confidence intervals) | ||
|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | |||||
| No steatosis | 4,607,737 | 119,220 | 46,910,301.8 | 2.54 | 1 (Ref.) | 1 (Ref.) | 1 (Ref.) |
| MASLD | 1,417,363 | 40,178 | 14,532,310.6 | 2.76 | 1.09 (1.08, 1.10) | 1.13 (1.12, 1.14) | 1.13 (1.12, 1.15) |
| MASLD with other combined etiologies | 59,054 | 2,014 | 605,441.3 | 3.33 | 1.31 (1.26, 1.37) | 1.36 (1.31, 1.43) | 1.37 (1.31, 1.43) |
| MetALD | 244,984 | 7,370 | 2,510,191.5 | 2.94 | 1.16 (1.13, 1.18) | 1.20 (1.18, 1.23) | 1.18 (1.15, 1.21) |
| ALD with metabolic factor | 61,044 | 1,838 | 621,139.5 | 2.96 | 1.17 (1.11, 1.22) | 1.21 (1.16, 1.27) | 1.18 (1.13, 1.24) |
| Specific-etiology SLD | 3,102 | 111 | 31,562.6 | 3.52 | 1.39 (1.15, 1.67) | 1.44 (1.20, 1.74) | 1.38 (1.15, 1.67) |
| Cryptogenic SLD | 7,306 | 190 | 75,134.4 | 2.53 | 1.00 (0.86, 1.15) | 1.04 (0.90, 1.20) | 1.02 (0.89, 1.18) |
Hazard ratio of Model 1 was non adjusted; hazard ratio of Model 2 was adjusted for age and sex; hazard ratio of Model 3 was adjusted for age, sex, smoking, regular exercise, total cholesterol, fasting glucose, systolic blood pressure, estimated glomerular filtration rate.
PY: person-years, MASLD: metabolic dysfunction-associated steatotic liver disease, MetALD: metabolic-alcohol-associated liver disease, ALD: alcohol-related liver disease, SLD: steatotic liver disease.
*The incidence rate is per 1,000 person-years of follow-up.
In the multivariable Cox proportional hazards model, model 2, which was adjusted for age and sex only, the HRs (95% CI) in ascending order were: cryptogenic SLD at 1.04 (0.90–1.20), MASLD at 1.13 (1.12–1.14), MetALD at 1.20 (1.18–1.23), ALD with metabolic factor at 1.21 (1.16–1.27), MASLD with other combined etiologies at 1.36 (1.31–1.43), and specific-etiology SLD at 1.44 (1.20–1.74). In model 3, which was further adjusted for additional covariates (smoking, regular exercise, total cholesterol, fasting glucose, systolic blood pressure, and eGFR), the HR estimates remained nearly unchanged, with cryptogenic SLD at 1.02 (0.89–1.18), MASLD at 1.13 (1.12–1.15), MetALD at 1.18 (1.15–1.21), ALD with metabolic factor at 1.18 (1.13–1.24), MASLD with other combined etiologies at 1.37 (1.31–1.43), and specific-etiology SLD at 1.38 (1.15–1.67).
Joint associations of FLI, cardiometabolic risk, and alcohol consumption with psoriasis incidence
The forest plot (Fig. 1) reflects the relative hazard for psoriasis incidence within each subgroup compared with the reference group. The reference group (HR, 1.00) comprised participants with FLI <30, no cardiometabolic risk factors, and no alcohol intake. Within the same FLI <30 and no-cardiometabolic risk-factor, mild drinking corresponded to an HR of 1.02 (95% CI, 1.00–1.04), heavy drinking to 1.05 (95% CI, 1.01–1.09), and alcoholic to 1.10 (95% CI, 1.01–1.20). For participants with FLI <30 and cardiometabolic risk factors, non-drinkers showed an HR of 1.04 (95% CI, 1.03–1.06), while mild, heavy, and alcoholic drinking were 1.06 (95% CI, 1.04–1.08), 1.10 (95% CI, 1.07–1.14), and 1.13 (95% CI, 1.05–1.21), respectively. Among those with FLI ≥30 and no cardiometabolic risk factors, non-drinkers had an HR of 1.14 (95% CI, 0.84–1.55), mild drinkers 1.10 (95% CI, 0.94–1.27), heavy drinkers 1.39 (95% CI, 1.10–1.75), and alcoholic consumers 1.38 (95% CI, 0.88–2.17). Finally, for FLI ≥30 combined with cardiometabolic risk factors, non-drinkers showed an HR of 1.22 (95% CI, 1.19–1.25), whereas mild, heavy, and alcoholic categories corresponded to HRs of 1.19 (95% CI, 1.16–1.21), 1.23 (95% CI, 1.20–1.27), and 1.24 (95% CI, 1.18–1.30), respectively.
Fig. 1. Forest plot of associations of FLI, cardiometabolic risk, and alcohol consumption with psoriasis incidence. HRs and 95% CIs are from Model 3, with covariate adjustment as specified in Table 3.
FLI: fatty liver index, HR: hazard ratio, CI: confidence interval.
DISCUSSION
In this study, FLI-defined steatosis in young adults (20–39 years) was associated with a higher risk of psoriasis, particularly when cardiometabolic risk factors were present. Risk estimates also varied across alcohol-intake categories. These results show joint variation across FLI, cardiometabolic risk, and alcohol-intake strata; formal interaction was not evaluated. With the recent shift to the MASLD framework, our findings reaffirm the relevance of hepatic metabolic dysfunction in psoriasis pathogenesis. Even under this updated classification, the link between metabolic liver disease and psoriasis remains strong, supporting further investigation of their shared determinants.
In this study, we found a higher incidence of psoriasis among individuals with steatosis compared to those without. Adjusted HRs for psoriasis, in ascending order, were: cryptogenic SLD (HR, 1.02; 95% CI, 0.89–1.18), MASLD (HR, 1.13; 95% CI, 1.12–1.15), MetALD (HR, 1.18; 95% CI, 1.15–1.21), ALD with metabolic factor (HR, 1.18; 95% CI, 1.13–1.24), MASLD with other combined etiologies (HR, 1.37; 95% CI, 1.31–1.43), and specific-etiology SLD (HR, 1.38; 95% CI, 1.15–1.67). These findings are consistent with previous research on NAFLD and psoriasis. A U.S. cross-sectional study reported that psoriasis was associated with higher odds of NAFLD (odds ratio [OR], 1.70; 95% CI, 1.06–2.72), especially among those aged 20–39 years (OR, 2.48; 95% CI, 1.09–5.67)20. Similarly, a Taiwanese cohort study found an increased HR for incident psoriasis in patients with NAFLD (HR, 1.07; 95% CI, 1.01–1.14 for overall; HR, 1.30; 95% CI, 1.14–1.48 for younger adults)21. Our findings support and extend this evidence by using study-defined groups adapted from the SLD framework, showing that hepatic steatosis—particularly when accompanied by metabolic dysfunction or other liver disease—remains significantly associated with psoriasis. By offering detailed stratification across the study-defined groups, our study provides a more nuanced understanding of psoriasis risk under this operational framework.
Accumulating evidence suggests a strong link between psoriasis and MASLD, primarily through shared inflammatory and metabolic pathways contributing to systemic and hepatic inflammation. In our study, psoriasis incidence was higher among individuals with MASLD than those without steatosis, and this association remained after multivariable adjustment. Both diseases involve chronic systemic inflammation, immune dysregulation, and metabolic dysfunction, collectively described as the “hepato-dermal axis,” where hepatic cytokines aggravate systemic inflammation and psoriasis severity22. A central mediator is the interleukin (IL)-17/IL-23 axis, which drives abnormal keratinocyte activity in psoriasis and promotes hepatic steatosis, insulin resistance, and fibrosis in MASLD. IL-17 stimulates macrophages, endothelial cells, and Kupffer cells, increasing tumor necrosis factor (TNF)-α, IL-6, and monocyte chemoattractant protein-1, thereby enhancing systemic inflammation23. It may also affect hepatic lipid metabolism23. Moreover, IL-17 may contribute to hepatic inflammation and progression from simple steatosis to steatohepatitis24. These findings highlight IL-17 as a shared inflammatory link between hepatic and cutaneous pathology in MASLD and psoriasis.
Given the shared involvement of the IL-17/IL-23 axis in psoriasis and MASLD, pathway-targeted therapies raise the possibility of dual cutaneous and hepatic benefits23,24,25. The hepatic effects of systemic psoriasis therapies have been reviewed,25 and associations between psoriasis and liver diseases beyond NAFLD have also been reported26. However, current evidence does not establish that biologic treatment prevents or improves MASLD. Whether these therapies can modify hepatic inflammation or fibrosis, or influence the broader cardiovascular risk associated with MASLD, remains an important question for future longitudinal and interventional studies.
This study has several limitations. First, MASLD was defined using the FLI rather than imaging or histology, which may have caused some misclassification; however, FLI is a validated tool for large-scale studies. In addition, MASLD status was assessed only at baseline (2009–2012), despite its dynamic and potentially reversible nature, which may have led to misclassification over time. Future studies incorporating time-varying analyses are warranted to better capture longitudinal changes in metabolic liver status. Second, psoriasis was identified using ICD-10 codes from claims data, which may miss mild or undiagnosed cases. Moreover, although a 1-year washout period was applied to define incident psoriasis, this duration may be insufficient given the chronic relapsing–remitting course of the disease, potentially leading to misclassification of prevalent cases as incident cases. Sensitivity analyses with longer washout periods would strengthen the robustness of the findings. Additionally, we lacked detailed clinical information on psoriasis severity and liver fibrosis stage, which limits our ability to assess disease burden and potential dose-response relationships between SLD and psoriasis risk. This limitation may affect the interpretation of clinical applicability, as differences in disease severity could influence both detection and prognosis. These associations should be interpreted in light of the above limitations. Finally, Groups 4 and 5 were study-defined, mutually exclusive operational categories rather than direct implementations of consensus clinical SLD categories; Group 4 included only participants with cardiometabolic risk factors and high alcohol intake, whereas participants without cardiometabolic risk factors who had increased alcohol intake were assigned to Group 5. Nonetheless, the study’s strengths include its large, nationally representative cohort and the use of study-defined groups adapted from the SLD framework to evaluate the association between metabolic liver disease and psoriasis risk.
These findings have potential clinical and research implications. Although this observational study does not establish a clinical screening or intervention strategy, the association observed in young adults provides a population-level rationale for prospective evaluation of multidisciplinary approaches integrating dermatologic, metabolic, and hepatic assessment. Such studies may identify clinically relevant subgroups in whom coordinated care is useful and determine whether earlier recognition of metabolic liver disease or psoriasis improves outcomes.
From a research perspective, further studies using clinically validated liver and psoriasis phenotypes are needed to clarify the shared inflammatory mechanisms underlying both conditions and to identify potentially modifiable pathways. By advancing this evidence base, future research may support a more comprehensive, patient-centered approach that addresses dermatologic, metabolic, and hepatic health.
Footnotes
FUNDING SOURCE: This research was supported by a grant of the Institute of Clinical Medicine Research in the Yeouido St. Mary’s Hospital, Catholic University of Korea (YSI24H007), and by the Catholic Medical Center Research Foundation made in the program year of 2026.
CONFLICTS OF INTEREST: The authors have nothing to disclose.
DATA SHARING STATEMENT: The data used in this study are based on data from the Korean National Health Insurance Service. According to Korean laws and regulations, all data in the NHIS claims database are confidential. The NHIS grants permission to use the registers and documents for scientific research. Data access is subject to approval by the Korean National Health Insurance Service.
SUPPLEMENTARY MATERIALS
ICD-10 codes for alcohol-related disorders, liver diseases and psoriasis
Flowchart showing the selection of the final study cohort and classification according to the presence or absence of SLD.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
ICD-10 codes for alcohol-related disorders, liver diseases and psoriasis
Flowchart showing the selection of the final study cohort and classification according to the presence or absence of SLD.