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MASLD and type 2 diabetes

Scope. Glycaemic management belongs to type 2 diabetes. This page covers the bidirectional relationship, the case-finding problem in diabetes clinics, and the outcomes that follow from the combination.

TL;DR — Roughly two in three people with type 2 diabetes have MASLD: pooled prevalence 65.33% (95% CI 62.35–68.18) across 123 studies and 2,224,144 patients, and 65.04% (61.79–68.15) across 156 studies and 1,832,125 patients (Younossi 2024, PMID 38521116; Cho 2023, PMID 37491159). Among those biopsied, 66.44% (56.61–75.02) have steatohepatitis, 40.78% (24.24–59.70) significant fibrosis and 15.49% (6.99–30.99) advanced fibrosis (PMID 38521116). Prospective systematic assessment in 501 adults aged ≥50 with T2D found advanced fibrosis in 14% and cirrhosis in 6% (Ajmera 2023, PMID 36410554). The relationship runs both ways: type 2 diabetes prevalence rises stepwise with fibrosis stage from 28% at F0 to 70% at F4 (Younossi 2026, PMID 41231627), while 28.3% (25.2–31.6) of people with NAFLD have T2D and incidence is 24.6 per 1,000 person-years (Cao 2024, PMID 38448943). The combination is worse than either alone: in 7,796,763 Koreans, five-year absolute risk of cardiovascular disease or death rose stepwise across NAFLD grade, and people with T2D and no NAFLD had higher risk than people with grade 2 NAFLD and no T2D (Kim 2024, PMID 38350680). The American Diabetes Association issued a 2025 consensus report calling for fibrosis screening as a new standard of care in prediabetes and type 2 diabetes (Cusi 2025, PMID 40434108).

Prevalence in each direction

Direction Estimate Source
MASLD in T2D 65.33% (62.35–68.18), 123 studies, N=2,224,144 Younossi 2024, PMID 38521116
MASLD in T2D 65.04% (61.79–68.15), 156 studies, N=1,832,125 Cho 2023, PMID 37491159
MASLD in T2D (narrative) ~60–70% Tilg 2026, PMID 41212550
MASH in T2D (biopsy subset) 66.44% (56.61–75.02), 12 studies, N=2,733 PMID 38521116
MASH in T2D (all methods) 31.55% (17.12–50.70) PMID 37491159
Significant fibrosis (F2–4) in T2D with MASLD 40.78% (24.24–59.70) / 35.54% (19.56–55.56) PMID 38521116 / PMID 37491159
Advanced fibrosis (F3–4) in T2D with MASLD 15.49% (6.99–30.99) / 14.95% (11.03–19.95) PMID 38521116 / PMID 37491159
T2D in NAFLD 28.3% (25.2–31.6), 395 studies, N=6,878,568 Cao 2024, PMID 38448943
T2D in MAFLD 26.2% (23.9–28.6), N=1,172,637 PMID 38448943
Incident T2D in NAFLD 24.6 per 1,000 person-years (20.7–29.2) PMID 38448943
Incident T2D in NAFLD (pooled cohort incidence) 19.0 per 1,000 person-years Le 2024, PMID 38281814

MASLD prevalence in T2D is rising: 55.86% (42.38–68.53) in 1990–2004 to 68.81% (63.41–73.74) in 2016–2021 (p=0.073), with the highest regional figure in Eastern Europe (80.62%, 75.72–84.73), then the Middle East (71.24%, 62.22–78.84), and the lowest in Africa (53.10%, 26.05–78.44) — the African estimate resting on few studies with a very wide interval (PMID 38521116).

Type 2 diabetes also tracks fibrosis stage within MASLD: 28% at F0 rising monotonically to 70% at F4 (trend p<0.0001) in 17,792 biopsy-confirmed patients, where T2D was an independent predictor of advanced fibrosis, of mortality and of clinical events (Younossi 2026, PMID 41231627).

The metabolic gradient of risk

NHANES III with mortality follow-up to 2019 (median 26.7 years, 11,231 adults, 3,982 deaths) stratified people by metabolic state rather than by liver disease alone (Golabi 2023, PMID 37380016):

Group Odds of having NAFLD vs metabolically healthy Age-standardised cumulative mortality among those with NAFLD
Type 2 diabetes OR 10.88 (7.33–16.16) 41.3%
Prediabetes OR 4.19 (3.02–5.81) 35.1%
Metabolically unhealthy, no dysglycaemia OR 3.36 (2.39–4.71) 30.0%
Metabolically healthy reference 21.9%

Versus metabolically healthy NAFLD, NAFLD with T2D carried all-cause mortality HR 4.71 (2.23–9.96) and cardiac-specific mortality HR 20.01 (3.00–133.61); NAFLD with prediabetes 2.91 (1.41–6.02) and 10.35 (1.57–68.08). The cardiac hazard ratios have enormous intervals — few cardiac deaths in the metabolically healthy reference — but the ordering is unambiguous. Independent predictors of mortality in NAFLD with T2D were older age, high CRP, CVD, CKD, high FIB-4 and active smoking; in metabolically healthy NAFLD, active smoking was the only predictor.

The Korean national cohort quantifies the interaction directly. Among 7,796,763 participants (6.49% with T2D), five-year absolute risk of cardiovascular disease and of all-cause death rose stepwise from no NAFLD through grade 1 to grade 2 (by fatty liver index) in both diabetic and non-diabetic strata, and the risk differences between NAFLD grades were larger in people with T2D. The finding that people with T2D and no NAFLD had higher five-year risk than people with grade 2 NAFLD and no T2D (3.34 and 3.68 versus 1.42 and 2.09 per 100) establishes the ordering of the two exposures: diabetes dominates, and NAFLD adds on top of it (Kim 2024, PMID 38350680).

Mortality rates in T2D with MASLD

Pooled rates per 1,000 person-years in T2D with NAFLD/MASLD (Younossi 2024, PMID 38521116):

Cause Rate (95% CI)
All-cause 16.79 (10.64–26.40)
Extrahepatic cancer 6.10 (0.78–4.88)*
Cardiac 4.19 (1.34–7.05)
Liver-specific 2.15 (0.00–2.21)*

*The published confidence intervals for extrahepatic-cancer and liver-specific mortality do not contain their point estimates as reported in the source abstract; the point estimates are quoted as published and the intervals should be treated with caution. Compared with unselected NAFLD (epidemiology and burden), all-cause mortality is roughly a third higher and liver-specific mortality more than double.

Does controlling the diabetes slow the liver disease?

The bidirectional epidemiology invites the assumption that glycaemic control is hepatoprotective. The largest test of it separates the two halves of that claim. In 7,543 MASLD patients from the VCTE-Prognosis cohort with serial elastography and HbA1c, classified by time-weighted average HbA1c (which captures both magnitude and duration of hyperglycaemia) over a median 4.1 years (Zhou 2026, PMID 41076043):

Comparison Liver stiffness progression Liver stiffness regression Liver-related events
T2D (n=4,090) vs no T2D (n=3,453) HR 1.501 (1.148–1.962), p=0.003 no difference HR 2.030 (1.241–3.320), p=0.005
Poorly controlled (TWA HbA1c ≥7%, n=2,045) vs well controlled (<7%, n=2,045) HR 1.524 (1.182–1.965), p=0.001 no difference (p=0.957) no difference (p=0.625)

Diabetes was associated with roughly twice the liver-event hazard; within diabetes, good glycaemic control was associated with slower stiffness progression but did not associate with fewer liver events or more regression. The asymmetry is the important part. It is compatible with two readings — that 4.1 years is too short for a progression difference to become an event difference, or that HbA1c indexes something other than the hepatic driver — and the observational study cannot establish that glycaemic control caused the difference.

Mechanistically, the two are separable in the other direction too. In a single-centre phase 2 study, 38 patients with T2D and MASLD were randomised 1:1 to the pan-PPAR agonist lanifibranor 800 mg or placebo for 24 weeks with gold-standard euglycaemic hyperinsulinaemic clamps (Barb 2025, PMID 39824443, NCT03459079): intrahepatic triglyceride fell −44% vs −12% (LS mean difference −31%, 95% CI −51 to −12; completers −50% vs −16%, both p<0.01), ≥30% IHTG reduction in 65% vs 22% and steatosis resolution in 25% vs 0% (p<0.05), with simultaneous improvement in hepatic, muscle and adipose insulin sensitivity, a 2.4-fold rise in adiponectin, and improvements in fasting glucose, insulin, HOMA-IR, HbA1c and HDL-C (all p<0.001). Weight rose 2.7%. This is the clearest demonstration that a drug can improve hepatic steatosis and multi-tissue insulin resistance together — and that weight gain does not preclude hepatic benefit, which cuts against the weight-loss-centric model of this disease (lifestyle and weight loss).

MASLD is not confined to type 2 diabetes

Steatotic liver disease in type 1 diabetes is a smaller, badly-measured literature, and the measurement is the finding. Pooling 20 studies (2009–2019, n=3,901), NAFLD prevalence in type 1 diabetes was 19.3% (12.3–27.5) overall and 22.0% (13.9–31.2) in adults — but the estimate varied by an order of magnitude with the diagnostic method (de Vries 2020, PMID 32827432):

Modality Pooled prevalence
Ultrasound 27.1% (18.7–36.3)
Liver biopsy 19.3% (10.0–30.7)
MRI 8.6% (2.1–18.6)
Transient elastography 2.3% (0.6–4.8)

A twelve-fold spread between ultrasound and elastography in the same disease is not a subtle heterogeneity problem; it means the type 1 diabetes literature has not yet established whether this is a common or a rare comorbidity. Note the direction of the measurement problem relative to type 2 diabetes, where the pooled prevalence of 65.33% (PMID 38521116) rests on a much larger and more consistently imaged evidence base.

Case-finding in the diabetes clinic

This is the highest-yield screening population in the condition, and it is systematically under-served.

Study Method Yield
Ajmera 2023, PMID 36410554 Prospective, 501 adults aged ≥50 with T2D from primary care and endocrinology, MRI-PDFF + MRE + VCTE + CAP NAFLD 65%, advanced fibrosis 14%, cirrhosis 6%; among 29 with cirrhosis, 2 had HCC and 1 gallbladder adenocarcinoma. Obesity OR 2.50 (1.38–4.54, p=0.003) and insulin use OR 2.71 (1.33–5.50, p=0.006) predicted advanced fibrosis
Caussy 2025, PMID 39887699 Prospective multicentre, 654 with T2D and/or obesity plus MASLD; blood NITs, VCTE, 2D-SWE 17.6% intermediate/high risk of advanced fibrosis, 9.3% high risk. AUROCs for high risk: FIB-4 0.78 (0.72–0.84), ELF 0.82 (0.76–0.87), SWE 0.84 (0.78–0.89). FIB-4→VCTE algorithm "excellent"; FIB-4→ELF at threshold 9.8 gave NPV 88–89% and PPV 39–46%; FIB-4→2D-SWE NPV 91%, PPV 58–62%
Vilar-Gomez 2023, PMID 34958922 NHANES 2017–2018, FAST score High-risk NASH prevalence 8.7%–22.5% in T2D depending on cut-off, versus 5.8% and 1.2% in the general population

The ADA consensus report is the strongest institutional statement: liver health "has not been at the forefront of complications tracked for disease prevention, as traditionally done for diabetic retinopathy, nephropathy, or neuropathy", yet steatosis affects about two of three people with T2D and places them at increased risk of MASH, cirrhosis, HCC and liver-related mortality, as well as extrahepatic cancer, atherosclerotic cardiovascular disease and progression from prediabetes to T2D. It calls for screening for liver fibrosis and risk stratification in prediabetes and T2D, particularly with obesity, and frames broad adoption of fibrosis screening as a new standard of care (Cusi 2025, PMID 40434108). A hepatology-side review sets out matching co-management strategies, including glucose monitoring considerations in the MASLD population (Qi 2026, PMID 38722246). See guidelines.

Cost-effectiveness analysis of MASH diagnosis and management approaches specifically in people with type 2 diabetes has been published (Lazarus 2025, PMID 41196592).

Treatment implications

Agent class Evidence in this overlap
Pioglitazone The trial with the largest histological effect was conducted in prediabetes/T2D: 58% met the primary endpoint (difference 41 points, 95% CI 23–59), 51% NASH resolution, fibrosis score −0.5 (p=0.039), sustained over 36 months (Cusi 2016, PMID 27322798)
SGLT2 inhibitors Lower HCC (HR 0.76, 0.62–0.93), cirrhosis (0.80, 0.76–0.84), CVD (0.82, 0.79–0.85), CKD (0.66, 0.62–0.70) versus other glucose-lowering drugs in diabetic MASLD; risk lower still with metformin co-use (Mao 2024, PMID 39122360). Best NAFLD-regression class versus sulfonylureas and the only class lowering adverse liver outcomes (Jang 2024, PMID 38345802)
GLP-1 receptor agonists In MASLD with diabetes, lower risk of progression to cirrhosis (HR 0.86, 0.75–0.98) and mortality (0.89, 0.81–0.98) versus DPP-4 inhibitors — but no association once cirrhosis was established (Kanwal 2024, PMID 39283612). Semaglutide is now approved for MASH F2–F3
Resmetirom Efficacy unaffected by background SGLT2-inhibitor or GLP-1 therapy in a MAESTRO-NASH secondary analysis (Noureddin 2025, PMID 41127972)

The convenient feature of this overlap is that several drugs act on both diseases. The inconvenient feature is that no trial has randomised a glucose-lowering strategy on hepatic endpoints in T2D with MASLD; every comparison above except the pioglitazone and resmetirom trials is observational.

Open questions

  • Does glycaemic control protect the liver, or just track it? Poor long-term control raises liver-stiffness progression by 52% but leaves liver-related events and stiffness regression unchanged in 4,090 patients with T2D and MASLD (PMID 41076043). Whether that is insufficient follow-up or a genuine dissociation determines whether HbA1c is a hepatic treatment target at all.
  • How common is steatotic liver disease in type 1 diabetes? Pooled prevalence ranges from 2.3% by elastography to 27.1% by ultrasound in the same meta-analysis (PMID 32827432). No study has applied a single modern reference standard (MRI-PDFF plus elastography) to an adequately sized type 1 cohort, and every downstream claim about screening or outcomes in type 1 diabetes inherits that uncertainty.
  • Can hepatic benefit be obtained alongside weight gain? Lanifibranor halved intrahepatic triglyceride and improved clamp-measured insulin sensitivity in liver, muscle and adipose tissue while participants gained 2.7% of body weight (PMID 39824443). If replicated at histological endpoints, this separates hepatic improvement from weight loss more cleanly than any incretin trial can.
  • Does fibrosis screening in diabetes clinics improve outcomes? The ADA calls for it as a standard of care (PMID 40434108) on the basis of prevalence and risk, not on a trial of screening. Query run 2026-09-02: (NASH OR MASH OR NAFLD OR MASLD) AND ("type 2 diabetes") AND (bidirectional OR incident OR screening OR prevalence OR risk) — 4,936 records; no randomised trial of a fibrosis screening programme with clinical endpoints retrieved.
  • Which glucose-lowering drug should be preferred for the liver? Two large observational datasets favour SGLT2 inhibitors (PMIDs: 38345802, 39122360), but observational comparisons do not establish superiority. A 60-person open-label randomised trial added luseogliflozin to semaglutide: MASH resolution was 34.9% versus 19.4%, NAS improvement 75.5% versus 55.6%, and fibrosis improvement 26.9% versus 13.9%, but none of the full-analysis comparisons was statistically significant (Miyake 2026, PMID 42605535). No adequately powered blinded head-to-head trial with hepatic clinical outcomes was identified.
  • Why is prevalence highest in Eastern Europe and lowest in Africa? 80.62% versus 53.10% (PMID 38521116), with the African estimate resting on very few studies. Whether this is real or an artefact of ascertainment is unresolved, and it parallels the unexplained regional variation in non-invasive test accuracy (noninvasive assessment).
  • Does MASLD accelerate diabetes, or vice versa? Genetic-instrument studies have separated the directions, but results depend on phenotype and instrument. One analysis found no persuasive causal effect in either direction (PMID 37223039); a bidirectional two-sample study found NAFLD→T2D (OR 1.1089) but no reverse effect, while liver fat and T2D showed bidirectional effects (PMID 37931882); shared-genetics analysis also supported NAFLD→T2D more strongly than the reverse (PMID 39690818). The remaining gap is triangulation with longitudinally adjudicated MASLD and incident diabetes rather than absence of genetic evidence.
  • Should liver fibrosis join retinopathy, nephropathy and neuropathy as a tracked diabetes complication? That is the ADA's explicit framing (PMID 40434108); no health system has reported implementation data.

References

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