A Biological-Systems-Based Analyses Using Proteomic and Metabolic Network Inference Reveals Mechanistic Insights into Hepatic Lipid Accumulation: An IMI-DIRECT Study.

Atabaki NN, Coral DE, Pomares-Millan H, Smith K, Behjat HH, Koivula RW, Tura A, Miller H, Pinnick K, Agudelo L, Allin KH, Brown AA, Chabanova E, Chmura PJ, Jacobsen UP, Dawed AY, Elders PJM, Fernandez-Tajes JJ, Forgie IM, Haid M, Hansen TH, Hansen EL, Jones AG, Kokkola T, Kalamajski S, Mahajan A, McDonald TJ, McEvoy D, Muilwijk M, Tsirigos KD, Vangipurapu J, van Oort S, Vestergaard H, Adamski J, Beulens JW, Brunak S, Dermitzakis ET, Giordano GN, Gupta R, Hansen T, Hart LT, Hattersley AT, Hodson L, Laakso M, Loos RJF, Merino J, Ohlsson M, Pedersen O, Ridderstråle M, Ruetten H, Rutters F, Schwenk JM, Tomlinson J, Walker M, Yaghootkar H, Karpe F, McCarthy MI, Thomas EL, Bell JD, Mari A, Pavo I, Pearson ER, Viñuela A, Franks PW

medRxiv - (-) - [2025-06-02; online 2025-06-02]

To delineate organ-specific and systemic drivers of metabolic dysfunction-associated steatotic liver disease (MASLD), we applied integrative causal inference across clinical, imaging, and proteomic domains in individuals with and without type 2 diabetes (T2D). We used Bayesian network analyses to quantify causal pathways linking adipose distribution, glycemia, and insulin dynamics with fatty liver using data from the IMI-DIRECT prospective cohort study. Measurements were made of glucose and insulin dynamics (using frequently-sampled metabolic challenge tests), MRI-derived abdominal and liver fat content, serological biomarkers, and Olink plasma proteomics from 331 adults with new-onset T2D and 964 adults free from diabetes at enrolment. The common protocols used in these two cohorts provided the opportunity for replication analyses to be performed. When the direction of the effect could not be determined with high probability through Bayesian networks, complementary two-sample Mendelian randomization (MR) was employed. High basal insulin secretion rate (BasalISR) was identified as the primary causal driver of liver fat accumulation in both diabetes and non-diabetes. Excess visceral adipose tissue (VAT) was bidirectionally associated with liver fat, indicating a self-reinforcing metabolic loop. Basal insulin clearance (Clinsb) worsened as a consequence of liver fat accumulation to a greater degree before the onset of T2D. Out of 446 analysed proteins, 34 mapped to these metabolic networks and 27 were identified in the non-diabetes network, 18 in the diabetes network, and 11 were common between the two networks. Key proteins directly associated with liver fat included GUSB, ALDH1A1, LPL, IGFBP1/2, CTSD, HMOX1, FGF21, AGRP, and ACE2. Sex-stratified analyses revealed distinct proteomic drivers: GUSB and LEP were most predictive of liver fat in females and males, respectively. Basal insulin hypersecretion is a modifiable, causal driver of MASLD, particularly prior to glycaemic decompensation. Our findings highlight a multifactorial, sex- and disease-stage-specific proteo-metabolic architecture of hepatic steatosis. Proteins such as GUSB, ALDH1A1, LPL, and IGFBPs warrant further investigation as potential biomarkers or therapeutic targets for MASLD prevention and treatment.

PubMed 40502600

DOI 10.1101/2025.06.02.25328773

Crossref 10.1101/2025.06.02.25328773

pmc: PMC12155020
pii: 2025.06.02.25328773