Identification of ACBP as a potential target in ciliopathic obesity through multi-omics network analysis

Domain: neuroscience
Published: 2026-01-09
Editorial outcome: major_revision

Abstract
Ciliopathies are genetic disorders characterized by defective primary cilia function, with obesity as a clinical manifestation in certain cases, including Alström syndrome, which is caused by ALMS1 mutations. The link between cilia and lipid metabolism remains poorly understood, but evidence suggests a role for impaired autophagy. Autophagy affects both intra- and extracellular levels of ACBP, which can act as an obesogenic factor. Our multi-omics study reveals early hepatic dyslipidemia, impaired autophagy, and hepatic accumulation of ACBP in presymptomatic male mice lacking Alms1 gene. These conditions are consistent with the obesogenic phenotype and with alterations in the gut microbiota that manifest as the mice age and develop obesity. Importantly, reducing excessive ACBP with a neutralizing monoclonal antibody limits weight gain and metabolic defects in Alms1-/- mice in an autophagy-independent manner. Altogether, the data support the idea that ciliopathy-associated obesity, particularly Alström syndrome, may be mitigated by ACBP neutralization.

Introduction
The primary cilium is an elongated cellular organelle consisting of a membrane-enclosed axoneme composed of microtubules and a basal body derived from a centriole that plays a key role in regulating diverse cellular processes including metabolism1,2. Defects in cilia function trigger a group of disorders known as ciliopathies3. One of these diseases is Alström syndrome (AöS), a rare autosomal recessive and pleiotropic disorder, caused by mutations in the ALMS1 gene4. AöS presents metabolic problems, such as insulin resistance, diabetes, obesity, and liver abnormalities5–8, and non-metabolic symptoms, such as sensorineural hearing loss, retinal degeneration and cardiomyopathy leading to heart failure. Most current treatments for AöS primarily focus on palliative care, addressing individual symptoms without actually curing or preventing the disease9.

The mechanisms by which obesity may be related to ciliary dysfunction remain unclear, but recent research suggests a potential link through impaired autophagy. Autophagy is an evolutionarily conserved catabolic process that allows cells to eliminatedysfunctional components by sequestering them within double-membrane autophagosomes10–13. Ciliogenesis and autophagy are both activated during nutritional deprivation, and both are necessary for the maintenance of bioenergetic homeostasis14,15. In addition, ciliogenesis and autophagy exhibit bidirectional functional connections. The cilium-dependent signaling is necessary for the formation of the autophagosome through the recruitment of proteins related to autophagy. Conversely, autophagy regulates both ciliogenesis and the length of the cilium through the degradation of specific proteins involved in the formation of cilia15–18. Moreover, autophagy functions as a survival mechanism that allows cells to adapt to environmental changes and contributes to cellular health by the selective removal and recycling of damaged cellular components. Autophagy also contributes to pathogens defense and atypical protein secretion, concerning factors like interleukin-1, interleukin-6 and acyl-CoA binding protein (ACBP)19–22. This wide range of cellular functions makes the maintenance of cellular homeostasis, both under physiological and pathological conditions, closely dependent on the autophagic capacity23. Thus, the cell responds to alterations in the extracellular and intracellular environment by adjusting the autophagic flux in response to internal metabolic demands, thereby contributing to stress adaptation, organismal homeostasis and healthy ageing12. In fact, several genetic or pharmacological autophagy activation confer improvements in health and lifespan to model organisms, including yeast, nematodes, flies and mice24. Conversely, deficient autophagy contributes to the development of major human diseases, including neurodegenerative and cardiovascular diseases, carcinogenesis and metabolic syndrome25,26. Prolonged genetic or pharmacological autophagy inhibition promotes an obesogenic phenotype and compromises weight loss during fasting.

ACBP has emerged as a novel lipogenic factor that is altered in obesity20, and anorexia27. Studies in animal models and cell cultures demonstrated that acute nutrient deprivation and autophagic activation led to ACBP secretion, reducing intracellular ACBP and increasing extracellular ACBP. Pharmacological ACBP reduction with neutralizing antibodies mimics the effects of a low-calorie diet or increased physical activity, enhancing lipolysis, and causing temporary hyperglycemia, which inhibits food intake. Conversely, systemic administration of recombinant ACBP results in temporary hypoglycemia as glucose is redirected for lipid synthesis, increasing appetite20,28–33. In fact, it has recently been described that supplementation with extracellular ACBP might constitute a viable strategy for treating anorexia nervosa and chemotherapy-induced cachexia27.

Our research aims to investigate the interplay between primary cilia, autophagy, and ACBP in AöS. As shown here, we observed that the ALMS1 mutation in mice caused a systemic autophagy defect coupled to increased ACBP levels. Neutralization of ACBP fully prevented the development of obesity, arguing in favor of a pathogenic role of ACBP in AöS.

Results
Asymptomatic Alms1-/- mice: early metabolic alterations
To characterize the metabolic events occurring in mice both prior to (Fig. 1) and after the onset of obesity associated with AöS (Fig. 2), we conducted metabolomic analyses of the liver, white adipose tissue (WAT), and plasma, and transcriptomic analyses of the liver, from Alms1 deficient (Alms1-/-) mice, which express a truncated protein without any residual function (Fig. 1a). As previously described34, no changes in body weight were observed between Alms1 wild-type (WT) and Alms1-/- mice up to 8 weeks of age. However, at a later stage, these strains of mice gradually diverged in their body weight, and Alms1-/- mice developed hyperglycemia (Fig. 1b, c). To unravel the metabolic modifications associated with the onset of obesity and diabetes, we conducted metabolomic and transcriptomic analyses on WT and Alms1-/- mice at three distinct ages: at 6 weeks of age (before the development of AöS symptoms), at 10 weeks of age (when Alms1-/- mice have acquired initial signs of an AöS-like phenotype, including obesity), and at 20 weeks of age (when Alms1-/- mice have developed an advanced AöS-like phenotype) (Fig. 1d).

We compared the metabolome of 6-week-old WT and Alms1-/- mice, which are indistinguishable with respect to their body weight and blood glucose levels (Supplementary Fig. 1a–c). At this early, pre-obese stage, differential enrichment metabolomic analysis identified metabolic alterations primarily in the liver (Fig. 1e, f and Supplementary Data 1), with 77 metabolites dysregulated due to the Alms1 mutation. In the plasma, Alms1-/- mice exhibited a selective reduction of one single metabolite, N-acetyl-DL-tryptophan (Supplementary Fig. 1d and Supplementary Data 1). In WAT, young Alms1-/- mice manifested a significant reduction in two metabolites, spermine and prostaglandin E1 (Supplementary Fig. 1e and Supplementary Data 1). Livers from Alms1-/- mice exhibited impaired lipid metabolism, marked by significant reductions in acylcarnitines, free fatty acids, and phosphatidylcholines (Fig. 1f). Additional alterations were observed in various pathways involving linoleic and linolenic acids, specifically phosphatidylethanolamine biosynthesis, as well as the transport of acyl groups into mitochondria, among others (Supplementary Fig. 1f–h). These findings highlight the liver’s central role in AöS pathogenesis. Consequently, we performed transcriptomic analyses of livers from 6-week-old WT and Alms1-/- mice (Fig. 1g–h and Supplementary Data 2), revealing alterations in the expression of 19 hepatic genes, highlighting genes related to metabolic stress, inflammation, and the regulation of protein synthesis.

Transcriptome and metabolome analysis in obese Alms1-/- mice
Next, we compared the metabolic profiles of early obese 10-week-old Alms1-/- mice with those of WT mice with diet-induced obesity (DIO) (Supplementary Fig. 2a and Supplementary Data 3). As expected, most of the metabolic alterations overlapped among both models of obesity (Fig. 2a, b and Supplementary Fig. 2b), suggesting that they cannot be attributed to specific effects of the Alms1 mutation itself. Therefore, we focused on metabolites that were modulated in Alms1-/- mice only, not by DIO (Fig. 2c). Alms1-/- mice, but not DIO mice, exhibited the accumulation of glucuronic and succinic acid, as well as increased C6:0 and C5:0 carnitines (red square in Fig. 2c). We also observed, among other changes, a decrease in phosphatidylcholine (17:0) and retinoic acid in Alms1-/- mice, but not in DIO mice (blue square in Fig. 2c), indicating an Alms1 mutation-dependent mitochondrial dysfunction and alterations in fatty acid β-oxidation.

Finally, as compared to their WT controls, 20-week-old AöS Alms1-/- mice were markedly overweight and hyperglycemic (Supplementary Fig. 2c–e) and exhibited numerous differences in their mass spectrometric metabolomics profile (Supplementary Data 4) that affected plasma (Supplementary Fig. 2f), WAT (Supplementary Fig. 2g) and liver (Fig. 2d, e and Supplementary Fig. 2h). In addition, 20-week-old AöS Alms1-/- mice exhibited numerous changes in gene expression in the liver (Fig. 2f, g and Supplementary Data 5). These changes concerned multiple biochemical pathways, including lipid, carbohydrate and protein metabolism, suggesting a rather widespread metabolic perturbation in advanced AöS.

Disabled autophagy and elevated ACBP levels in AöS
Next, we examined the hepatic genes and proteins associated with lipid metabolism from pre-syndromic (6-week-old) and syndromic (20-week-old) Alms1-/- mice (Fig. 3 and Supplementary Fig. 3). Consistent with the results observed in the transcriptomic analyses (Supplementary Data 2 and 5), livers from 6-week-old Alms1-/- mice revealed no significant changes in mRNAs related to lipogenesis, including fatty acid synthase (Fasn), peroxisome proliferator-activated receptor gamma (Pparg), acetyl-CoA carboxylase 1 (Acc1), sterol regulatory element binding protein (Srebp1) and Acbp, or related to lipolysis, as AMP-activated protein kinase (Ampk) and carnitine palmitoyltransferase 1 (Cpt1). However, livers from 6-week-old Alms1-/- mice exhibited an important reduction in mRNAs coding for peroxisome proliferator-activated receptor gamma coactivator 1 (Pgc1), adipose triglyceride lipase (AtgL) mRNAs (Supplementary Fig. 3a). In 20-week-old Alms1-/- mice several lipogenesis genes (Acc1, Cpt1, Fasn, Srebp1 or Pparg) were upregulated, but hepatic Acbp mRNA levels remained stable (Supplementary Fig. 3b). This contrasted with the observation that ACBP protein was elevated in both 6- and 20-week-old Alms1-/- mice compared to WT mice (Fig. 3a, b). We therefore measured autophagy, which is known to affect intracellular ACBP protein levels at the post-transcriptional level. We observed a significant increase in the autophagy substrate sequestosome 1 (SQSTM1, best known as p62) levels in both 6- and 20-week-old Alms1-/- mice, as compared to age-matched WT controls, suggesting a reduction in autophagic flux (Fig. 3a, c). The ratio of lipidated over non-lipidated microtubule-associated protein light chain 3 (LC3-II/LC3-I) (Fig. 3a, d), was not changed at younger but increased in adult mice. These results suggest that autophagy is blocked through different steps: (i) early, before autophagosome formation at 6 weeks of age (Fig. 3a–d), corroborated with an autophagic flux inhibitor, such as leupeptin, that effectively increases ACBP and SQSTM1 levels (Fig. 3e–f and Supplementary Fig. 3c) and showed a decrease in the degradation flux (Fig. 3g); (ii) late, after autophagosome formation at 20 weeks of age (Fig. 3a–d).

Plasma ACBP levels were indistinguishable in 6-week-old Alms1-/- and WT mice, but significantly increased in obese 20-week-old Alms1-/- mice (Fig. 3h). Following 24 hours (h) of caloric restriction (starvation), 6-week-old Alms1-/- mice demonstrated the capacity to release intracellular ACBP, in the same manner as occurs in WT mice (Fig. 3i). Moreover, both Alms1-/- and WT mice exhibited similar weight loss upon starvation (Supplementary Fig. 3d). Hence, despite underlying deficiencies in basal autophagy, Alms1-/- mice respond to autophagic stimuli.

There is no evidence that the anti-ACBP mAb would reach the intracellular space, but prior studies indicate that extracellular ACBP elicits a feedforward loop elevating the expression of intracellular ACBP due to a cascade of events that involves activation of GABA A receptor 1 (to which ACBP binds via an interaction with the γ2 chain) and the PPARγ-mediated transactivation of the DBI gene, which encodes for ACBP32,35. For this reason, inhibition of extracellular ACBP diminishes intracellular ACBP levels32,35. To elucidate the effects of ALMS1 on autophagy and intracellular ACBP levels, we isolated primary hepatocytes from both WT and Alms1-/- mice. Alms1-/- hepatocytes contained higher levels of FASN, p62/SQSTM1 and ACBP (Fig. 3j, k). Similarly, depletion of ALMS1 from HepG2 cells by temporary knockdown (KD) of Alms1 with siRNAs (Fig. 3l, m and Supplementary Fig. 3e) or stable knockout (KO) of Alms1 by CRISPR-Cas9 technology (Fig. 3n–p and Supplementary Fig. 3f, g) increased the intracellular abundance of ACBP by approximately 50% compared to control cells.

ACBP neutralization and lipid metabolism in ALMS1 models
Previous research has established an obesogenic role for ACBP, which stimulates lipogenesis. Therefore, we investigated whether ACBP contributes to the phenotypic manifestations of ALMS1-deficient mice. For this, we reduced the elevated levels of ACBP observed in Alms1-/- mice by administration of an anti-ACBP monoclonal antibody (mAb) or, as a control, an isotype-matched (IgG2) irrelevant antibody for 4 weeks. In WT mice, neutralization of ACBP with this mAb and the conditional knockout of ACBP is known to have similar metabolic consequences, including a reduction in food intake, a switch from lipo-anabolism to lipo-catabolism, anti-obesity and antidiabetic effects, and protection of various organs against cytotoxic insults35,36. These findings suggest that anti-ACBP mAb mediated its effects through on-target mechanisms. The treatment of Alms1-/- mice with mAb involved two approaches: (i) curative, consisting in the treatment of 20-week-old mice with an established AöS phenotype for 4 weeks (Supplementary Fig. 4a); or (ii) preventive, consisting in the treatment of 6-week-old mice without an AöS phenotype for 4 weeks (Supplementary Fig. 4b). In the curative approach, anti-ACBP mAb failed to cause weight reduction in Alms1-/- mice compared to the IgG2 isotype-treated control mAb (Fig. 4a), although anti-ACBP mAb reduced food intake (Supplementary Fig. 4c). However, in the prophylactic approach, anti-ACBP mAb achieved significant prevention of weight gain in Alms1-/- mice (Fig. 4b) but not in WT mice compared to isotype controls (Supplementary Fig. 4d). This preventive effect on weight gain was confirmed in experiments in which anti-ACBP mAb was administered to 4-week-old Alms1-/- mice (Supplementary Fig. 4e). Of note, in the preventive setting, ACBP neutralization also normalized the glucose tolerance test in Alms1-/- mice (Fig. 4c). In parallel, injection of anti-ACBP mAb into Alms1-/- mice caused a decrease in organ weight, adipocyte size, liver and brown adipose tissue lipid content (Fig. 4d, e and Supplementary Fig. 4f–j), as well as liver FASN protein levels (Fig. 4f, g) but failed to affect liver p62/SQSTM1 levels (Fig. 4f, g). We also isolated primary hepatocytes from WT and Alms1-/- mice and treated them with the same anti-ACBP mAb (Fig. 4h, i) or silenced Acbp with siRNAs (Supplementary Fig. 4l, m). Both methods of ACBP inhibition decreased FASN levels but failed to reduce SQSTM1 abundance.

Finally, we probed lipogenic labeling in Alms1⁻/⁻ mice by intraperitoneal administration of ¹³C-labeled glucose (Supplementary Fig. 4n). Under these conditions, we observed a significant uncoupling of ¹³C-glycerol-3-phosphate (gly3P), increased in plasma and decreased in liver, compatible with rapid utilization toward esterification (Supplementary Fig. 4o). In contrast, hepatic ¹³C-palmitate enrichment 2h after ¹³C-glucose injection was directionally higher in obese Alms1-/- than in WT mice (unpaired two-sided Student’s t test; two-sided nominal P-value = 0.049; exact values are shown in Source Data) and positively correlated with body weight, but this difference did not remain significant after correction for multiple comparisons (Fig. 4j, k). Collectively these tracer data are consistent with lipid-anabolic signatures, but do not establish causal changes in de novo lipogenesis rates, which would require dedicated flux analyses.

Multi-omics after ACBP neutralization in Alms1-/- mice
To further investigate the metabolic impact of ACBP neutralization on Alms1-/- mice in the preventive setting, we conducted integrated multi-omics analyses, including metabolomics, transcriptomics, and proteomics, focused on the liver, the primary target tissue (Fig. 5, Supplementary Fig. 5 and Supplementary Data 3, 7–8).

Across all omics methods, we observed that ACBP neutralization reversed significant changes at the early disease stage (10 weeks of age), indicated by opposing log fold changes (FC) in untreated WT vs Alms1-/- tissues and anti-ACBP mAb-treated vs untreated Alms1-/- tissues (Supplementary Fig. 5). The metabolomic, transcriptomic and proteomic (Fig. 5a–c) alterations observed in Alms1-/- mice negatively correlated with the modulations observed after the treatment with anti-ACBP mAb (Pearson correlation value for the combined dataset: r = −0.82) showing a close-to-complete normalization of the Alms1-/- phenotype by ACBP neutralization (Fig. 5d).

Previously, Fig. 2 demonstrated the multiple metabolic changes in obese mice, whether induced by HFD and/or by the Alms1 mutation. Among these alterations, we observed that the anti-ACBP treatment is able to reverse changes common to both types of obesity (Fig. 5e and Supplementary Fig. 2b), such as alterations in folic acid, acylated phosphatidylcholine (15:0) or dihydrobiopterin. However, there are other metabolic changes reversed by the treatment that are exclusively Alms1-/- dependent (not observed in the HFD model) (Figs. 5e and 2c and Supplementary Data 3). These include the reversal of increased succinic acid and gluconic acid, as well as the decrease in malic acid, 3-methylhistidine, and acylated phosphatidylcholines (17:0), indicating a correction of metabolic and mitochondrial dysfunction that is Alms1 mutation-dependent rather than a mere consequence of reduced weight.

At the level of the hepatic transcriptome (Fig. 5f) Alms1-/- mice manifested altered transcription of key genes involved in energy, lipid, and mitochondrial metabolism. ACBP neutralization reduced transcription of lipogenic genes such as Cd36, Cidec, Fasn, Srebf1, and Scd1, which are associated with lipid accumulation. Conversely, ACBP neutralization increased transcription of genes related to lipolysis, such as Angptl4, Cyp4f13, Cyp4f15, Cyp7b1, Pla2g7, and Ppp2r1a, as well as that of other genes like Irs2, Pck1, and Slc7a2, suggesting an improvement in glucose homeostasis and insulin sensitivity (Supplementary Data 7).

In terms of the hepatic proteome, ACBP neutralization induced relatively few changes in enzymes involved in lipid metabolism in Alms1-/- mice (Fig. 5g). Nonetheless, the decrease in Hadhb (hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex beta subunit) is noteworthy, suggesting reduced use of beta-oxidation in a fat-burning context (Supplementary Data 8).

Overall, these data suggest that ACBP neutralization normalizes shifts in lipid, energy, and glucose metabolism in the liver from Alms1-/- mice, in accord with the normalization of other parameters such as weight gain.

ACBP neutralization and gut microbiota in Alms1-/- mice
The fecal microbiota of WT or Alms1-/- mice that were treated with isotype control or anti-ACBP mAb showed no significant differences in diversity or richness (Supplementary Fig. 6a, b). However, significant differences were found in composition (Supplementary Fig. 6c) at the phylum and genus levels (Supplementary Fig. 6d and Supplementary Data 9). To explore genotype- vs obesity-dependent effects, we included three controls: 3-week-old WT and Alms1-/- mice (which are still lean) and 10-week-old mice with high-fat diet (HFD)-induced obesity (Fig. 6a–d and Supplementary Fig. 6d). This initial analysis allowed us to evaluate the modulated taxa in the 10-week-old obese Alms1-/- mice and analyzed their potential causes, as well as the ability of the mAb treatment to reverse these changes. Alms1-/- obese mice, exhibited a decrease in Akkermansia, Alistipes, Allobaculum, Prevotella, Ruminococcaceae, and an increase in Anaeroplasma, Clostridiales, Desulfovibrio, Desulfovibrionaceae, Lactobacillus, Rikenellaceae_AF12, Rikenellaceae and Roseburia (Fig. 6c, e). Notably, only the increase in Desulfovibrio was already observed in lean 3-week-old Alms1-/- mice (Fig. 6c). Many Alms1-/- mutation associated changes (e.g., in Allobaculum, Akkermansia, Roseburia, and Clostridiales) also appeared in DIO, whereas others, such as increased Desulfovibrio and Rikenellaceae_AF12 and decreased Ruminococcaceae and Alistipes, were specifically associated with the Alms1-/- genotype (Fig. 6d).

Using the global FDR-controlled differential-abundance analysis, anti-ACBP treatment in Alms1-/- mice was associated with significant changes in a small set of taxa, decreases in Adlercreutzia, Butyricicoccus, Candidatus Arthromitus and Desulfovibrio, and increases in Lachnospiraceae and Ruminococcus (q<0.05; Supplementary Data 9). To prioritize targeted post-hoc testing, we first selected candidate taxa from the baseline WT vs Alms1-/- contrast using LEfSe (Fig. 6e), and then evaluated the treatment contrast (WT vs Alms1-/- vs treated Alms1-/- mice) with Tukey-adjusted post-hoc tests in those taxa. This specific analysis revealed that there were no effects of treatment in some taxa, even reversing the obesogenic phenotype (Supplementary Fig. 6e). However, we observed reversions of the Alms1-linked dysbiosis after anti-ACBP, with Desulfovibrio, Roseburia, Rikenellaceae_AF12, and Ruminococcaceae moving toward Alms1 WT levels (Fig. 6f). Importantly, Desulfovibrio satisfied both criteria, remaining significant under the FDR analysis and in the Tukey contrasts, and was already elevated at the presymptomatic stage, highlighting it as a priority taxon for follow-up.

Methods
Inclusion & ethics statement
This study complies with all relevant ethical regulations. All procedures involving animals were conducted in accordance with the European Directive 2010/63/EU, Spanish Royal Decree 53/2013, and the NIH Guide for the Care and Use of Laboratory Animals. Experimental protocols were reviewed and approved by the Animal Welfare Body of the Universidad Complutense de Madrid and by the Animal Experimentation Ethics Committee of the Comunidad de Madrid (protocol PROEX012_8-21).

Animals and treatments
The “Fat Aussie” (NOD.B10-Alms1^foz/foz) mouse strain was kindly provided by Dr. Christopher C. Goodnow53 and maintained in the animal facility at Complutense University of Madrid under specific pathogen-free conditions with 12h light/12h dark cycle and temperature (19–23°C) and relative humidity (45–65%) according to FELASA guidelines. Only male mice were used in this study to avoid the potential confounding effects of the estrous cycle on metabolic, transcriptomic, proteomic, and microbiota profiles. Since hormonal fluctuations in females can introduce additional variability, male mice were selected to improve the reproducibility and consistency of the data across the multi-omics analyses performed.

After genotyping, healthy male mice were used. For experiments without microbiota, animals were stratified by litter and basal body weight and randomly assigned (computer-generated list) to the corresponding diet and, where applicable, treatment. Experimental cages contained randomly selected male mice to mitigate potential effects of cage-specific microbial changes. Importantly, the observed phenotypic differences between groups remained robust regardless of the cohousing strategy, supporting the reliability of our conclusions. For microbiota experiments, the cohousing strategy was designed to prevent microbiota exchange through coprophagy. Samples were collected from cages containing mice under identical experimental conditions to ensure consistency. To control covariates in metabolomics, we applied the predefined inclusion window (±10% body-weight and glycemia).

Male mice received normal chow (LASQCdiet, cat. D.Rod18.H; protein 18.9%, fat 5.3%, fiber 3.9 %, ash 7.0 %; with vitamins and minerals) with access to water ad libitum. To obtain the DIO-mice model, male animals were fed with a high fat diet (HFD) (Envigo cat. MD.2204 Adjusted 60/Fat Diet, protein 23%, fat 34%, fiber 5%, ash 5%; with vitamins and minerals) with an excess of dietary fats until 10 weeks old. Diets were supplied as pellets (16 mm) and stored at 4°C.

On breeding, the genotype was verified by polymerase chain reaction (PCR) using genomic DNA isolated from tail biopsies with specific primer pairs detailed in Supplementary Data 10. PCR products were separated by electrophoresis in 4% agarose gels (R0492, Thermo Fisher Scientific) and visualized using GelRed (BT-41003, Biogen).

Tissues were snap-frozen in liquid nitrogen, extracted and homogenized in 20mM Tris buffer (pH 7.4) containing 150mM NaCl, 1% Triton X-100, 10mM EDTA, phosphatase inhibitor cocktail (4906837001, Roche) and protease inhibitor cocktail tablets (11836170001, Roche). Tissue extracts were then centrifuged at 10000 xg (4°C), and supernatants were collected. Protein concentration in supernatants was evaluated by the bicinchoninic acid technique (23225, Pierce Biotechnology). Plasma was harvested from blood collection tubes by centrifugation at 10000 xg for 30min.

Male mice were analyzed at baseline or after one month of treatment with a monoclonal antibody against ACBP or isotype IgG (Bioxcell, NH, USA) (2.5µg/g body weight, BW intraperitoneally in 200µL of saline) administered in 5 doses, once per week. Leupeptin (30mg/kg BW; 108976, Sigma-Aldrich) was used in vivo by intraperitoneal injection 6h before the end of the experiment.

Presymptomatic cohorts consisted of 6-week-old male mice, and symptomatic cohorts were 20-week-old. Prevention studies used mice at 6 weeks of age, administered the assigned treatment for 4 weeks, and were analyzed at 10 weeks, and curative studies started treatment at 20 weeks of age and were analyzed at 24 weeks.

ACBP detection in murine plasma samples
ACBP levels in plasma were determined using a specific ELISA kit (MBS2025156, MyBioSource) as instructed by the manufacturer.

Glucose tolerance test (GTT)
Male animals were fasted for 16h and given an intraperitoneal injection of glucose (2.5g/kg BW). Blood was collected each 30min from the lateral vein of the tail prior to and at the indicated time points after the injection. Glucose was measured using a precision glucometer (Accu-Chek Performa).

¹³C-Glucose tracing
To assess lipid metabolism, mice completed a 4-week preventive anti-ACBP treatment; the last antibody dose was given 30min before tracer administration. After an overnight fast, mice received an intraperitoneal injection of anti-ACBP monoclonal antibody or isotype IgG control. Thirty minutes later, mice were injected i.p. with [U-¹³C₆]-D-glucose (Merck/Sigma-Aldrich, 389374; 2.5gkg⁻¹ in saline). Two hours after tracer injection, mice were euthanized, and plasma and liver were collected. ¹³C-labeled metabolites were quantified by mass spectrometry.

Food intake analysis
Male mice were housed and acclimated to the chambers for 48h before experimental measurements and food intake was measured by weighting the food consumed by mice each 6h.

Histology
After fixation of liver and white adipose tissues, 4µm thick paraffin sections were stained with hematoxylin and eosin. Each slide was examined using a Zeiss Axiophot microscope.

Cell culture and treatments
HepG2 cells (HB-806, ATCC) obtained from human hepatocellular carcinoma were cultured at 37°C under 5% CO2 in Dulbecco’s Modified Eagle Medium (DMEM) (41966029, Gibco) containing D-glucose 25mM, sodium pyruvate 1mM, L-glutamine 4mM, and supplemented with 10% heat-inactivated fetal bovine (10500064, Gibco), HEPES buffer 1M (15630056, Gibco), and 10000 units/mL penicillin G sodium and 100000µg/mL streptomycin sulfate (15140122, Gibco). Cells were seeded in 6–12-well plates and grown for 36h before treatment with 50nM BafA1 (S-S1413, Selleckchem), EBSS medium (24010043, Gibco) or anti-ACBP (or respective isotype control) in vitro (1–10µg/mL; ab232760, Abcam). Treatments were maintained for a period of 4h.

Primary hepatocyte isolation and cultures
Mice were injected intraperitoneally with 150µL of 1000U/mL heparin 5min prior to anesthesia with a ketamine/xylazine mixture (30mg/mL and 6mg/mL, respectively, in saline serum) 3.75µL/g body weight. Once the mouse was properly anesthetized and didn’t present signs of consciousness nor reflexes, the abdomen was vertically cut to have access to the vena cava. Perfusion was initiated by attaching a catheter to the inferior vena cava, followed by a sequence of perfusion solutions (1.50mL EBSS w/o Ca&Mg + 250µL 100mM EGTA, 2.30mL EBSS with Ca&Mg + 10mM HEPES (pH 7.4), and 3.2×50mL Solution 2 + 0.3mg/mL Collagenase + 0.04mg/mL trypsin inhibitor 100cdu/mL − 100mL) pre-heated at 42°C. Liver digestion was monitored, and after sufficient digestion, the liver was transferred to Solution 4 (Williams E medium + 2mM (1%) L-glutamine + 1% Penicillin/Streptomycin + 10% FBS) and disrupted with a forceps for posterior cell isolation. Hepatocytes were filtered through a 100µm cell strainer, centrifuged a 500×g for 3min 4°C, and washed with Williams E medium 3 times. Living hepatocytes were then counted using Trypan blue and plated on 6-well plates (106 cells per well). After 4–6h, plated hepatocytes were washed with sterile PBS, and the media (Solution 4) was renewed before subsequent assays54,55. Materials: water (50mL), ethanol (50mL), peristaltic pump, water bath, Falcon tube holders (9-tube and 16-tube), Vacutainer Safety-Lok Blood Collection Set, syringes (1mL), 27G needles, paper roll, tray, tape, and various reagents including calcium and magnesium-free EBSS (Gibco™, 12539069), EGTA, HEPES, Williams E medium (Gibco™, 11570606), L-glutamine, penicillin/streptomycin, fetal bovine serum (FBS), collagenase type IV (Thermo, 17104019), trypsin inhibitor (Merck, T6522), heparin, ketamine, and xylazine. Solutions were prepared for hepatocyte isolation, including EGTA-EBSS, HEPES-EBSS, and a collagenase solution. Equipment was set up prior to the experiment, including a water bath (42°C), a peristaltic pump, and a cell culture hood, with sterile pipettes, Petri dishes, and other consumables prepared.

RNA interference and plasmid transfection
Full details of all oligonucleotides and plasmids are found in Supplementary Data 10. Cells were transfected at 50–60% confluence using medium without antibiotics. Specific siRNAs for ACBP and/or ALMS1 were reverse transfected at a concentration of 10nM using Lipofectamine RNAi MaxTM Transfection Reagent (13778075, Invitrogen) for 36–48h before treatments. A scrambled siRNA was always used as a control, and siRNA-mediated protein downregulation was controlled by immunoblotting. The CRISPR/Cas9 ALMS1-encoding plasmids (KN414632, OriGene) were also applied by lipofectamine transfection according to the manufacturer’s instructions, and cells were analyzed after puromycin (P8833, Sigma) selection. The insertion of the linear donor was verified by PCR (Supplementary Data 10). To confirm transfection, cells were fixed in 4% paraformaldehyde for 15min at room temperature, and GFP fluorescence was assessed (Leica DMI 3000 microscope; Leica AG, Wetzlar, Germany).

ACBP detection in culture medium
ACBP levels in culture medium were determined using a specific human ELISA kit (KA0532-96, Abnova) as instructed by the manufacturer.

Immunoblotting
For immunoblotting, tissue or cellular proteins were collected and resuspended in 50mM Tris buffer (pH 7.4) containing 250mM NaCl, 0.5% NP-40, 5mM EDTA, 50mM NaF, phosphatase inhibitor cocktail (4906837001, Roche Applied Science) and protease inhibitor cocktail tablets (11836170001, Roche Applied Science) and 15–20µg were loaded on 4–12% polyacrylamide gel (5678094, Biorad). The gels were initially run without the protein samples for 60min at 70V, followed by the inclusion of samples for a duration of 60–90min at 110–130V, aimed at enhancing the separation of smaller proteins. Samples are electrotransferred to PVDF membranes (3010040001, Roche), which were horizontally sliced according to the molecular weight of the protein of interest to allow simultaneous detection within the same experiment. Unspecific binding sites were saturated by incubating membranes for 1hour in 0.1% Tween-20 (BP337-100, Fisher Bioreagents) (v:v in TBS) supplemented with 5% non-fat powdered milk (w:v in TBS), followed by overnight incubation with specifics primary and secondary antibodies: ACBP (human, Abcam ab16871, rabbit pAb, 1:1000, lot GR121034-6); ACBP (mouse, Abcam ab231910, rabbit pAb, 1:1000, lots GR3413135-1; GR3236201-4); ALMS1 (Abcam ab84892, rabbit pAb, 1:1000, lot GR288319-18); FASN (Abcam Ab22759, rabbit pAb, 1:1000, lot Gr3422783-1); GAPDH (CST#2118, clone 14C10, rabbit mAb, 1:5000, lots 14; 16); LC3B (CST#2775, rabbit pAb, 1:1000, lots 14; 13); p62/SQSTM1 (Abnova #H00008878 M01, clone 2C11, mouse IgG2a, 1:5000, lots M591-2C11; N3131-2C11). Secondary antibodies: anti-rabbit IgG–HRP (Sigma A0545, goat pAb, 1:5000, lot 0000130704) and anti-mouse IgG–HRP (Sigma A9044, rabbit pAb, 1:5000, lots 0000118493; 0000127278). All info is also detailed in Supplementary Data 10. Signals from the protein bands were detected using chemiluminescence (EPN2235, Cytiva Amersham).

Gene expression analysis
Total RNA from cell lines was purified using QIAwave RNA Mini Kit (74536, QIAGEN) and total RNA from murine tissues was isolated by trituration with a motorized micro pestle, followed by column purification with QIAwave RNA Mini Kit (74536, QIAGEN). Following the manufacturer’s instructions, the High-Capacity cDNA Reverse Transcription Kit (10400745, Applied Biosystems) was used for the generation of cDNA. Quantitative PCR was performed on a StepOnePlus Real-Time PCR System (Applied Biosystems) using PowerUp SYBR Green (A25777, Applied Biosystems). All oligonucleotide sequences are provided in Supplementary Data 10 together with catalog numbers, annealing temperatures and amplicon sizes.

Metabolome analysis
Samples were treated following the protocol described previously56 to extract metabolites. Briefly, 50µL of serum were vortexed with 500µL of ice-cold extraction mixture (MeOH/water, 9/1, −20°C, with a cocktail of internal standards) for 5min, and then centrifuged (10min at 15000 xg, 4°C). Regarding the tissue, 30mg were weighed and homogenized by a Precellys (Bertin) protocol (3 cycles, 5500rpm), then centrifuged (10min at 15000 xg, 4°C). After, several fractions of the supernatant were split to be analyzed by different Liquid and Gas chromatographies coupled with mass spectrometers (LC/MS and GC/MS) as previously described57.

Widely targeted analyses were performed by GC and LC MS couplings. GC-MS/MS was performed on a 7890A gas chromatography (Agilent Technologies) coupled to a QQQ (triple quadrupole) 7000C (Agilent Technologies). Bile acids, polyamines and short chain-fatty acids analyses were performed by LC-MS/MS with a 1290 UHPLC (Ultra-High Performance Liquid Chromatography) (Agilent Technologies) coupled to a QQQ 6470 (Agilent Technologies). Widely pseudo-targeted analysis by UHPLC-HRMS (Ultra-High Performance Liquid Chromatography – High Resolution Mass Spectrometer) was performed on a Dionex U3000/Orbitrap q-Exactive (Thermo) coupling.

All targeted treated data were merged then cleaned by mean of a dedicated R package (@Github/Kroemerlab/GRMeta). Complete codes are available in the repository https://github.com/kroemerlab. R was used to perform bioinformatic analyses. Differentially expressed metabolites were identified using linear models (Limma), and P-values adjusted for multiple comparisons by applying the Benjamini-Hochberg correction. Differences were considered significant when P < 0.05 and FDR Q < 0.25. Heatmaps and volcano plots were generated using the heatmap3 and EnhancedVolcano packages, respectively. Glimma was used for interactive visualizations. Functional metabolite annotation was performed using Metaboanalyst.

13C labeling and analysis
Sample preparation for labeling analysis: Murine tissues (around 30mg) were weighted and transferred to 2mL-homogenizer tubes with ceramic beads (Precellys, Bertin Technologies), containing 1mL of ice-cold extraction mixture (metOH/water, 9/1, −20°C). The samples were homogenized in Precellys 24 tissue homogenizer (3 cycles of 20s/5000rpm), followed by centrifugation (15min at 10000 xg, 4°C). Murine plasma (25µL) was mixed at 2500rpm during 5min with 500µL of ice-cold extraction mixture (metOH/water, 9/1, −20°C) and centrifuged (15min at 10000 xg, 4°C). Supernatants were split as previously described56.

Labeling experiment by targeted analysis of glycolysis pathway by ion pairing ultra-high performance liquid chromatography (UHPLC) coupled to a Triple Quadrupole (QQQ) mass spectrometer
Targeted analysis is performed on an RRLC 1290 system (Agilent Technologies) coupled to a Triple Quadrupole 6470 (Agilent Technologies) equipped with an electrospray source operating in negative mode. The gas temperature is set to 325°C with a gas flow of 10 L/min. The capillary voltage is set to 4.5 kV. Ten μL of sample are injected on a Poroshell 120 phenyl-hexyl (100mm×2.1mm particle size 2.7µm) column from Agilent Technologies, protected by a SB-C18 (5mm×2.1mm particle size 1.8μm) guard column and heated at 40°C by a Pelletier element. The gradient mobile phase consists of 10mM tributylamine (TBA) and 10mM acetic acid (AA) dissolved in H2O (phase A) or in MeOH (phase B). The flow rate is set to 0.4mL/min, and a gradient is established as follows: initial condition is 98% phase A and 2% phase B, maintained for half a minute, then eluted using a gradient from 2% to 70% B over 5min. The column is washed using 95% B for 2min and equilibrated using 2% mobile phase B for 2min. The MRM method is adapted here to track polyamines but also its isotopes. Peak detection and integration of the isotopomers were performed using the Agilent MassHunter quantitative software.

Labeling experiment by targeted analysis of by gas chromatography (GC) coupled to a Triple Quadrupole (QQQ) mass spectrometer
Targeted analysis methods are described in Izzo et al. Cell Cycle. 2017. Briefly, derivatization of GC aliquot was carried out with 50µL of O-ethylhydroxylamine hydrochloride stored at room temperature in the dark for 16h followed by silylation with 80µL of N-tert-butyldimethylsilyl-N-methyltrifluoroacetamid (MSTBFA) at 40°C for 30min.

The GC-MS/MS method was performed on a 7890B gas chromatography (Agilent Technologies, Waldbronn, Germany) coupled to a triple quadrupole 7000C (Agilent Technologies, Waldbronn, Germany) equipped with an electron impact source (EI) operating in positive mode.

The scan mode used was the MRM for biological samples, with the Q1 corresponding to the maximally derivatised molecule and with Q3 corresponding to a typical fragment of the silyl group (73 or 147). Peak detection and integration of the isotopomers were performed using the Agilent MassHunter quantitative software (B.07.01).

Labeling experiment by Untargeted analysis of metabolites by ultra-high performance liquid chromatography (UHPLC) coupled to a quadrupole-time of flight (QTOF) mass spectrometer
Profiling of intracellular metabolites was performed on a Liquid Chromatography (LC) 1260 system (Agilent Technologies, Waldbronn, Germany) coupled to a QTOF 6520 (Agilent Technologies) equipped with an electrospray source operating in positive mode and full scan mode from 50 to 1000 m/z. The gas temperature was set to 350°C with a gas flow of 12 L/min. The capillary voltage was set to 3.5kV, the fragmentor to 175V, and the skimmer to 65V. Two reference masses were used to maintain the mass accuracy during analysis: m/z 121.050873 and m/z 922.009798 in positive mode and m/z 112.985587. 10μL of sample were injected on a SB-Aq column (100mm×2.1mm particle size 1.8μm) from Agilent Technologies, protected by a guard column XDB-C18 (5mm×2.1mm particle size 1.8μm) and heated at 40°C by a pelletier oven.

The gradient mobile phase consisted of water with 0.2% of acetic acid (A) and acetonitrile (B). The flow rate was set to 0.3mL/min. The initial condition was 98% phase A and 2% phase B. Molecules were then eluted using a gradient from 2% to 95% phase B in 7min. The column was washed using 95% mobile phase B for 3min and equilibrated using 2% mobile phase B for 3min. The autosampler was kept at 4°C.

Peak detection and integration of the isotopomers were performed using the Agilent MassHunter quantitative software (B.07.01), extracting chromatograms of ion signal from the full scan data.

13C-Palmitic acid analysis
Palmitic acid was measured in liver samples by liquid chromatography coupled to mass spectrometry (LC-MS). Briefly, liver samples (ca. 100mg) were homogenized with 1.2mL of acetonitrile with 0.1% formic acid using an Ultra-turrax disperser (IKA-Werke GmbH, Germany) at 12000 min-1 for 10–15s. The homogenate was then centrifuged at 14500 rpm and 4°C for 5min, and 2µL of the supernatant were directly injected into the LC-MS system.

LC-MS analysis was performed on an Acquity I-Class UPLC system (Waters Associates) for the chromatographic separation coupled to a triple quadrupole (Xevo TQ-S micro) mass spectrometer provided with an orthogonal Z-spray-electrospray interface (ESI) (Waters Associates, Milford, MA, USA) working in negative ion mode. Chromatographic separation was carried out on an Acquity BEH C18 column (Waters, 2.1×100mm, 1.7µm). The isotopic distribution of palmitic acid was determined by a Selected Ion Monitoring (SIM) method by acquiring the m/z of the corresponding [M-H]- species for palmitic acid (m/z 255) and its isotopically shifted ions (m/z 256, 257, 258, 259, 260, 261, 262).

Data were acquired and processed using MassLynx 4.2 software and TargetLynx application manager (Waters Corp, Manchester, UK).

To accurately assess de novo lipogenesis from exogenous ¹³C-glucose, we focused our analysis on the heavier isotopologues of palmitic acid (M+4, m/z 259). This isotopologue more reliably reflects glucose-derived fatty acid synthesis, as their presence is not significantly influenced by the natural isotopic abundance of palmitate or by pre-existing unlabeled lipid pools. In contrast, M+2 (m/z 257) may include a substantial endogenous contribution due to the natural presence of ¹³C and ¹8O, which could confound interpretation. Therefore, M+4 was selected as the most specific indicator of newly synthesized palmitate.

Proteomic analysis
In-solution trypsin digestion: 200µL of solution were mixed with 100µL of 25mM ammonium bicarbonate buffer pH 8.5, reduced by adding 30µL of 10mM DTT and incubated at 56°C for 20min. Then, the proteins were alkylated by adding 30µL of 20mM IAA and incubating 30min at RT in the dark. Finally, digestion was performed by adding 1µL of Trypsin Proteomics Grade (Sigma) during at least 3h to overnight at 37°C. Reaction was stopped with 10µL of 0.1% formic acid and filtered through 0.2µm (hydrophilic PTFE) to 2mL dark glass vial. Finally, samples were dried using a nitrogen current with the vial in a heating block at 35°C. The dry samples were resuspended in 20µL of buffer A, consisting in water/acetonitrile/formic acid (94.9:5:0.1). HPLC-MS/MS analysis: The separation and analysis of the samples were performed with a UHPLC/MS system consisting of an Agilent 1290 Infinity II Series HPLC (Agilent Technologies, Santa Clara, CA, USA) equipped with an automated multisampler module and a High Speed Binary Pump, and coupled to an Agilent 6550 Q-TOF Mass Spectrometer (Agilent Technologies, Santa Clara, CA, USA) using an Agilent Jet Stream Dual electrospray (AJS-Dual ESI) interface. The control of the HPLC and Q-TOF were made by the MassHunter Workstation Data Acquisition software (Agilent Technologies, Rev. B.06.01). Sample was injected onto an Agilent Advance Bio Peptide Mapping HPLC column (2.7µm, 150×2.1mm, Agilent technologies), thermostatted at 55°C, at a flow rate of 0.4mL/min. This column is suitable for peptide separation and analysis. The gradient program started with 2% of B (buffer B: water/acetonitrile/formic acid, 10:89.9:0.1) that stayed 5min in isocratic mode, and then it increased linearly up to 45% B in 40min, and then it increased up to 95% B in 15min and it remained constant for 5min. After this 70min of run, 5min of post-time followed using the initial condition for the conditioning of the column for the next run. The mass spectrometer was operated in the positive mode. The nebulizer gas pressure was set to 35psi, whereas the drying gas flow was set to 10 L/min at a temperature of 250°C, and the sheath gas flow was set to 12 L/min at a temperature of 300°C. The capillary spray, fragmentor and octopole RF Vpp voltages were 3500V, 340V and 750V, respectively. Profile data were acquired for both MS and MS/MS scans in extended dynamic range mode. MS and MS/MS mass range was 50–1700 m/z and scan rates were 8 spectra/sec for MS and 3 spectra/sec for MS/MS. Auto MS/MS mode was used with precursor selection by abundance and a maximum of 20 precursors selected per cycle. A ramped collision energy was used with a slope of 3.6 and an offset of −4.8. The same ion was rejected after two consecutive scans. Data processing and analysis was performed Spectrum Mill MS Proteomics Workbench (Rev B.04.01, Agilent Technologies, Santa Clara, CA, USA). Briefly, raw data were extracted under default conditions as follows: non fixed or variable modifications were selected; [MH]+ 50–10000 m/z; maximum precursor charge +5; retention time and m/z tolerance ±60s; minimum signal-to-noise MS (S/N) 25; finding 12C signals. The MS/MS search against the appropriate and updated protein database (in this case: Uniprot/Mouse) was performed with the following criteria: non fixed modifications were selected and with the following selected as variable modifications: carbamidomethylated cysteines, phosphorylated Serine (S), phosphorylated Threonine (T), and phosphorylated Tyrosine (Y), was selected and tryptic digestion with 5 maximum missed cleavages; ESI-Q-TOF instrument; minimum matched peak intensity 50%; maximum ambiguous precursor charge +5; monoisotopic masses; peptide precursor mass tolerance 20 ppm; production mass tolerance 50 ppm; and calculation of reversed database scores. Validation of peptide and protein data was performed using the auto-validational algorithm for validation of peptide and protein data. The auto-validation strategy used was auto-threshold, in which the peptide score is automatically optimized for a target % false discovery rate (FDR) (1.2%). Protein polishing validation was then performed to increase the sequence coverage of validated results with the restriction of a new maximum target protein FDR (0%). The exact FASTA file (UniProtKB/Swiss-Prot Mus musculus reference proteome (17,170 reviewed entries; file UniProt.mouse.fasta; MD5=6015ca1e9465cb64a8be4451dc581ef8) supplemented with a database of common contaminants (cRAP) and its manifest are deposited with the dataset (MassIVE MSV000099335).

Enrichment study of biological pathways. Over Representation Analysis (ORA) using the Gene Ontology (Biological Processes)58,59 or the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases60–62. We accounted for multiple testing using the Benjamini-Hochberg method, with FDR < 0.05. All analyses were performed using R Statistical Software (v4.4.1; R Core Team 2021) with the Bioconductor package “clusterProfiler”63.

Transcriptomic analysis
mRNA-seq. Total RNA is treated with beads poliT, which binds with poliA tail present in eukaryotic mRNAs. After this, it is recovered only mRNAs with beads poliT and beads poliT are removed in order to get only mRNAs. The library step is done using these mRNAs with the typical steps of a library construction using commercial kit called Truseq stranded mRNA Library from Illumina. Sequencing step was done with a 150 PE read length and with a minimum of 40M reads/sample in an Illumina sequencer NovaSeq6000 Bioinformatics: The bioinformatics analysis was performed by Dreamgenics S.L. First, raw FASTQ files were evaluated using FastQC [https://www.bioinformatics.babraham.ac.uk/projects/fastqc/] quality checks, and sequence trimming was performed to remove bases, adapters, and other low-quality sequences with fastp [https://github.com/OpenGene/fastp] software. Next, pseudo-alignment of the sequences against the reference transcriptome for Mus musculus GRCm39 (Gencode: release M32) [https://www.gencodegenes.org/mouse/release_M32.html] and direct quantification of transcripts were carried out using Salmon (v1.10.0) [https://combine-lab.github.io/salmon/]. For differential expression analysis between conditions, the DESeq2 [https://bioconductor.org/packages/release/bioc/html/DESeq2.html] algorithm was used; said analysis was carried out considering the adjusted p-value, using the Benjamini-Hochberg method for adjusting the P-value (padj). Genes with an adjusted P-value less than 0.05 and a log2 Fold Change greater than 1 or less than −1 were considered differentially expressed.

Analyses of the mice gut microbiota
The total DNA per sample was extracted from 200mg of feces using the QIAamp Power Fecal Pro DNA Kit (Qiagen). Illumina libraries of the V3-V4 region of the 16S rRNA gene were prepared following the manufacturer’s instructions. High-throughput sequencing was performed with a MiSeq Illumina sequencer (2×300bp) by the Translational Genomics (NGS) Unit of the Ramón y Cajal Hospital https://www.irycis.org/en/services/11/translational-genomics-ngs. The Quantitative Insights into Microbial Ecology (QIIME2) pipeline (version qiime2-2020.8) was used to perform the quality filtering, discard chimeric sequences, merge the paired-end reads and estimate the Amplicon Single Variants (ASVs)64. The ASV calculation was based on the DADA2 method implemented in QIIME2 https://qiime2.org/. The Greengenes database65,66 was used for the taxonomic assignment, and the analyses were performed at the genus level. Read clusters that not reaching the genus level were assigned to the last well-identified taxonomic assignation. The alpha-diversity metrics Shannon Index (diversity) and Chao1 (richness) were calculated with the “microbiome” R package “https://github.com/microbiome/microbiome”. To statistically compare the metric distribution between groups, we used the Wilcoxon signed-rank test with Benjamini-Hochberg correction to adjust for multiple comparisons implemented in the R core. The composition patterns between samples were explored with the non-metric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarity. We estimated the significance of the differences between groups with the Permutational multivariate analysis of variance (PERMANOVA) in the R package Vegan: https://github.com/vegandevs/vegan. To identify the taxa associated with the experimental groups, we used the LefSe method (R package microbial) https://github.com/guokai8/microbial67.

Statistical & reproducibility
Data are reported as the mean±SEM, as specified. The number of independent data points (n, individual mice values or number of independent experiments), P-values and statistical tests used are indicated in the figures and legends of the corresponding figures. Two-group comparisons used unpaired, two-sided Student’s t tests (or Wilcoxon tests for non-normal microbiota diversity metrics). Multi-group designs used one-way ANOVA with Tukey correction; mixed designs (age × genotype) used two-way mixed-effects models with Sidak correction. Correlations used two-sided Pearson’s r. Omics-wide analyses (metabolome, transcriptome, proteome) and microbiota differential taxa used multiple-testing control (Benjamini–Hochberg FDR; LEfSe where indicated). Beta-diversity differences were tested by PERMANOVA. Statistical significance was defined as P < 0.05 and exact P-values, test names, tailing (two-sided), effect sizes and n are reported in figures and legends. We did not perform formal a priori power calculations. Group sizes were guided by pilot data and literature while balancing statistical power with the 3Rs. Primary in vivo endpoints targeted effects of ~20–30% (SD ~10–15%), for which n ≈ 8 per group gives ~80% power at α = 0.05. Sample sizes by modality were: histology and immunoblotting (n=5–6/group; large effects, blinded scoring, tissue-processing throughput); metabolomics (n=8/group; a predefined inclusion window restricted analysis to 8 mice per group whose body weight and blood glucose were within the target range to isolate the effects of obesity genotype); transcriptomics (n=7–8/group; instrument time/cost); proteomics (n=5/group; instrument time/cost); microbiota (n=5–6/group; cage considered the experimental unit when appropriate); 13C-lipid screening (n=4–5/group; one mouse died before sacrifice for unknown reasons and was not analyzed); leupeptin-flow controls (n=3/group; mechanistic confirmation, limited cohort); primary hepatocytes (n=3 independent isolations). In vitro assays were repeated across n=3 independent experiments; ≥50 images/condition were quantified with fixed, pre-set parameters.

Researchers were not blinded during animal handling or sample collection, as genotype and diet produced obvious phenotypes, and microbiota analyses required group-specific housing and labeling. To limit bias, endpoints and analyses settings were predefined and based on objective instrument readings. Mouse tissue analyses were performed blindly and were analyzed after the corresponding parameters (hepatic steatosis and adipocyte size) had been determined. The Omics datasets were also processed using coded sample IDs, and the group labels were revealed at the time of analysis.

No post-hoc data exclusions were made, apart from: (i) applying the a priori predefined inclusion window for metabolomics (±10% around cohort mean body weight and glycemia) to isolate genotype effects from obesity; and (ii) one animal that died immediately before sampling, which was therefore not analyzed.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The present study aims at linking extracellular levels of ACBP to the development of ciliopathic obesity. The authors use mice carrying a mutation in the ALMS1 gene, a model of Alström syndrome, which clinically manifests in metabolic problems, including insulin resistance, diabetes, obesity, and liver abnormalities, and non-metabolic symptoms including sensorineural hearing loss, retinal degeneration and cardiomyopathy. They take a systems-wide biology approach using LC/MS based metabolomics, proteomics and sequencing to identify putative links between metabolism, autophagy and microbiome and argues that inactivation of ACBP in the circulation can prevent the metabolic manifestations of Alms1-/- mice. Unfortunately, the study relies on using neutralizing antibodies against ACBP and not genetically ablated ACBP mice. The study is interesting, however there are major issues that prevent the manuscript from being acceptable for publication in Nature Communication.\nMajor issues:\n1. The authors initially use metabolomics to show that functional loss of ALMS1 affects the metabolome in liver, adipose and plasma. Yet this is an interesting phenotype of Alms1-/- mice, this part of the study seems to be disconnected from the parts revolving around ACBP. The authors later argue that neutralizing ACBP using antibodies can prevent the development of the metabolic manifestations of AöS in Alms1-/- mice. Thus, the authors need to show how neutralizing ACBP in Alms1-/- mice can restore these metabolic manifestations using metabolomics. To this end, the authors need to genetically target ACBP in Alms1-/- mice to show that this also restore the metabolic manifestations.\n2. An overall shortage of the entire study is the lack of using ACBP knock out mice. The authors solely rely on using neutralizing antibodies in an effort to link ACBP levels to the metabolic manifestations of Alms1 mice. The authors must experimentally use ACBP knock out animals to strengthen the point of the study.\n3. All WBs show ACBP as a 14 kDA, yet ACBP is normally considered as a 10 kDa protein of 86 amino acids. The authors must clearly indicate which isoform of ACBP they are targeting by siRNA, antibodies etc. To this end, as the authors use siRNA to knock down ACBP in cell lines (HepG2), how does siRNA affect expression levels of other ACBP isoforms?\n4. Figure 4; the authors argue that there is an effect on lipogenesis, yet they only provide expression levels of selected genes involved in lipogenesis. They must experimentally show that there is an effect on de novo fatty acid- and lipid synthesis using e.g. tracer analyses.\n5. Figure 7 summarizes the findings and along with the text, the authors indicate that ACBP neutralizing antibodies also will target intracellular ACBP. What is the evidence for antibodies reaching intracellular ACBP.? Again, if the neutralizing antibodies have an effect on ACBP and thus on lipogenesis and metabolic manifestations, the authors must use ACBP KO animals to confirm their findings. Can the observed phenotypes be ascribed to targeting of intracellular ACBP and not extracellular ACBP per se?\n6. For all WBs, it is unclear how many independent samples that are loaded? Is a sample in one lane a pool of several samples from replicate experiments? or does N equal one? At least three independent replicates for one treatment must be shown.\n7. There is no info on which antibodies that have been used. The authors must provide specific catalog numbers/info to inform which specific protein the antibodies have been raised against.\n8. The authors solely discuss ACBP as an extracellular protein. Yet, it was first identified as an intracellular protein involved in termination of fatty acid synthesis. The authors must elaborate the role of ACBP in lipid metabolism throughout the manuscript, both its intracellular role as well as its extracellular role.\nMinor:\n1. Suppl. table 5 is missing", "reviewer_2": "This is an interesting study that seeks to understand the underlying mechanism by which AoS results in weight gain and metabolic syndrome. It utilizes unbiased profiling methods to look at metabolomic and transcriptomic changes, as well targeted analysis and direct perturbations of cell culture systems and mice (in this case, anti-ACBP treatment), to advance the concept that altered autophagic flux is an initiating event that affect metabolic balance through ACBP secretion. There are many interesting aspects to the story. The study however suffers in many places from lack of appropriate controls to properly deconvolute the effects of obesity per se, from genotype and/or treatment. This is a major deficiency. Secondly, the metabolic characterization of the mice is also too superficial to conclude that food intake is the only or dominant driver of obesity as implied. Lastly, there are aspects of rigor of study design and interpretation that need attention.\nSpecific comments are below:\n1) The study needs to explicitly state the gender of the animals used in each experiment. Given the significance of gender on body weight, the data is hard to interpret without this information.\n2) Animal breeding scheme and housing is also very important to the entire study and should be clearly stated. Mice should be littermates, and if microbiome as a factor is of interest, the animals should be segregated by genotype after weaning. Complete segregation of the colonies causes genetic and microbiome drifts that cannot be properly controlled and this should be avoided. If microbiome changes want to be avoided, cohousing of mutant and control animals into adulthood should be used. For this story, are the control animals littermates of the mutant mice? Where they co-housed with mutant mice or segregated at weaning, or derived from 2 parallel colonies in the same vivarium?\n3) Without a diet induced obesity control group, the metabolomic disturbance in 20 wk old AoS mice is impossible to interpret (Fig 1, Fig S1). It is unclear what may be due to obesity alone and what may be the result of the AoS genetic alteration. This shortcoming is present also in many subsequent figures.\nThe pre-obese mice studied are less problematic, at least when they are matched by weight, but does not completely overcome the problems noted for studies of older mice as important metabolic changes seen after week 8 of life that are due to AoS may have been missed.\nWhenever a key conclusion is being drawn, a diet induced obese group, weight matched to the mutant mouse, needs to be included. Alternatively, pair-feeding the mutant mice to match a control group by weight is another strategy.\n4) This point of weight vs genotype vs treatment is also a problem for the interpretation of Fig 6, a key figure in the paper. AoS mutant and isotype treated mice are obese while WT isotype treated mice are lean (top comparison in panel 6A). AoS mutant and anti-ACBP treated mice are lean, where are AoS mutant and isotype treated mice are obese, exactly the reciprocal weight relationship (bottom comparison in panel 6A). The observed differences seem to correlate with weight rather than genotype or treatment. It should be noted that obesity will also drive dysbiosis, so again, results from these comparisons cannot deconvolute the contributions of weight alone, from genotype or treatment group.\n5) Anti-ACPB treatment did not reverse obesity in older mice, even though it did reduce food intake considerably. The interpretation of the effect of anti-ACBP treatment is incomplete without full metabolic phenotyping of the mice. Weight matched, pre-obese mice (or pair fed mice that are weight matched), should be placed in metabolic cages to measure all the key determinants of energy balance, not just food intake, but also thermogenesis, movement, etc. Stool calorimetry should be included as well to assess caloric losses (or efficiency of caloric extraction from the diet). Beside studying mice by genotype, this experiment should be done in isotype and anti-ACBP treated mice, so that we can conclude convincingly what drives the effect of the treatment (or its failure in older mice).\n6) The manuscript should avoid making any claims on non-statistically significant nominal differences. Rigorously speaking, the probability that those values are different is low, and should not be interpreted as potential differences between the groups (eg, Acc1 in Fig S5). Similarly, it is problematic to compare gene expression profiles in different groups that were not studied simultaneously (like when Fig 3B and S5H are compared). This should be avoided.", "reviewer_3": "A multi-omics study by Corral Nieto, Y. and Fernández Pereira, A.G. et al. showed that presymptomatic AöS mice had early liver dyslipidemia, impaired autophagy, and hepatic ACBP accumulation. The above pathological features lead to changes in the adipogenic response and bacterial microbiota in adult obese AöS mice. Importantly, the researchers found that reducing excess available ACBP via a neutralizing monoclonal antibody prevented weight gain and metabolic defects in Alms1-/- mice in an autophagy-independent manner. These findings suggest that obesity associated with ciliopathies (particularly AöS) can be treated by ACBP neutralization. However, how Alms1-/- induces autophagy and the mechanisms underlying the promotive role of autophagy in ACBP remain unclear. Is autophagy the most critical regulator for increased ACBP? The following concerns still need to be addressed.\nI have several comments on this work:\n1. Figure 3C, the representative images of GAPDH also show a similar trend as SQSTM1 and LC3. Additionally, the band corresponding to LC3Ⅱ is not visible. Please replace Western blotting images with more representative ones.\n2. The author used different numbers of mice for analysis in different experiments of the same Figure. What was the basis for the excluded mice?\n3. Figure 3A, ACC1 and ACBP1 groups seem to be statistically significant.\n4. “Moreover, mice exhibit no changes in weight loss under caloric restriction conditions (Figure 3H)”. However, the weight changes shown in the chart are statistically significant.\n5. Figure 4C, the knockout efficiency of ALMS1 is missing.\n6. Similarly, the trend of the autophagy-related protein expression tested in the Western blot in Figure 4J is not representative.\n7. The WT+Unt group in Figure 4B, D, and K should exhibit variance. In addition, Figures 4B, and D lack statistical analysis. What does Unt mean?\n8. Figure 4D, the authors should merge the two statistical graphs into one. The current analysis cannot compare the changes between the KO+BAFA1 and KO groups, the same as Figure 2B.\n9. Figure 4K, please clearly indicate which two groups undertook the comparative analysis.\n10. Missing statistics for the siACBP1+KD2 group in Figure 4I.\n11. Is the statistical method of Figure 2 F-I correct? The author used one-way ANOVA analysis. However, there are two variables. Two-way ANOVA is more appropriate\n12. In Figure 5I, the variance bars and points in the panel deviate from the column chart.\n13. Authors should unify how statistics are written, ns or precise p-values.\n14. How was the UNR control group treated? Negative controls should be applied for siACBP and antiACBP.\n15. In fact, the conclusion that ‘autophagy blockers did not further increase protein expression in knockout mice’ is only supported by indirect evidence. Is there a more direct way to prove it?\n16. In Figure 5, the authors conclude that 20 weeks does not have a protective effect, but 6 weeks does. The statement is not correct since it is unable to diagnose the disease at 6 weeks."}, "author_response": "Manuscript number: NCOMMS-23-62105\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-\nomics network analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: Oct 1 2024\nPoint-by-point reply to Reviewer No. 1. \nGeneral critique by reviewer No. 1: The present study aims at linking extracellular levels of\nACBP to the development of ciliopathic obesity. The authors use mice carrying a mutation in\nthe ALMS1 gene, a model of Alström syndrome, which clinically manifests in metabolic\nproblems, including insulin resistance, diabetes, obesity, and liver abnormalities, and non-\nmetabolic symptoms including sensorineural hearing loss, retinal degeneration and\ncardiomyopathy. They take a systems-wide biology approach using LC/MS based\nmetabolomics, proteomics and sequencing to identify putative links between metabolism,\nautophagy and microbiome and argues that inactivation of ACBP in the circulation can prevent\nthe metabolic manifestations of Alms1-/- mice. Unfortunately, the study relies on using\nneutralizing antibodies against ACBP and not genetically ablated ACBP mice. The study is\ninteresting, however there are major issues that prevent the manuscript from being acceptable\nfor publication in Nature Communication.\nOur response: We addressed the suggestions by this reviewer, as indicated below. We\nthank the reviewer for their positive appraisal of our paper and for their valuable\ncontribution to our work. This effort has undoubtedly improved the manuscript\nsignificantly.\nRemark No. 1 by reviewer No. 1: The authors initially use metabolomics to show that\nfunctional loss of ALMS1 affects the metabolome in liver, adipose and plasma. Yet this is an\ninteresting phenotype of Alms1-/- mice, this part of the study seems to be disconnected from\nthe parts revolving around ACBP. The authors later argue that neutralizing ACBP using\nantibodies can prevent the development of the metabolic manifestations of AöS in Alms1-/-\nmice. Thus, the authors need to show how neutralizing ACBP in Alms1-/- mice can restore\nthese metabolic manifestations using metabolomics. To this end, the authors need to genetically\ntarget ACBP in Alms1-/- mice to show that this also restore the metabolic manifestations.\nOur response: We appreciate the reviewer's comments. To address this issue, we have\nperformed an additional metabolomic analysis of the livers from mice treated with anti-\nACBP mAb antibody. As suggested by the reviewer, this analysis allows us to confirm that\nneutralization of ACBP with antibodies prevents the metabolic alterations observed in\nAlms1-/- mice. These transcriptomic data complement our results obtained by\nmetabolomics and proteomics. They are detailed in the new Figure 5. All these omics\ntechnologies convergently demonstrate the disease-reversing effects of ACBP\nneutralization on Alms1-/- mice.\nACBP knock out mice. The authors solely rely on using neutralizing antibodies in an effort to\nlink ACBP levels to the metabolic manifestations of Alms1 mice. The authors must\nexperimentally use ACBP knock out animals to strengthen the point of the study.\nOur response: We appreciate the reviewer’s suggestion. Unfortunately, obtaining the\nrequired genotype (and controls) and completing the experiments would take more than\n12 months. Constitutive Acbp knockout (genotype: Acbp-/-) leads to a postnatally lethal\nphenotype (due to the requirement of Acbp for the fetal and perinatal development of the\nskin barrier), meaning that the Acbp knockout has to be performed in a conditional\nfashion, in adult mice, as we described in our 2019 paper published in Cell Metabolism\n(PMID: 31422903). For this reason, we would have to perform multiple backcrosses to\nobtain mice that are Alms1-/-, Acbpflox/flox and bear UBC-cre/ERT2, a transgene that codes\nfor a tamoxifen-inducible recombinase allowing to inactivate the floxed Acbp gene. For\nthis reason, it would be impossible to obtain the desired genotype mice (and controls) in\nsufficient numbers and to perform the experiments within less than 12-15 months.\nInstead of performing these experiments, we isolated primary hepatocytes from WT and\nAlms1-/- mice and studied their phenotype after inhibiting ACBP by: (i) the addition of the\nsame anti-ACBP mAb used in vivo (mAb 7A) and (ii) silencing of Acbp gene. These results\ndemonstrated that genetic inhibition of Acbp has similar effects at the neutralization of\nACBP by means of the antibody, strongly suggesting that the antibody acts on target.\nFurthermore, we explicitly mentioned the literature showing that the neutralization of\nACBP by monoclonal antibody 7A and the conditional knockout of ACBP in adult mice\nyields similar phenotypes with respect to a reduction in food intake, a switch from lipo-\nanabolism to lipo-catabolism, anti-obesity and anti-diabetic effects, as well as the\nprotection of various organs against cytotoxic insults (PMID: 31422903, PMID: 36191214,\nPMID: 36198092). Again, these published results argue in favor of the notion that the\neffects of mAb 7A against ACBP that we use in our study are indeed mediated by on-\ntarget effects (because genetic inactivation of ACBP yields a similar phenotype as mAb).\nRemark No. 3 by reviewer No. 1: All WBs show ACBP as a 14 kDa, yet ACBP is normally\nconsidered as a 10 kDa protein of 86 amino acids. The authors must clearly indicate which\nisoform of ACBP they are targeting by siRNA, antibodies etc. To this end, as the authors use\nsiRNA to knock down ACBP in cell lines (HepG2), how does siRNA affect expression levels\nof other ACBP isoforms?\nOur response: We appreciate this comment from the reviewer since\nthere is indeed a mistake. The band observed is less than 14 KDa as\ncan be checked in the datasheet of the antibodies used (ab231910 and\nab232760) and as we have shown in previous papers (PMIDs:\n31422903, 35436993). Furthermore, we have verified that the intensity\nof this band decreases after the use of specific ACBP siRNAs (New\nFigure 4J). The electrophoretic mobility of this band corresponds to\nthat of a protein of 10 kDa, and it exhibit the same apparent molecular\nweight as purified ACBP recombinant protein (see immunoblot at the\nleft). Accordingly, our previous bioinformatic analyses reveals that\none single isoform of ACBP (ACBP1) is the dominant one (~90% of\nall ACBP transcripts, with the sole exception of the testis, where it is\n~70%) in mouse and human organs including the liver (PMID:\n34308254).\nlipogenesis, yet they only provide expression levels of selected genes involved in lipogenesis.\nThey must experimentally show that there is an effect on de novo fatty acid- and lipid synthesis\nusing e.g. tracer analyses.\nOur response: We analyzed the full metabolome and transcriptome of these mice after\nantibody treatment, hence providing more information about lipid synthesis.\nFurthermore, as shown in Figure S5E-F, both proteomic and transcriptomic analyses\nreveal that lipogenesis pathways are upregulated in the mutant mouse. Numerous genes\ninvolved in increased lipogenesis or decreased lipolysis in the KO mouse are normalized\nby treatment with anti-ACBP mAb (Figure 5F-H). Beyond this, we performed a glucose\ntolerance test (GTT) (new figure 4C), showing that the treatment with anti-ACBP mAb\nnormalized the altered values observed in Alms1-/- mouse.\nRemark No. 5 by reviewer No. 1: Figure 7 summarizes the findings and along with the text,\nthe authors indicate that ACBP neutralizing antibodies also will target intracellular ACBP.\nWhat is the evidence for antibodies reaching intracellular ACBP? Again, if the neutralizing\nantibodies have an effect on ACBP and thus on lipogenesis and metabolic manifestations, the\nauthors must use ACBP KO animals to confirm their findings. Can the observed phenotypes be\nascribed to targeting of intracellular ACBP and not extracellular ACBP per se?\nOur response: We have no evidence that the anti-ACBP mAb would reach the\nintracellular space. However, we have shown in the past that extracellular ACBP is\nengaged in a feedforward loop leading to an increase in the expression of intracellular\nACBI due to a cascade of events that involve activation of GABA receptor 1 (to which\nACBP binds via an interaction with the gamma-2 subunit), the transcription factor\nPPAR-gamma, and the transactivation of the DBI gene, which codes for ACBP. For this\nreason, inhibition of extracellular ACBP causes a diminution of intracellular ACBP levels\nPMID: 35436993, PMID: 36191214.\nAs we have mentioned above, we cannot address the experiments with the double KO\nmouse, but we addressed this point by isolating primary hepatocytes from Alms1 WT and\nKO mice and then comparing the effects of ACBP siRNAs (reducing the intracellular\nACBP pool) with those of the anti-ACBP mAb (acting on extracellular ACBP).\nWe have revised the new figure 7, removing the visual representation of the mAb binding\nthe intracellular ACBP, as suggested by the reviewer, to more accurately reflect the\nresults.\nRemark No. 6 by reviewer No. 1: For all WBs, it is unclear how many independent samples\nthat are loaded? Is a sample in one lane a pool of several samples from replicate experiments?\nor does N equal one? At least three independent replicates for one treatment must be shown.\nOur response: All western blot experiments were performed in 3 independent\nexperiments. Each lane represents an independent in vitro experiment or an individual\nmouse. Due to limitations in loading capacity on a single blot, some samples are shown on\nthe same blot, while others are displayed on different blots, each of which includes similar\ncontrols. All the information about the blots used in the paper (including uncropped\nImagen) is included in the excel file \"Info figures BRAVO\".\nThe authors must provide specific catalog numbers/info to inform which specific protein the\nantibodies have been raised against.\nOur response: All information about the antibodies (and primers) used in the work is\nshown in supplementary table 5 (New Supplementary table 9: Information about the\nmaterials used for PCR and immunoblot techniques) in the supplementary tables.\nRemark No. 8 by reviewer No. 1: The authors solely discuss ACBP as an extracellular\nprotein. Yet, it was first identified as an intracellular protein involved in termination of fatty\nacid synthesis. The authors must elaborate the role of ACBP in lipid metabolism throughout\nthe manuscript, both its intracellular role as well as its extracellular role.\nOur response: We explained this point in the revised manuscript, as we mentioned in\nremark No.5.\nRemark No. 9 by reviewer No. 1: Suppl. table 5 is missing\nOur response: The supplementary table 5 is included in the excel file named\n“Supplementary table 9: Information about the materials used for PCR and immunoblot\ntechniques”.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-\nomics network analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: Oct 1 2024\nPoint-by-point reply to Reviewer No. 2.\nGeneral critique by reviewer No. 2: This is an interesting study that seeks to understand the\nunderlying mechanism by which AöS results in weight gain and metabolic syndrome. It utilizes\nunbiased profiling methods to look at metabolomic and transcriptomic changes, as well targeted\nanalysis and direct perturbations of cell culture systems and mice (in this case, anti-ACBP\ntreatment), to advance the concept that altered autophagic flux is an initiating event that affect\nmetabolic balance through ACBP secretion. There are many interesting aspects to the story.\nThe study however suffers in many places from lack of appropriate controls to properly\ndeconvolute the effects of obesity per se, from genotype and/or treatment. This is a major\ndeficiency. Secondly, the metabolic characterization of the mice is also too superficial to\nconclude that food intake is the only or dominant driver of obesity as implied. Lastly, there are\naspects of rigor of study design and interpretation that need attention.\nOur response: We thank the Reviewer for reading our paper and for proposing a series\nof points that we have addressed below.\nRemark No. 1 by reviewer No. 2: The study needs to explicitly state the gender of the animals\nused in each experiment. Given the significance of gender on body weight, the data is hard to\ninterpret without this information.\nOur response: We thank the reviewer for their comment. We specified the sex of the\nanimals in the revised Materials and Methods section for each experiment.\nRemark No. 2 by reviewer No. 2: Animal breeding scheme and housing is also very important\nto the entire study and should be clearly stated. Mice should be littermates, and if microbiome\nas a factor is of interest, the animals should be segregated by genotype after weaning. Complete\nsegregation of the colonies causes genetic and microbiome drifts that cannot be properly\ncontrolled and this should be avoided. If microbiome changes want to be avoided, cohousing\nof mutant and control animals into adulthood should be used. For this story, are the control\nanimals littermates of the mutant mice? Where they co-housed with mutant mice or segregated\nat weaning, or derived from 2 parallel colonies in the same vivarium?\nOur response: We clarified in supplemental annex 1 the different co-housing protocols\nused for the microbiota analysis. Specifically, the co-housing method employed in the\nmicrobiota analysis differed from that used in the other experiments to prevent the\nexchange of microbiota through coprophagy between mice within the same cage. For the\nmicrobiota experiments, samples were collected from cages containing mice under\nidentical experimental conditions. Conversely, for all other experiments, cages contained\nrandomly selected mice to mitigate the potential effects of cage-specific microbial shifts.\nmetabolomic disturbance in 20 week old AöS mice is impossible to interpret (Fig 1, Fig S1). It\nis unclear what may be due to obesity alone and what may be the result of the AöS genetic\nalteration. This shortcoming is present also in many subsequent figures.\nThe pre-obese mice studied are less problematic, at least when they are matched by weight, but\ndoes not completely overcome the problems noted for studies of older mice as important\nmetabolic changes seen after week 8 of life that are due to AoS may have been missed.\nWhenever a key conclusion is being drawn, a diet induced obese group, weight matched to the\nmutant mouse, needs to be included. Alternatively, pair-feeding the mutant mice to match a\ncontrol group by weight is another strategy.\nOur response: Thanks to the reviewer for this valuable point. We have included in the\nnew version the fat-diet obese mouse model (DIO-mice) and compared it with the obesity\nmodel developed by the Alms1-/- mouse (Figure S5A-D). In the new manuscript, the\ncommonalities and differences between DIO and Alms1-/- mice were analyzed. Although\nmany changes are common to both models of obesity, some are specific for Alms1-/- mice.\nRemark No. 4 by reviewer No. 2: This point of weight vs genotype vs treatment is also a\nproblem for the interpretation of Fig 6, a key figure in the paper. AoS mutant and isotype treated\nmice are obese while WT isotype treated mice are lean (top comparison in panel 6A). AoS\nmutant and anti-ACBP treated mice are lean, where are AoS mutant and isotype treated mice\nare obese, exactly the reciprocal weight relationship (bottom comparison in panel 6A). The\nobserved differences seem to correlate with weight rather than genotype or treatment. It should\nbe noted that obesity will also drive dysbiosis, so again, results from these comparisons cannot\ndeconvolute the contributions of weight alone, from genotype or treatment group.\nOur response: The aim of the old Figure 6A (now Figure 5, along with metabolomics and\ntranscriptomics data) was to provide an overview of the omics changes in different groups,\nhighlighting the general capacity of the anti-ACBP treatment in reversing the alterations\nobserved in Alms1-/- mice. While the weight reduction associated with the treatment could\ncontribute to these changes, we have included new metabolomic data with a diet-induced\nobese (DIO) control group. This allows us to observe how the treatment reverses some\nchanges (succinic acid, glucuronic acid, malic acid… etc.) that are exclusively found\nin Alms1-/- (but not in DIO) mice, reinforcing the idea that ACBP neutralization does not\nonly mediate effects associated with weight loss per se, but also specifically influences the\nmetabolism altered by the Alms1 mutation. This point has been discussed in the revised\nmanuscript.\neven though it did reduce food intake considerably. The interpretation of the effect of anti-\nACBP treatment is incomplete without full metabolic phenotyping of the mice. Weight\nmatched, pre-obese mice (or pair fed mice that are weight matched), should be placed in\nmetabolic cages to measure all the key determinants of energy balance, not just food intake, but\nnot just food intake, but also thermogenesis, movement, etc. Stool calorimetry should be included as well to assess caloric losses (or efficiency of caloric extraction from the diet). Beside studying mice by genotype, this experiment should be done in isotype and anti-ACBP treated mice, so that we can conclude convincingly what drives the effect of the treatment (or its failure in older mice).\nOur response: The assessment is very interesting, however this point is unapproachable\nfor adult mice since we need 20-week-old mice and then treat for another 4 additional\nweeks, meaning that we would need about 9 months to complete this point. We have made\na significant effort by analyzing the model by three omics approaches, all of which show\nthe effectiveness of ACBP/DBI neutralization. These comparatively od mice suffer from\nmultiple problems, including blindness, generalized fibrosis, and heart problems. For this\nreason, we think that the treatment with anti-ACBP/DBI effect has no effect because a\npoint-of-no-return has been trespassed.\nRemark No. 6 by reviewer No. 2: The manuscript should avoid making any claims on non-statistically significant nominal differences. Rigorously speaking, the probability that those values are different is low, and should not be interpreted as potential differences between the groups (eg, Acc1 in Fig S5). Similarly, it is problematic to compare gene expression profiles in different groups that were not studied simultaneously (like when Fig 3B and S5H are compared). This should be avoided.\nOur response: We greatly appreciate the reviewer’s comment and have revised the\nsentences related to the results where the statistics were not significant.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-\nomics network analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: Oct 1 2024\nPoint-by-point reply to Reviewer No. 3.\nGeneral critique by reviewer No. 3: A multi-omics study by Corral Nieto, Y. and Fernández\nPereira, A.G. et al. showed that presymptomatic AöS mice had early liver dyslipidemia,\nimpaired autophagy, and hepatic ACBP accumulation. The above pathological features lead to\nchanges in the adipogenic response and bacterial microbiota in adult obese AöS mice.\nImportantly, the researchers found that reducing excess available ACBP via a neutralizing\nmonoclonal antibody prevented weight gain and metabolic defects in Alms1-/- mice in an\nautophagy-independent manner. These findings suggest that obesity associated with\nciliopathies (particularly AöS) can be treated by ACBP neutralization. However, how Alms1-\n/- induces autophagy and the mechanisms underlying the promotive role of autophagy in ACBP\nremain unclear. Is autophagy the most critical regulator for increased ACBP? The following\nconcerns still need to be addressed.\nOur response: We thank the Reviewer for their positive appraisal of our paper. We\naddressed their suggestions as indicated below, in our detailed point-by-point reply.\nRemark No. 1 by reviewer No. 3: Figure 3C, the representative images of GAPDH also show\na similar trend as SQSTM1 and LC3. Additionally, the band corresponding to LC3Ⅱ is not\nvisible. Please replace Western blotting images with more representative ones.\nOur response: The statistics used take into account more samples (n=9 mice) than those\nshown, as you can see in the excel file provided with the uncropped blots. However, as the\nreviewer suggested, we used a better representative image for this figure. Now we show\n(in new Figure 3A) n=3 samples (each from different mice) per condition in the same blot.\nRemark No. 2 by reviewer No. 3: The author used different numbers of mice for analysis in\ndifferent experiments of the same Figure. What was the basis for the excluded mice?\nOur response: The differences within each experiment are based on the use of very\ndifferent techniques and special cohousing conditions, but no mice was eliminated\nbetween experiments. Within the metabolome there are differences due to the absence of\na specific signal in the detection of some metabolite in certain samples (for example n=6\nin old Fig 2I). However, for the metabolomic analysis, 8 mice per group were used in all\nconditions, and all the results obtained are shown. For the measurements after the\ntreatments, all treated mice are also shown. For the microbiota analysis, a different batch\nof mice was analyzed after housing groups of mice in a way that inter-group coprophagy\nwould be avoided. Data from all the mice included in that experiment are shown. For the\nnew transcriptome experiments, adult mice we used n=7 as recommended based on the\nRNA quality control assessments. For the new transcriptomic and metabolomic analyses\nof the liver we used the same mice without removing any sample (WT n=5, KO n=5 and\nKO treated with anti-ACBO mAb n=6). All analyses performed are shown and explicitly\nmentioned in the figures.\nstatistically significant.\nOur response: In our opinion, the statistical analyses are correct since we used a multiple\ncomparison test. We calculated adjusted p values for the intergroup comparisons, which\nwere p=0.13 for Acc1 and p=0.27 for Acbp.\nRemark No. 4 by reviewer No. 3: “Moreover, mice exhibit no changes in weight loss under\ncaloric restriction conditions (Figure 3H)”. However, the weight changes shown in the chart\nare statistically significant.\nOur response: We apologize for this error. We clarified in the revised version that there\nare no differences between both genotypes, which suffer a similar loss after a period of\nstarvation. In both cases, this weight loss is significant. The new sentence reads\n\"Moreover, Alms1-/- and WT mice exhibit efficient weight loss after caloric restriction\n(Figure S3D).”\nRemark No. 5 by reviewer No. 3: Figure 4C, the knockout efficiency of ALMS1 is missing.\nOur response: After CRISPR/Cas9-mediated knockout, the non-functional protein\ncontinues to be detected by Western blot. Therefore, the efficiency of the knockout is\ndemonstrated in Figure 3N (previously Figure S4B-C) by PCR. Additionally, we have\nincluded immunofluorescence images showing GFP-positive cells after the insertion of the\nlinear donor containing the GFP signal. Moreover, we cultured the cells for several weeks\nunder high puromycin pressure, which eliminates the cells that do not express the\ntransfected vector.\nRemark No. 6 by reviewer No. 3: Similarly, the trend of the autophagy-related protein\nexpression tested in the Western blot in Figure 4J is not representative.\nOur response: We have removed the data corresponding to the previous Figure 4J, as we\nhave added new experiments with primary hepatocytes that provide more valuable\ninformation.\nRemarks No. 7 and No. 8 by reviewer No. 3: The WT+Unt group in Figure 4B, D, and K\nshould exhibit variance. In addition, Figures 4B, and D lack statistical analysis. What does Unt\nmean?\nFigure 4D, the authors should merge the two statistical graphs into one. The current analysis\ncannot compare the changes between the KO+BAFA1 and KO groups, the same as Figure 2B.\nOur response: Thanks for your useful comments. We have reanalyzed the data and\nclarified this point. \"Unt\" refers to the untreated condition, and we have now replaced it\nwith \"Vehicle\" for clarity. Previously, we performed the analysis by normalizing the data\nto the untreated controls. However, as per your suggestion, we have redone the analyses,\nincorporating the variance of the controls and we have unified the analyses for conditions\nwith and without bafilomycin to ensure consistency (new Figure 3L and M).\ngroups undertook the comparative analysis.\nMissing statistics for the siACBP1+KD2 group in Figure 4I.\nOur response: We have removed the data corresponding to the previous Figure 4K and I,\nas explained above.\nRemark No. 11 by reviewer No. 3: Is the statistical method of Figure 2 F-I correct? The author\nused one-way ANOVA analysis. However, there are two variables. Two-way ANOVA is more\nappropriate\nOur response: In these panels, we only compared the differences in each of the metabolites\nin WT or mutant mice, so we only analyzed that variable. There is no additional treatment\nnor a kinetic comparison. Therefore, we believe that the one-way ANOVA test is the\ncorrect one for the comparison of 2 groups. However, when adding all the transcriptomic\ndata to the figure, these data were removed and are now only discussed and referenced in\nthe tables that list the metabolites. In the Results, we wrote: “In the plasma, Alms1-/- mice\nexhibited the selective reduction of one single metabolite, N-acetyl-DL-tryptophan (Figure\n2E and Supplementary table 3). In WAT, Alms1-/- mice were characterized by a significant\nreduction in two metabolites, spermine and prostaglandin E1 (Figure 2F and\nSupplementary table 3).”\nRemark No. 12 and No. 13 by reviewer No. 3: In Figure 5I, the variance bars and points in\nthe panel deviate from the column chart.\nAuthors should unify how statistics are written, ns or precise p-values.\nOur response: We fixed these minor errors and unified the nomenclature that we used\nduring the text. The old Figure 5I was removed as it was redundant with the new\ntranscriptomic results, which corroborate the increased expression of Fasn and several\nother genes coding for lipogenic enzymes in the liver of Alms1-/- mice, as well as their\nnormalization by treatment with the antiACBP mAb.\nRemark No. 14 by reviewer No. 3: How was the UNR control group treated? Negative\ncontrols should be applied for siACBP and antiACBP.\nOur response: All conditions were silenced following the same protocol (by transfection\ncells with siRNAs specific for Acbp or Alms1 or a scrambled RNA, SCR). Then, after 48h\nof culture, cells were treated with either anti-ACBP mAb or an isotype control mAb). We\nclarified this protocol in the material and methods for all experiments: “or anti-ACBP\nmAb (or the isotype control mAb) in vitro (1-10 µg/mL; ab232760, Abcam). (...) A\nscrambled siRNA (SCR) was always used as a control, and siRNA-mediated protein\ndownregulation was controlled by immunoblotting or by qPCR.”\nfurther increase protein expression in knockout mice’ is only supported by indirect evidence.\nIs there a more direct way to prove it?\nOur response: This figure demonstrates the results of SQSTM1 accumulation following\nthe use of an autophagic flux inhibitor such as leupeptin. Leupeptin, which inhibits\nautophagic flux, failed to further increase SQSTM1 and ACBP protein levels in Alms1-/-\nmice, supporting. This fact should be considered by considering the accumulation of\nSQSTM1 and ACBP at basal levels in Alms1-/- adult mice (New Figure 3A-C).\nPMID: 22966490. We have rewritten this section to clarify this point: “To confirm the\nblockade of late-stage autophagy flux in 20-week-old Alms1-/- mice (indicated by elevated\nSQSTM1 levels compared to WT mice), we administered the autophagy flux blocker\nleupeptin through injection33. As expected, livers from WT mice with intact autophagy\nflux showed an accumulation of SQSTM1 and ACBP after leupeptin treatment. In\ncontrast, livers from leupeptin-treated Alms1-/- mice displayed no further increase in\nACBP (Figure 3G-H), and SQSTM1 (Figure 3G and S3C), in line with the conclusion of\na late-stage blockade of autophagy flux.”\nRemark No. 16 by reviewer No. 3: In Figure 5, the authors conclude that 20 weeks does not\nhave a protective effect, but 6 weeks does. The statement is not correct since it is unable to\ndiagnose the disease at 6 weeks.\nOur response: We sincerely thank the reviewer for this comment that indeed spots an\nerror. As detailed in the diagram in Figure S5B (new Figure S4B), all measurements for\nthe preventive approach were performed at week 10, four weeks after starting the\ntreatment. This implies that by week 10, the first symptoms of the disease had already\ndeveloped. We have revised the text as follows: “The treatment involved two approaches:\ncurative, applied to 20-week-old mice with an established AöS phenotype (Figure S4A);\nor preventive, applied to 6-week-old mice that are not yet obese (Figure S4B). After 4\nweeks of treatment of 20-week-old Alms1-/- mice, anti-ACBP mAb failed to cause a\nreduction in weight gain compared to the IgG2 isotype-treated control mAb (Figure 4A),\neven though the neutralizing treatment was able to reduce food intake (Figure S4C).\nHowever, in the preventive approach, in 10-week-old Alms1-/- mice treated with anti-\nACBP mAb, a significant prevention of weight gain was observed compared to Alms1-/-\nmice receiving the isotype control (Figure 4B).”\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-\nomics network analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nGeneral comments to the reviewers\nWe would like to express our sincere gratitude to the reviewers for their exceptionally thorough\nand constructive evaluation during both rounds of review. Their insightful comments and\nsuggestions have allowed us to significantly improve the manuscript, which now includes a\ncomplete characterization of Alström syndrome at different disease stages. Over the course of\nthe two rounds of review, we have integrated four comprehensive omics analyses\n(metabolomics, proteomics, transcriptomics, and microbiome), providing a robust\nmultidimensional description of the pathophysiology and its modulation by targeting ACBP.\nMoreover, we present a detailed insight into the role of cilia, autophagy, and ACBP in this\ndisease, and report on the preclinical efficacy of a potential therapeutic strategy. We are\nconvinced that these advances significantly enhance the translational value and potential impact\nof our work.\nPoint-by-point reply to Reviewer No. 1.\nOverall: The manuscript presents a compelling study linking extracellular levels of acyl-CoA\nbinding protein (ACBP) to ciliopathic obesity, particularly Alström syndrome (AöS), through\nmulti-omics approaches. The study is valuable for identifying a novel target in ACBP that could\nmitigate obesity-related complications. However, the reliance on neutralizing antibodies\nwithout using an acbp knockout model significantly weakens the mechanistic insights into the\nrole of ACBP, particularly when claiming its extracellular versus intracellular roles.\nOur response: The reviewer raises a few additional points that we address as indicated below.\nRemark No. 1 by reviewer No. 1: ACBP Neutralization with Antibodies vs. Gene Ablation:\nOne of the core issues is the authors' reliance on neutralizing antibodies to inhibit ACBP.\nAlthough the authors argue that neutralizing ACBP in Alms1-/- mice prevents metabolic\nmanifestations, they fail to demonstrate the same through genetic ablation of acbp. As originally\nwas pointed out, the use of genetically modified acbp knockout mice would have provided a\nmore robust mechanistic understanding. In their rebuttal, the authors state that acbp ablation\nleads to lethality. This is incorrect as several studies have shown that Acbp ablation in mice\nresults in impaired epidermal barrier resulting in among others increased systemic energy\nexpenditure, beiging of white adipose tissue, resistance to diet-induced obesity and improved\nglucose tolerance (doi: 10.1016/j.molmet.2020.101144; doi: 10.1194/jlr.M060780; doi:\n10.1016/j.celrep.2013.11.010; doi: 10.1074/jbc.M110.161109). I acknowledge that creating\nsuch a model will take time due to the complexity of breeding required genotypes. However,\nthis is not an acceptable justification for excluding critical control experiments, as this leaves\nopen questions about how much of the observed phenotype is due to antibody targeting versus\ngene ablation.\nthe knockout Acbp mouse model was lethal. Indeed, a non-lethal full-body ACBP knockout\nmouse has already been generated (Doi: 10.1074/jbc.M110.161109). However, in 2015, we\nformally requested a collaboration to the authors of this model, which was unfortunately\nrejected. Furthermore, it is important to highlight that the available non-lethal ACBP knockout\nmodel shows only a transient metabolic phenotype restricted to a narrow period between\npostnatal days 20 and 30, as described by the original authors (Doi: 10.1074/jbc.M110.161109),\nand the displayed Alström syndrome phenotype occurs from day 60 of life of the diseased\nmouse. In fact, the authors themselves state in the Discussion section that \"future investigations\nusing tissue-specific knock-out models are needed to establish the role of ACBP in TAG and\nCE accumulation in the liver and in SREBP processing\" highlighting the importance of\nconditional approaches, such as the one we implemented. This situation led us to develop our\nown tissue-specific ACBP conditional KO mouse to target the specific extracellular and tissue\nfunctions of ACBP, published in Cell Metabolism in 2019.\nWe fully understand and appreciate the reviewer's interest in a double knockout model (DKO,\nAlms1/Acbp). However, based on our experience generating the Acbp conditional knockout\nmodel, we estimate that generating the double knockout mouse (Alms1 mutant crossed with\nAcbp-floxed mice and a tissue-specific Cre line) would require approximately 18 months, due\nto the complexity of breeding schemes and the need for additional approvals of animal testing\nprotocols according to national regulations. We believe that while this model would\nundoubtedly be valuable, its generation exceeds the feasibility of the study.\nAlthough technically more limited than a complete DKO, our current strategy provides a solid\nmechanistic understanding of the extracellular role of ACBP in the context of Alström\nsyndrome. Moreover, it’s important to note that the effect of the neutralizing antibody used in\nthis study has already been compared to genetic manipulations that inhibit the Acbp system,\nnamely:\n(i) Conditional knockout of Acbp by a ubiquitous tamoxifen-inducible CRE recombinase\nexcising the floxed exon 2 of the Acbp gene in adult mice (PMID: 31422903)\n(ii) Point mutation of the Acbp receptor, GABRG2, in position 72, which if present in\nhomozygosity (genotype: Gabrg2F77I/F77I) abolishes binding of Acbp protein to the GABA\nType 1 receptor complex (PMID: 28343864, PMID: 35436993, PMID: 38582872).\nFor example, we showed in a model of steatohepatitis induced by a methionine/choline-\ndeficient diet that mAb 7G4a, knockout of Acbp and Gabrg2F77I/F77I mutation had similar\neffects in inhibiting the manifestation of liver disease (PMID: 36191214). In addition, mAb\n7G4a, knockout of Acbp and Gabrg2F77I/F77I mutation similarly protected the liver against high-\nfat diet-induced steatosis (PMID: 35436993). Moreover, mAb 7G4a, knockout\nof Acbp and Gabrg2F77I/F77I mutation have been systematically compared with respect to\ntheir capacity to block the metabolic manifestations of Cushing syndrome induced by\nsupplementation with corticosterone. Thus, mAb 7G4a, knockout\nof Acbp and Gabrg2F77I/F77I mutation similarly attenuated the corticosterone-induced\nweight gain, hepatomegaly, visceral adiposity, sarcopenia, dyslipidemia and type-2 diabetes\n(PMID: 39578649). Finally, mAb 7G4a and knockout of Acbp similarly mitigated mechanical\ndestabilization-induced knee osteoarthritis (PMID: 40082721).\nFinally, we have added this information as a limitation in the Discussion of the revised version:\n\"A limitation of our study is the absence of an in vivo genetic ACBP knockout model. However,\nour study incorporates in vitro models using both primary hepatocytes and HepG2 cells, in\n2\nwhich ALMS1 was genetically silenced or knocked out, supporting the relevance of our findings\nat the cellular level. Nonetheless, prior studies have shown that inhibiting the ACBP system—\nwhether by neutralizing extracellular ACBP, knocking out the Acbp gene (thus removing both\nintra- and extracellular ACBP), or mutating the ACBP receptor (thus affecting only signaling\nby extracellular ACBP)—provides comparable protection against liver damage induced by\nmethionine-choline deficiency, hepatic steatosis triggered by high-fat diets, and high-dose\ncorticotherapy-induced metabolic shifts leading to visceral obesity, steatosis, dyslipidemia and\ninsulin resistance. These findings strongly suggest that extracellular ACBP has pathogenic\neffects that can be counteracted by neutralizing antibodies acting on target. In this study, we\nobserved that certain metabolites, which are dysregulated exclusively in the AöS model, but\nnot in DIO model, are normalized by ACBP inhibition, suggesting that ACBP neutralization\nmay have broadly positive effects across different models of metabolic derangement.”\nRemark No. 2 by reviewer No. 1: Incomplete Evidence for Lipogenesis and Lipolysis: The\nauthors claim an impact on lipogenesis in Alms1-/- mice treated with anti-ACBP antibodies.\nHowever, the original reviewer's request for tracer analyses to directly quantify de novo\nlipogenesis remains unaddressed. While the authors provide additional transcriptomic and\nproteomic data supporting reduced lipogenesis, these are indirect measures. The authors should\nhave included isotope-labeled fatty acid or glucose tracers to more convincingly demonstrate\nan actual decrease in lipid synthesis, strengthening their claims about the metabolic impact of\nACBP inhibition.\nOur response: Thank the reviewer for this point that we have addressed. To evaluate the state\nof lipogenesis and lipolysis in Alms1-/- mice with or without treatment, we intraperitoneally\ninjected 13C-labeled glucose (New Figure 4J-K and S4N). As compared to WT controls, in\nAlms1-/- mice, we observed an increase in 13C-glycerol-3-phosphate and alterations in 13C-\nglucose-6-phosphate in plasma, as well as lower retention of 13C-glycerol-3-phosphate and\naccumulation of 13C-citrate in the liver, indicating a shift of glucose carbon toward lipid\nsynthesis. Upon neutralization of ACBP, these parameters largely return to normal, reflecting\nthe restoration of a normal glucose metabolism. We conclude that reducing excess ACBP\nnormalizes metabolism in Alms1-/- mice even without correcting the autophagy deficit.\nRemark No. 3 by reviewer No. 1: Knock-down in primary hepatocytes: In their resubmitted\nstudy, the authors have used primary hepatocytes to knock down acbp via siRNA to\ndemonstrate the intracellular effects of ACBP inhibition. This methodology, however, raises\nconcerns in light of their primary aim of investigating the extracellular role of ACBP. By\nfocusing on intracellular knockdown through siRNA in primary hepatocytes, the authors\nintroduce a mechanistic inconsistency, as this approach (primarily) targets intracellular ACBP,\nwhich does not align with their hypothesis that extracellular ACBP is the critical driver of\nmetabolic disturbances.\nOur response: We thank the reviewer for raising this important point. We fully agree that our\ncentral hypothesis relates to the role of extracellular ACBP in the development of metabolic\ndisorders. The siRNA experiments in primary hepatocytes were not intended to contradict this\nhypothesis, but rather to complement it by exploring whether ACBP has any intracellular\neffects on hepatocytes. We recognize that this could be confusing and have clarified the\nrationale and scope of these experiments in the revised manuscript.\nTo better address the reviewer's concern, we highlight that multiple independent studies have\nshown that inhibition of the ACBP system, whether through extracellular neutralizing\n3\nantibodies, complete gene inactivation (eliminating both intracellular and extracellular ACBP),\nor mutation of the ACBP receptor (selectively affecting extracellular signaling), consistently\nproduces comparable biological outcomes. These include protection against (i) liver damage\ninduced by methionine-choline deficient, (ii) hepatic steatosis induced by HFD, (iii) systemic\nmetabolic shifts induced by high-dose corticotherapy, and (iv) knee osteoarthritis induced by\nmechanical destabilization. In our opinion, these findings strongly suggest that the inhibition\nof extracellular Acbp with the antibody affects the system by on-target effects. Moreover, they\nindicate that inhibition of extracellular Acbp (which is achieved by injection of the antibody or\nby mutation of the receptor) is sufficient to obtain protection against obesogenic stimuli.\nWe have revised the Discussion section to better clarify the consistency across models and\napproaches and to make our mechanistic interpretation more consistent with our central\nhypothesis.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nPoint-by-point reply to Reviewer No. 2\nGeneral critique by reviewer No. 2:\nUnfortunately, many of the problems noted in the initial review persist in this revised version.\nRemark No. 1 by reviewer No. 2: The point of including a DIO control in the omics analysis\nis to control for the effects of obesity itself and truly identify the effects of the mutation. This\ntype of control is needed on Fig 1, and the analysis performed in Fig S5 does not really address\nthis problem.\nOur response: Thank you for your valuable comment. We have now revised the figures in the\nmain manuscript to better differentiate the effects of the Alms1 mutation from those caused by\nobesity. Specifically, we have reorganized the figures as follows:\n1. Figure 1 now presents data from mice prior to the development of obesity and\nsymptoms.\n2. Figure 2 includes data from 10-week-old and 20-week-old mice. At 10 weeks, mice are\nat an early stage of obesity where the treatment is effective, and obesity parameters\nderived from both diet-induced and mutation-induced obesity are evaluated. At 20\nweeks, mice are at an advanced stage of the disease, a stage in which the treatment is\nno longer efficient.\nFurthermore, we have separated the PCA analysis into:\n• New Figure 2C: Showing metabolites that change exclusively in Alms1 mutant mice\n(Alms1-specific changes), since both models are obese.\n• New Figure S2B: Displaying common changes that are more likely dependent on\nobesity rather than the mutation per se.\nThese revisions, along with our previous correlation analysis between the two models, clarify\nthe distinctions between Alms1 mutation-specific effects and obesity-specific changes. These\nresults are essential for understanding later (new Figure 5) that ACBP neutralization does not\nonly reverse changes that occur in obese mice irrespective of the cause of obesity (induced by\ndiet or by Alms1 mutation), but also reverses changes that a specific to obese Alms1mutant\nmice.\nremain unclear. The rebuttal letter mentions that this information is contained in supplementary\nannex 1, but after 15 minutes of searching through all the documents this could not be found.\nThis information is so central to the rigor of the experiments that it really should be described\nin the methods section.\nOur response: We sincerely apologize for the error in our previous response and for any\ninconvenience this may have caused. We appreciate the reviewer's assessment and patience in\nsearching for this information. To ensure clarity and accessibility, we have included details\ninformation on cohousing in the Materials and Methods section of the main manuscript. It is\nnow placed there instead of in the Supplemental Annex 1 to make it easier to locate.\nRegarding these cohousing conditions, we confirmed that control animals were littermates of\nthe mutant mice and were cohoused with mutants until weaning. After weaning, mice were\neither randomly housed (for general experiments) or maintained under specific cohousing\nconditions (for microbiota analysis), as detailed in the Materials and Methods:\n“Cohousing strategy: For microbiota experiments, the cohousing strategy was designed to\nprevent microbiota exchange through coprophagy. Samples were collected from cages\ncontaining mice under identical experimental conditions to ensure consistency. For all other\nexperiments, cages contained randomly selected mice to mitigate potential effects of cage-\nspecific microbial changes. Importantly, the observed phenotypic differences between groups\nremained robust regardless of cohousing strategy, supporting the reliability of our conclusions.”\nRemark No. 3 by reviewer No. 2: The microbiota analysis comparing animals of different\nweights will detect differences that may simply result from obesity itself, and again, DIO\ncontrols would be needed to clarify the nature of the results.\nOur response: We are very grateful for your comment. To clarify the specific effects of the\nmutation versus those derived from obesity, we have added two new control groups to our\nexperiments:\n• 3-week-old Alms1 mutant mice (Alms1-/- which are not yet obese).\n• An additional group with 10-week-old diet-induced obesity mice (DIO).\nWe would like to especially thank the reviewer for this point of improvement. Thanks to this\nimplementation of the experiment, we have been able to expand the number of bacterial genera\nmodified and normalized by the treatment and, better yet, to discriminate which of them are a\nsimple consequence of the mouse obesogenic state (including the genera initially shown, such\nas Akkermansia and Allobaculum). These additional control groups have substantially\nimproved our work, resulting in completely new Figures 6 and S6, which allow us to conclude\nthat an increase in the intestinal population of Desulfovibrio (among other new genera) is\nspecifically associated with the Alms1 mutation, even before obesity manifests. All other\nmicrobial changes appear to be a consequence of obesity, since they are also observed in diet-\ninduced obesity.\nWe have added a final paragraph to the discussion that includes the potential in the field of this\nresult:\n“Taken together, our study opens an interesting avenue to investigate whether the relationship\nbetween Alström syndrome, cilia, autophagy, ACBP, and obesity could be extrapolated to other\nciliopathies with associated metabolic alterations. Furthermore, our data suggest that the\n6\nspecific microbiota alterations identified in this study could serve as biomarkers or even\ntherapeutic targets for personalized interventions in ciliopathies. Future studies are warranted\nto assess the applicability of these findings to patients with Alström syndrome and to further\nexplore these promising possibilities, including the therapeutic potential of ACBP\nneutralization and microbiome modulation in the context of cilia-related disorders.”\nRemark No. 4 by reviewer No. 2: The lack of metabolic cage analysis is also a weakness that\npersists in this revision.\nOur response: We apologize for not being able to perform the metabolic cage analysis.\nUnfortunately, we could not modify our approved ethical authorization in time, and we also\nfaced limitations in the availability of the mice. However, we conducted an experiment with\n13C-labeled glucose, providing additional metabolic insights that partially compensate for the\nlack of metabolic cage data. We appreciate your understanding and hope this alternative\napproach is satisfactory.\nTo evaluate the state of lipogenesis and lipolysis in Alms1-/- mice with or without treatment, we\nperformed the intraperitoneal injection of 13C-labeled glucose (New Figure 4J-K and S4N). In\nAlms1-/- mice, we observed an increase in 13C-glycerol-3-phosphate and alterations in 13C-\nglucose-6-phosphate in plasma, as well as lower retention of 13C-glycerol-3-phosphate and\naccumulation of 13C-citrate in the liver, indicating a shift of glucose carbon toward lipid\nsynthesis. Upon ACBP neutralization, these parameters largely return to normal. We conclude\nthat reducing excess ACBP normalizes metabolism in Alms1-/- mice even without correcting\nthe autophagy deficit.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nPoint-by-point reply to Reviewer No. 4\nReviewer No. 4:\nThe authors have satisfactorily addressed all the comments by the reviewer.\nOur response: No further action is required on our side with respect to Reviewer No. 4. We\nthank reviewers 3 and 4 for their contributions to this work.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 08/07/2025\nGeneral response to the reviewers\nWe would like to express our sincere gratitude to the four reviewers for their constructive\ncomments and suggestions during the three rounds of review. We were able to address and\nrespond to all of their questions during this process, and the changes and results we added have\nallowed us to significantly improve the manuscript. We are convinced that these improvements\nenhance the value and potential impact of our work.\nPoint-by-point reply to Reviewer No. 1.\nOverall: While I appreciate the authors’ substantial efforts to strengthen their manuscript\nthrough extensive multi-omics profiling and the addition of new experiments, I must raise two\nessential issues that remain inadequately addressed and preclude my recommendation for\nacceptance in the manuscript’s current form.\nConclusion: I remain positive about the general direction and novelty of the study. However,\nuntil the two concerns outlined above — the underrepresentation of ACBP KO data and the\nindirect nature of lipogenesis evidence — are appropriately addressed, I cannot recommend the\nmanuscript for publication. I encourage the authors to revise the manuscript to strengthen\nmechanistic clarity while maintaining their otherwise thorough systems-level approach.\nRemark No. 1 by reviewer No. 1: Misrepresentation of the ACBP KO Mouse Literature\nThe authors originally stated that ACBP knockout mice are non-viable, which has now been\ncorrected in their response. However, their revised justification for not using these mice —\nnamely that they only display transient metabolic phenotypes — is misleading. Multiple\npublished studies (e.g. PMID 28343864, 30938715 and 33346070) have demonstrated the\nviability of ACBP knockout mice and described robust phenotypes, including enhanced energy\nexpenditure, WAT beiging, resistance to obesity, and improved glucose homeostasis. Given\nthis, I strongly urge the authors to acknowledge this body of work more transparently and revise\ntheir discussion to reflect that viable ACBP KO models exist and are informative. While I\nunderstand the challenges of generating a double KO (Alms1/Acbp), dismissing existing\nmodels may diminish the credibility of the mechanistic claims made in the manuscript.\nOur response: We sincerely thank the reviewer for this important comment and fully agree\nwith his/her observation. We appreciate the opportunity to correct and clarify this point. In\nresponse to the reviewer's point, we have revised the discussion section to more transparently\n1\nacknowledge the existing body of literature on viable Acbp knockout mice and their relevance.\nSpecifically, we have expanded the limitations of our study to include the following statement:\n“One major limitation of our study is the absence of a genetic ACBP knockout model. We\nacknowledge that viable Acbp knockout mice exist and display robust phenotypes, including\nenhanced energy expenditure, beiging of white adipose tissue, resistance to diet-induced\nobesity, and improved glucose homeostasis, as reported in several studies (PMIDs 28343864,\n30938715 and 33346070). These findings highlight the mechanistic relevance of the ACBP\nsystem in energy metabolism and validate its role in obesity-related phenotypes. While these\nmodels offer important insights, generating a double Alms1/Acbp knockout mouse model was\nnot technically feasible within the timeframe and scope of this study. Based on our experience\nwith conditional Acbp knockout strategies, we estimate that developing such a model, requiring\nmultiple breeding steps, tissue-specific alleles, and ethical approvals for animal\nexperimentation, would require at least 9-12 months. Nonetheless, our study incorporates in\nvitro models using both primary hepatocytes and HepG2 cells, in which ALMS1 was genetically\nsilenced or knocked out, supporting the relevance of our findings at the cellular level. In\naddition, prior studies have shown that inhibiting the ACBP system in vivo—whether by\nneutralizing extracellular Acbp, knocking out the Dbi gene (thus removing both intra- and\nextracellular ACBP), or mutating the ACBP receptor (thus affecting only signaling by\nextracellular ACBP)—provides comparable protection against liver damage induced by\nmethionine-choline deficiency (PMID: 36191214), hepatic steatosis triggered by high-fat diets\n(PMID: 35436993, 38582872), and high-dose corticotherapy-induced metabolic shifts leading\nto visceral obesity, steatosis, dyslipidemia and insulin resistance (PMID: 39578649). These\nfindings strongly suggest that extracellular ACBP has pathogenic effects that can be\ncounteracted by neutralizing antibodies acting on target. Our study identified metabolites that\nare dysregulated exclusively in the AöS model, but not in the DIO model, and are normalized\nby ACBP inhibition. This suggests that ACBP neutralization could have wide-ranging benefits\nacross various models of metabolic dysfunction”.\nWe hope this expanded discussion adequately addresses the reviewer’s concern and reinforces\nthe scientific context and rationale for our experimental approach.\nThe authors use changes in 13C-glucose-derived glycerol-3-phosphate (G3P) as a proxy for\naltered lipogenesis. However, G3P is primarily derived from glycolysis and reflects glycerol\nbackbone availability rather than fatty acid synthesis per se. This metabolite alone is not a\ndefinitive readout of de novo lipogenesis. Without parallel measurement of 13C-incorporation\ninto fatty acid chains (e.g., palmitate or other lipids), the claim that ACBP neutralization\nnormalizes lipogenesis remains speculative. I encourage the authors to provide additional tracer\ndata that more directly quantifies lipid synthesis.\nOur response:\nWe thank the reviewer for this scientifically sound comment. We fully agree that glycerol-3-\nphosphate alone does not provide a direct proxy for de novo lipogenesis. Thanks to the\nreviewer's suggestion, we expanded our analysis by incorporating additional 13C tracer data that\ndirectly measure 13C incorporation from 13C-labeled glucose into palmitate in the liver, thus\nproviding stronger evidence of fatty acid synthesis. These new results have been included in\nthe revised manuscript (Figure 4J-K, Figure S4N-O, and Supplementary Table S6) and are\ndetailed in the Results section.\n“Finally, we evaluated lipogenesis in Alms1⁻/⁻ mice by intraperitoneal administration of ¹³C-\nlabeled glucose (Figure S4N). In these obese animals, an increase in ¹³C-palmitate was\nobserved in the liver, indicating de novo lipogenesis from glucose (Figure 4J). In parallel, we\nidentified an uncoupling between plasma (increased) and hepatic (decreased) ¹³C-glycerol-3-\nphosphate (gly3P) levels, suggesting accelerated consumption of this metabolite in the liver for\ntriglyceride synthesis. This pattern is consistent with a hyperactive lipogenic state in which\ngly3P does not accumulate freely, but is rapidly channeled towards fatty acid esterification\n(Figure S4O). Of note, treatment with anti-ACBP antibody prevented both ¹³C-palmitate\naccumulation and ¹³C-gly3P uncoupling, indicating the normalization of carbon flux into lipid\npathways and a restoration of metabolic balance (Figures 4J and S4O). Moreover, a positive\ncorrelation between the levels of ¹³C-labeled palmitate and body weight was observed (Figure\n4K), supporting the idea that ACBP neutralization prevents obesity in Alms1-/- mice through an\neffect on lipogenesis. In conclusion, ACBP neutralization normalizes lipid metabolism both in\nisolated hepatocytes from Alms1-/- mice and in vivo, in mice with this genotype, even without\nrestoring impaired autophagy.”\nThese results fully support the initial hypothesis, confirming that neutralization of ACBP\nreverses metabolic reprogramming towards accrued lipogenesis in Alms1⁻/⁻ mice.\nOverall: The authors have addressed all my concerns. The inclusion of pre-obese, weight\nmatched Alsm1 knockout mice as the inclusion of weight matched DIO controls overcome all\nconcerns I had and I delighted to recommend publication of the paper.\nOur response: No further action is required on our side with respect to Reviewer No. 2. We\nthank reviewers 2, 3 and 4 for their contributions to this work.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 10/10/2025\nGeneral response to the reviewers\nWe sincerely thank the reviewers and the editorial team for their constructive comments during\nthe review rounds. Thanks to their work, the article has been significantly improved, and the\nconclusions and results have been considerably refined.\nPoint-by-point reply to Reviewer No. 1.\nRemark No. 1 by reviewer No. 1: I appreciate the authors’ efforts to address my earlier\nconcerns, and I find that the manuscript has generally improved. However, I remain skeptical\nabout the 13C-palmitate data presented (Figure 4, panel o). From the data shown, it is not\npossible for me to determine whether the findings are statistically significant, and the results\nwould be considerably more convincing if additional data points were provided.\nOur response: After rigorously analyzing the data, we observed that, although the increase in\nAlms1-/- mice compared to Alms1 WT mice was significantly directional, we were unable to\nconfirm this in multiple comparisons when analyzing the treatment effect. Therefore, we thank\nthe reviewer for their accurate assessment and have definitively removed any statements about\nexacerbated lipogenesis from the entire text, in addition to tempering the interpretation of the\ntracers. The abstract, results, discussion, figure 4 and the new Figure 7 have been updated\naccordingly:\nRemoved from Abstract: ”These conditions triggered a lipogenic response and changes in the\nbacterial microbiota, which were observed in adult male AöS mice with obesity”.\nNew version: “These conditions are consistent with the obesogenic phenotype and with\nalterations in the gut microbiota that become manifest as the mice age and develop obesity”.\nRemoved from Results: “supporting the idea that ACBP neutralization prevents obesity in\nAlms1-/- mice through an effect on lipogenesis. In conclusion, ACBP neutralization normalizes\nlipid metabolism both in isolated hepatocytes from Alms1-/- mice and in vivo, in mice with this\ngenotype, even without restoring impaired autophagy”\nNew version: “In contrast, hepatic ¹³C-palmitate enrichment 2 h after ¹³C-glucose injection was\ndirectionally higher in obese Alms1-/- than in WT mice (unpaired two-sided Student’s t-test;\nnominal P value = 0.049; exact values showed in Source Data) and positively correlated with\nbody weight, but this difference did not remain significant after correction for multiple-\ncomparisons (Figure 4j–k). Collectively these tracer data are consistent with lipid-anabolic\n1\nsignatures, but do not establish causal changes in de novo lipogenesis rates, which would\nrequire dedicated flux analyses.”\nRemove from Discussion: “These events might predispose to excessive lipogenesis and the\ndevelopment of metabolic syndrome”\nNew version: “Altogether, our multi-omics and physiological analyses identify ACBP as a\npromising target for mitigating metabolic manifestations in Alms1⁻/⁻ mice”.\nFigure 7 revised to avoid mechanistic overstatement of lipogenesis: We have revised Figure\n7 to use the neutral descriptor “lipid storage”, thus representing a shift in lipid balance without\nconclusive induction of de novo lipogenesis.\n2"}, {"round": 2, "reviewer_comments": {"reviewer_1": "Overall:\nThe manuscript presents a compelling study linking extracellular levels of acyl-CoA binding protein (ACBP) to ciliopathic obesity, particularly Alström syndrome (AöS), through multi-omics approaches. The study is valuable for identifying a novel target in ACBP that could mitigate obesity-related complications. However, the reliance on neutralizing antibodies without using an acbp knockout model significantly weakens the mechanistic insights into the role of ACBP, particularly when claiming its extracellular versus intracellular roles.\nMajor concerns:\nACBP Neutralization with Antibodies vs. Gene Ablation: One of the core issues is the authors' reliance on neutralizing antibodies to inhibit ACBP. Although the authors argue that neutralizing ACBP in Alms1-/- mice prevents metabolic manifestations, they fail to demonstrate the same through genetic ablation of acbp. As originally was pointed out, the use of genetically modified acbp knockout mice would have provided a more robust mechanistic understanding. In their rebuttal, the authors state that acbp ablation leads to lethality. This is incorrect as several studies have shown that Acbp ablation in mice results in impaired epidermal barrier resulting in among others increased systemic energy expenditure, beiging of white adipose tissue, resistance to diet-induced obesity and improved glucose tolerance (doi: 10.1016/j.molmet.2020.101144; doi: 10.1194/jlr.M060780; doi: 10.1016/j.celrep.2013.11.010; doi: 10.1074/jbc.M110.161109). I acknowledge that creating such a model will take time due to the complexity of breeding required genotypes. However, this is not an acceptable justification for excluding critical control experiments, as this leaves open questions about how much of the observed phenotype is due to antibody targeting versus gene ablation.\nIncomplete Evidence for Lipogenesis and Lipolysis: The authors claim an impact on lipogenesis in Alms1-/- mice treated with anti-ACBP antibodies. However, the original reviewer's request for tracer analyses to directly quantify de novo lipogenesis remains unaddressed​. While the authors provide additional transcriptomic and proteomic data supporting reduced lipogenesis, these are indirect measures. The authors should have included isotope-labeled fatty acid or glucose tracers to more convincingly demonstrate an actual decrease in lipid synthesis, strengthening their claims about the metabolic impact of ACBP inhibition.\nKnock-down in primary hepatocytes: In their resubmitted study, the authors have used primary hepatocytes to knock down acbp via siRNA to demonstrate the intracellular effects of ACBP inhibition. This methodology, however, raises concerns in light of their primary aim of investigating the extracellular role of ACBP. By focusing on intracellular knockdown through siRNA in primary hepatocytes, the authors introduce a mechanistic inconsistency, as this approach (primarily) targets intracellular ACBP, which does not align with their hypothesis that extracellular ACBP is the critical driver of metabolic disturbances.", "reviewer_2": "Unfortunately, many of the problems noted in the initial review persist in this revised version.\n- The point of including a DIO control in the omics analysis is to control for the effects of obesity itself and truly identify the effects of the mutation. This type of control is needed on Fig 1, and the analysis performed in Fig S5 does not really address this problem.\n- The nature of the breeding scheme and housing conditions, remain unclear. The rebuttal letter mentions that this information is contained in supplementary annex 1, but after 15 minutes of searching through all the documents this could not be found. This information is so central to the rigor of the experiments that it really should be described in the methods section.\n- The microbiota analysis comparing animals of different weights will detect differences that may simply result from obesity itself, and again, DIO controls would be needed to clarify the nature of the results.\n- The lack of metabolic cage analysis is also a weakness that persists in this revision.", "reviewer_4": "The authors have satisfactorily addressed all the comments by the reviewer."}, "author_response": "Manuscript number: NCOMMS-23-62105\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nGeneral comments to the reviewers\nWe would like to express our sincere gratitude to the reviewers for their exceptionally thorough\nand constructive evaluation during both rounds of review. Their insightful comments and\nsuggestions have allowed us to significantly improve the manuscript, which now includes a\ncomplete characterization of Alström syndrome at different disease stages. Over the course of\nthe two rounds of review, we have integrated four comprehensive omics analyses\n(metabolomics, proteomics, transcriptomics, and microbiome), providing a robust\nmultidimensional description of the pathophysiology and its modulation by targeting ACBP.\nMoreover, we present a detailed insight into the role of cilia, autophagy, and ACBP in this\ndisease, and report on the preclinical efficacy of a potential therapeutic strategy. We are\nconvinced that these advances significantly enhance the translational value and potential impact\nof our work.\nPoint-by-point reply to Reviewer No. 1.\nOverall: The manuscript presents a compelling study linking extracellular levels of acyl-CoA\nbinding protein (ACBP) to ciliopathic obesity, particularly Alström syndrome (AöS), through\nmulti-omics approaches. The study is valuable for identifying a novel target in ACBP that could\nmitigate obesity-related complications. However, the reliance on neutralizing antibodies\nwithout using an acbp knockout model significantly weakens the mechanistic insights into the\nrole of ACBP, particularly when claiming its extracellular versus intracellular roles.\nOur response: The reviewer raises a few additional points that we address as indicated below.\nRemark No. 1 by reviewer No. 1: ACBP Neutralization with Antibodies vs. Gene Ablation:\nOne of the core issues is the authors' reliance on neutralizing antibodies to inhibit ACBP.\nAlthough the authors argue that neutralizing ACBP in Alms1-/- mice prevents metabolic\nmanifestations, they fail to demonstrate the same through genetic ablation of acbp. As originally\nwas pointed out, the use of genetically modified acbp knockout mice would have provided a\nmore robust mechanistic understanding. In their rebuttal, the authors state that acbp ablation\nleads to lethality. This is incorrect as several studies have shown that Acbp ablation in mice\nresults in impaired epidermal barrier resulting in among others increased systemic energy\nexpenditure, beiging of white adipose tissue, resistance to diet-induced obesity and improved\nglucose tolerance (doi: 10.1016/j.molmet.2020.101144; doi: 10.1194/jlr.M060780; doi:\n10.1016/j.celrep.2013.11.010; doi: 10.1074/jbc.M110.161109). I acknowledge that creating\nsuch a model will take time due to the complexity of breeding required genotypes. However,\nthis is not an acceptable justification for excluding critical control experiments, as this leaves\nopen questions about how much of the observed phenotype is due to antibody targeting versus\ngene ablation.\nthe knockout Acbp mouse model was lethal. Indeed, a non-lethal full-body ACBP knockout\nmouse has already been generated (Doi: 10.1074/jbc.M110.161109). However, in 2015, we\nformally requested a collaboration to the authors of this model, which was unfortunately\nrejected. Furthermore, it is important to highlight that the available non-lethal ACBP knockout\nmodel shows only a transient metabolic phenotype restricted to a narrow period between\npostnatal days 20 and 30, as described by the original authors (Doi: 10.1074/jbc.M110.161109),\nand the displayed Alström syndrome phenotype occurs from day 60 of life of the diseased\nmouse. In fact, the authors themselves state in the Discussion section that \"future investigations\nusing tissue-specific knock-out models are needed to establish the role of ACBP in TAG and\nCE accumulation in the liver and in SREBP processing\" highlighting the importance of\nconditional approaches, such as the one we implemented. This situation led us to develop our\nown tissue-specific ACBP conditional KO mouse to target the specific extracellular and tissue\nfunctions of ACBP, published in Cell Metabolism in 2019.\nWe fully understand and appreciate the reviewer's interest in a double knockout model (DKO,\nAlms1/Acbp). However, based on our experience generating the Acbp conditional knockout\nmodel, we estimate that generating the double knockout mouse (Alms1 mutant crossed with\nAcbp-floxed mice and a tissue-specific Cre line) would require approximately 18 months, due\nto the complexity of breeding schemes and the need for additional approvals of animal testing\nprotocols according to national regulations. We believe that while this model would\nundoubtedly be valuable, its generation exceeds the feasibility of the study.\nAlthough technically more limited than a complete DKO, our current strategy provides a solid\nmechanistic understanding of the extracellular role of ACBP in the context of Alström\nsyndrome. Moreover, it’s important to note that the effect of the neutralizing antibody used in\nthis study has already been compared to genetic manipulations that inhibit the Acbp system,\nnamely:\n(i) Conditional knockout of Acbp by a ubiquitous tamoxifen-inducible CRE recombinase\nexcising the floxed exon 2 of the Acbp gene in adult mice (PMID: 31422903)\n(ii) Point mutation of the Acbp receptor, GABRG2, in position 72, which if present in\nhomozygosity (genotype: Gabrg2F77I/F77I) abolishes binding of Acbp protein to the GABA\nType 1 receptor complex (PMID: 28343864, PMID: 35436993, PMID: 38582872).\nFor example, we showed in a model of steatohepatitis induced by a methionine/choline-\ndeficient diet that mAb 7G4a, knockout of Acbp and Gabrg2F77I/F77I mutation had similar\neffects in inhibiting the manifestation of liver disease (PMID: 36191214). In addition, mAb\n7G4a, knockout of Acbp and Gabrg2F77I/F77I mutation similarly protected the liver against high-\nfat diet-induced steatosis (PMID: 35436993). Moreover, mAb 7G4a, knockout\nof Acbp and Gabrg2F77I/F77I mutation have been systematically compared with respect to\ntheir capacity to block the metabolic manifestations of Cushing syndrome induced by\nsupplementation with corticosterone. Thus, mAb 7G4a, knockout\nof Acbp and Gabrg2F77I/F77I mutation similarly attenuated the corticosterone-induced\nweight gain, hepatomegaly, visceral adiposity, sarcopenia, dyslipidemia and type-2 diabetes\n(PMID: 39578649). Finally, mAb 7G4a and knockout of Acbp similarly mitigated mechanical\ndestabilization-induced knee osteoarthritis (PMID: 40082721).\nFinally, we have added this information as a limitation in the Discussion of the revised version:\n\"A limitation of our study is the absence of an in vivo genetic ACBP knockout model. However,\nour study incorporates in vitro models using both primary hepatocytes and HepG2 cells, in\n2\nwhich ALMS1 was genetically silenced or knocked out, supporting the relevance of our findings\nat the cellular level. Nonetheless, prior studies have shown that inhibiting the ACBP system—\nwhether by neutralizing extracellular ACBP, knocking out the Acbp gene (thus removing both\nintra- and extracellular ACBP), or mutating the ACBP receptor (thus affecting only signaling\nby extracellular ACBP)—provides comparable protection against liver damage induced by\nmethionine-choline deficiency, hepatic steatosis triggered by high-fat diets, and high-dose\ncorticotherapy-induced metabolic shifts leading to visceral obesity, steatosis, dyslipidemia and\ninsulin resistance. These findings strongly suggest that extracellular ACBP has pathogenic\neffects that can be counteracted by neutralizing antibodies acting on target. In this study, we\nobserved that certain metabolites, which are dysregulated exclusively in the AöS model, but\nnot in DIO model, are normalized by ACBP inhibition, suggesting that ACBP neutralization\nmay have broadly positive effects across different models of metabolic derangement.”\nRemark No. 2 by reviewer No. 1: Incomplete Evidence for Lipogenesis and Lipolysis: The\nauthors claim an impact on lipogenesis in Alms1-/- mice treated with anti-ACBP antibodies.\nHowever, the original reviewer's request for tracer analyses to directly quantify de novo\nlipogenesis remains unaddressed. While the authors provide additional transcriptomic and\nproteomic data supporting reduced lipogenesis, these are indirect measures. The authors should\nhave included isotope-labeled fatty acid or glucose tracers to more convincingly demonstrate\nan actual decrease in lipid synthesis, strengthening their claims about the metabolic impact of\nACBP inhibition.\nOur response: Thank the reviewer for this point that we have addressed. To evaluate the state\nof lipogenesis and lipolysis in Alms1-/- mice with or without treatment, we intraperitoneally\ninjected 13C-labeled glucose (New Figure 4J-K and S4N). As compared to WT controls, in\nAlms1-/- mice, we observed an increase in 13C-glycerol-3-phosphate and alterations in 13C-\nglucose-6-phosphate in plasma, as well as lower retention of 13C-glycerol-3-phosphate and\naccumulation of 13C-citrate in the liver, indicating a shift of glucose carbon toward lipid\nsynthesis. Upon neutralization of ACBP, these parameters largely return to normal, reflecting\nthe restoration of a normal glucose metabolism. We conclude that reducing excess ACBP\nnormalizes metabolism in Alms1-/- mice even without correcting the autophagy deficit.\nRemark No. 3 by reviewer No. 1: Knock-down in primary hepatocytes: In their resubmitted\nstudy, the authors have used primary hepatocytes to knock down acbp via siRNA to\ndemonstrate the intracellular effects of ACBP inhibition. This methodology, however, raises\nconcerns in light of their primary aim of investigating the extracellular role of ACBP. By\nfocusing on intracellular knockdown through siRNA in primary hepatocytes, the authors\nintroduce a mechanistic inconsistency, as this approach (primarily) targets intracellular ACBP,\nwhich does not align with their hypothesis that extracellular ACBP is the critical driver of\nmetabolic disturbances.\nOur response: We thank the reviewer for raising this important point. We fully agree that our\ncentral hypothesis relates to the role of extracellular ACBP in the development of metabolic\ndisorders. The siRNA experiments in primary hepatocytes were not intended to contradict this\nhypothesis, but rather to complement it by exploring whether ACBP has any intracellular\neffects on hepatocytes. We recognize that this could be confusing and have clarified the\nrationale and scope of these experiments in the revised manuscript.\nTo better address the reviewer's concern, we highlight that multiple independent studies have\nshown that inhibition of the ACBP system, whether through extracellular neutralizing\n3\nantibodies, complete gene inactivation (eliminating both intracellular and extracellular ACBP),\nor mutation of the ACBP receptor (selectively affecting extracellular signaling), consistently\nproduces comparable biological outcomes. These include protection against (i) liver damage\ninduced by methionine-choline deficient, (ii) hepatic steatosis induced by HFD, (iii) systemic\nmetabolic shifts induced by high-dose corticotherapy, and (iv) knee osteoarthritis induced by\nmechanical destabilization. In our opinion, these findings strongly suggest that the inhibition\nof extracellular Acbp with the antibody affects the system by on-target effects. Moreover, they\nindicate that inhibition of extracellular Acbp (which is achieved by injection of the antibody or\nby mutation of the receptor) is sufficient to obtain protection against obesogenic stimuli.\nWe have revised the Discussion section to better clarify the consistency across models and\napproaches and to make our mechanistic interpretation more consistent with our central\nhypothesis.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nPoint-by-point reply to Reviewer No. 2\nGeneral critique by reviewer No. 2:\nUnfortunately, many of the problems noted in the initial review persist in this revised version.\nRemark No. 1 by reviewer No. 2: The point of including a DIO control in the omics analysis\nis to control for the effects of obesity itself and truly identify the effects of the mutation. This\ntype of control is needed on Fig 1, and the analysis performed in Fig S5 does not really address\nthis problem.\nOur response: Thank you for your valuable comment. We have now revised the figures in the\nmain manuscript to better differentiate the effects of the Alms1 mutation from those caused by\nobesity. Specifically, we have reorganized the figures as follows:\n1. Figure 1 now presents data from mice prior to the development of obesity and\nsymptoms.\n2. Figure 2 includes data from 10-week-old and 20-week-old mice. At 10 weeks, mice are\nat an early stage of obesity where the treatment is effective, and obesity parameters\nderived from both diet-induced and mutation-induced obesity are evaluated. At 20\nweeks, mice are at an advanced stage of the disease, a stage in which the treatment is\nno longer efficient.\nFurthermore, we have separated the PCA analysis into:\n• New Figure 2C: Showing metabolites that change exclusively in Alms1 mutant mice\n(Alms1-specific changes), since both models are obese.\n• New Figure S2B: Displaying common changes that are more likely dependent on\nobesity rather than the mutation per se.\nThese revisions, along with our previous correlation analysis between the two models, clarify\nthe distinctions between Alms1 mutation-specific effects and obesity-specific changes. These\nresults are essential for understanding later (new Figure 5) that ACBP neutralization does not\nonly reverse changes that occur in obese mice irrespective of the cause of obesity (induced by\ndiet or by Alms1 mutation), but also reverses changes that a specific to obese Alms1mutant\nmice.\nremain unclear. The rebuttal letter mentions that this information is contained in supplementary\nannex 1, but after 15 minutes of searching through all the documents this could not be found.\nThis information is so central to the rigor of the experiments that it really should be described\nin the methods section.\nOur response: We sincerely apologize for the error in our previous response and for any\ninconvenience this may have caused. We appreciate the reviewer's assessment and patience in\nsearching for this information. To ensure clarity and accessibility, we have included details\ninformation on cohousing in the Materials and Methods section of the main manuscript. It is\nnow placed there instead of in the Supplemental Annex 1 to make it easier to locate.\nRegarding these cohousing conditions, we confirmed that control animals were littermates of\nthe mutant mice and were cohoused with mutants until weaning. After weaning, mice were\neither randomly housed (for general experiments) or maintained under specific cohousing\nconditions (for microbiota analysis), as detailed in the Materials and Methods:\n“Cohousing strategy: For microbiota experiments, the cohousing strategy was designed to\nprevent microbiota exchange through coprophagy. Samples were collected from cages\ncontaining mice under identical experimental conditions to ensure consistency. For all other\nexperiments, cages contained randomly selected mice to mitigate potential effects of cage-\nspecific microbial changes. Importantly, the observed phenotypic differences between groups\nremained robust regardless of cohousing strategy, supporting the reliability of our conclusions.”\nRemark No. 3 by reviewer No. 2: The microbiota analysis comparing animals of different\nweights will detect differences that may simply result from obesity itself, and again, DIO\ncontrols would be needed to clarify the nature of the results.\nOur response: We are very grateful for your comment. To clarify the specific effects of the\nmutation versus those derived from obesity, we have added two new control groups to our\nexperiments:\n• 3-week-old Alms1 mutant mice (Alms1-/- which are not yet obese).\n• An additional group with 10-week-old diet-induced obesity mice (DIO).\nWe would like to especially thank the reviewer for this point of improvement. Thanks to this\nimplementation of the experiment, we have been able to expand the number of bacterial genera\nmodified and normalized by the treatment and, better yet, to discriminate which of them are a\nsimple consequence of the mouse obesogenic state (including the genera initially shown, such\nas Akkermansia and Allobaculum). These additional control groups have substantially\nimproved our work, resulting in completely new Figures 6 and S6, which allow us to conclude\nthat an increase in the intestinal population of Desulfovibrio (among other new genera) is\nspecifically associated with the Alms1 mutation, even before obesity manifests. All other\nmicrobial changes appear to be a consequence of obesity, since they are also observed in diet-\ninduced obesity.\nWe have added a final paragraph to the discussion that includes the potential in the field of this\nresult:\n“Taken together, our study opens an interesting avenue to investigate whether the relationship\nbetween Alström syndrome, cilia, autophagy, ACBP, and obesity could be extrapolated to other\nciliopathies with associated metabolic alterations. Furthermore, our data suggest that the\n6\nspecific microbiota alterations identified in this study could serve as biomarkers or even\ntherapeutic targets for personalized interventions in ciliopathies. Future studies are warranted\nto assess the applicability of these findings to patients with Alström syndrome and to further\nexplore these promising possibilities, including the therapeutic potential of ACBP\nneutralization and microbiome modulation in the context of cilia-related disorders.”\nRemark No. 4 by reviewer No. 2: The lack of metabolic cage analysis is also a weakness that\npersists in this revision.\nOur response: We apologize for not being able to perform the metabolic cage analysis.\nUnfortunately, we could not modify our approved ethical authorization in time, and we also\nfaced limitations in the availability of the mice. However, we conducted an experiment with\n13C-labeled glucose, providing additional metabolic insights that partially compensate for the\nlack of metabolic cage data. We appreciate your understanding and hope this alternative\napproach is satisfactory.\nTo evaluate the state of lipogenesis and lipolysis in Alms1-/- mice with or without treatment, we\nperformed the intraperitoneal injection of 13C-labeled glucose (New Figure 4J-K and S4N). In\nAlms1-/- mice, we observed an increase in 13C-glycerol-3-phosphate and alterations in 13C-\nglucose-6-phosphate in plasma, as well as lower retention of 13C-glycerol-3-phosphate and\naccumulation of 13C-citrate in the liver, indicating a shift of glucose carbon toward lipid\nsynthesis. Upon ACBP neutralization, these parameters largely return to normal. We conclude\nthat reducing excess ACBP normalizes metabolism in Alms1-/- mice even without correcting\nthe autophagy deficit.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 31/03/2025\nPoint-by-point reply to Reviewer No. 4\nReviewer No. 4:\nThe authors have satisfactorily addressed all the comments by the reviewer.\nOur response: No further action is required on our side with respect to Reviewer No. 4. We\nthank reviewers 3 and 4 for their contributions to this work.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 08/07/2025\nGeneral response to the reviewers\nWe would like to express our sincere gratitude to the four reviewers for their constructive\ncomments and suggestions during the three rounds of review. We were able to address and\nrespond to all of their questions during this process, and the changes and results we added have\nallowed us to significantly improve the manuscript. We are convinced that these improvements\nenhance the value and potential impact of our work.\nPoint-by-point reply to Reviewer No. 1.\nOverall: While I appreciate the authors’ substantial efforts to strengthen their manuscript\nthrough extensive multi-omics profiling and the addition of new experiments, I must raise two\nessential issues that remain inadequately addressed and preclude my recommendation for\nacceptance in the manuscript’s current form.\nConclusion: I remain positive about the general direction and novelty of the study. However,\nuntil the two concerns outlined above — the underrepresentation of ACBP KO data and the\nindirect nature of lipogenesis evidence — are appropriately addressed, I cannot recommend the\nmanuscript for publication. I encourage the authors to revise the manuscript to strengthen\nmechanistic clarity while maintaining their otherwise thorough systems-level approach.\nRemark No. 1 by reviewer No. 1: Misrepresentation of the ACBP KO Mouse Literature\nThe authors originally stated that ACBP knockout mice are non-viable, which has now been\ncorrected in their response. However, their revised justification for not using these mice —\nnamely that they only display transient metabolic phenotypes — is misleading. Multiple\npublished studies (e.g. PMID 28343864, 30938715 and 33346070) have demonstrated the\nviability of ACBP knockout mice and described robust phenotypes, including enhanced energy\nexpenditure, WAT beiging, resistance to obesity, and improved glucose homeostasis. Given\nthis, I strongly urge the authors to acknowledge this body of work more transparently and revise\ntheir discussion to reflect that viable ACBP KO models exist and are informative. While I\nunderstand the challenges of generating a double KO (Alms1/Acbp), dismissing existing\nmodels may diminish the credibility of the mechanistic claims made in the manuscript.\nOur response: We sincerely thank the reviewer for this important comment and fully agree\nwith his/her observation. We appreciate the opportunity to correct and clarify this point. In\nresponse to the reviewer's point, we have revised the discussion section to more transparently\n1\nacknowledge the existing body of literature on viable Acbp knockout mice and their relevance.\nSpecifically, we have expanded the limitations of our study to include the following statement:\n“One major limitation of our study is the absence of a genetic ACBP knockout model. We\nacknowledge that viable Acbp knockout mice exist and display robust phenotypes, including\nenhanced energy expenditure, beiging of white adipose tissue, resistance to diet-induced\nobesity, and improved glucose homeostasis, as reported in several studies (PMIDs 28343864,\n30938715 and 33346070). These findings highlight the mechanistic relevance of the ACBP\nsystem in energy metabolism and validate its role in obesity-related phenotypes. While these\nmodels offer important insights, generating a double Alms1/Acbp knockout mouse model was\nnot technically feasible within the timeframe and scope of this study. Based on our experience\nwith conditional Acbp knockout strategies, we estimate that developing such a model, requiring\nmultiple breeding steps, tissue-specific alleles, and ethical approvals for animal\nexperimentation, would require at least 9-12 months. Nonetheless, our study incorporates in\nvitro models using both primary hepatocytes and HepG2 cells, in which ALMS1 was genetically\nsilenced or knocked out, supporting the relevance of our findings at the cellular level. In\naddition, prior studies have shown that inhibiting the ACBP system in vivo—whether by\nneutralizing extracellular Acbp, knocking out the Dbi gene (thus removing both intra- and\nextracellular ACBP), or mutating the ACBP receptor (thus affecting only signaling by\nextracellular ACBP)—provides comparable protection against liver damage induced by\nmethionine-choline deficiency (PMID: 36191214), hepatic steatosis triggered by high-fat diets\n(PMID: 35436993, 38582872), and high-dose corticotherapy-induced metabolic shifts leading\nto visceral obesity, steatosis, dyslipidemia and insulin resistance (PMID: 39578649). These\nfindings strongly suggest that extracellular ACBP has pathogenic effects that can be\ncounteracted by neutralizing antibodies acting on target. Our study identified metabolites that\nare dysregulated exclusively in the AöS model, but not in the DIO model, and are normalized\nby ACBP inhibition. This suggests that ACBP neutralization could have wide-ranging benefits\nacross various models of metabolic dysfunction”.\nWe hope this expanded discussion adequately addresses the reviewer’s concern and reinforces\nthe scientific context and rationale for our experimental approach.\nThe authors use changes in 13C-glucose-derived glycerol-3-phosphate (G3P) as a proxy for\naltered lipogenesis. However, G3P is primarily derived from glycolysis and reflects glycerol\nbackbone availability rather than fatty acid synthesis per se. This metabolite alone is not a\ndefinitive readout of de novo lipogenesis. Without parallel measurement of 13C-incorporation\ninto fatty acid chains (e.g., palmitate or other lipids), the claim that ACBP neutralization\nnormalizes lipogenesis remains speculative. I encourage the authors to provide additional tracer\ndata that more directly quantifies lipid synthesis.\nOur response:\nWe thank the reviewer for this scientifically sound comment. We fully agree that glycerol-3-\nphosphate alone does not provide a direct proxy for de novo lipogenesis. Thanks to the\nreviewer's suggestion, we expanded our analysis by incorporating additional 13C tracer data that\ndirectly measure 13C incorporation from 13C-labeled glucose into palmitate in the liver, thus\nproviding stronger evidence of fatty acid synthesis. These new results have been included in\nthe revised manuscript (Figure 4J-K, Figure S4N-O, and Supplementary Table S6) and are\ndetailed in the Results section.\n“Finally, we evaluated lipogenesis in Alms1⁻/⁻ mice by intraperitoneal administration of ¹³C-\nlabeled glucose (Figure S4N). In these obese animals, an increase in ¹³C-palmitate was\nobserved in the liver, indicating de novo lipogenesis from glucose (Figure 4J). In parallel, we\nidentified an uncoupling between plasma (increased) and hepatic (decreased) ¹³C-glycerol-3-\nphosphate (gly3P) levels, suggesting accelerated consumption of this metabolite in the liver for\ntriglyceride synthesis. This pattern is consistent with a hyperactive lipogenic state in which\ngly3P does not accumulate freely, but is rapidly channeled towards fatty acid esterification\n(Figure S4O). Of note, treatment with anti-ACBP antibody prevented both ¹³C-palmitate\naccumulation and ¹³C-gly3P uncoupling, indicating the normalization of carbon flux into lipid\npathways and a restoration of metabolic balance (Figures 4J and S4O). Moreover, a positive\ncorrelation between the levels of ¹³C-labeled palmitate and body weight was observed (Figure\n4K), supporting the idea that ACBP neutralization prevents obesity in Alms1-/- mice through an\neffect on lipogenesis. In conclusion, ACBP neutralization normalizes lipid metabolism both in\nisolated hepatocytes from Alms1-/- mice and in vivo, in mice with this genotype, even without\nrestoring impaired autophagy.”\nThese results fully support the initial hypothesis, confirming that neutralization of ACBP\nreverses metabolic reprogramming towards accrued lipogenesis in Alms1⁻/⁻ mice.\nOverall: The authors have addressed all my concerns. The inclusion of pre-obese, weight\nmatched Alsm1 knockout mice as the inclusion of weight matched DIO controls overcome all\nconcerns I had and I delighted to recommend publication of the paper.\nOur response: No further action is required on our side with respect to Reviewer No. 2. We\nthank reviewers 2, 3 and 4 for their contributions to this work.\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 10/10/2025\nGeneral response to the reviewers\nWe sincerely thank the reviewers and the editorial team for their constructive comments during\nthe review rounds. Thanks to their work, the article has been significantly improved, and the\nconclusions and results have been considerably refined.\nPoint-by-point reply to Reviewer No. 1.\nRemark No. 1 by reviewer No. 1: I appreciate the authors’ efforts to address my earlier\nconcerns, and I find that the manuscript has generally improved. However, I remain skeptical\nabout the 13C-palmitate data presented (Figure 4, panel o). From the data shown, it is not\npossible for me to determine whether the findings are statistically significant, and the results\nwould be considerably more convincing if additional data points were provided.\nOur response: After rigorously analyzing the data, we observed that, although the increase in\nAlms1-/- mice compared to Alms1 WT mice was significantly directional, we were unable to\nconfirm this in multiple comparisons when analyzing the treatment effect. Therefore, we thank\nthe reviewer for their accurate assessment and have definitively removed any statements about\nexacerbated lipogenesis from the entire text, in addition to tempering the interpretation of the\ntracers. The abstract, results, discussion, figure 4 and the new Figure 7 have been updated\naccordingly:\nRemoved from Abstract: ”These conditions triggered a lipogenic response and changes in the\nbacterial microbiota, which were observed in adult male AöS mice with obesity”.\nNew version: “These conditions are consistent with the obesogenic phenotype and with\nalterations in the gut microbiota that become manifest as the mice age and develop obesity”.\nRemoved from Results: “supporting the idea that ACBP neutralization prevents obesity in\nAlms1-/- mice through an effect on lipogenesis. In conclusion, ACBP neutralization normalizes\nlipid metabolism both in isolated hepatocytes from Alms1-/- mice and in vivo, in mice with this\ngenotype, even without restoring impaired autophagy”\nNew version: “In contrast, hepatic ¹³C-palmitate enrichment 2 h after ¹³C-glucose injection was\ndirectionally higher in obese Alms1-/- than in WT mice (unpaired two-sided Student’s t-test;\nnominal P value = 0.049; exact values showed in Source Data) and positively correlated with\nbody weight, but this difference did not remain significant after correction for multiple-\ncomparisons (Figure 4j–k). Collectively these tracer data are consistent with lipid-anabolic\n1\nsignatures, but do not establish causal changes in de novo lipogenesis rates, which would\nrequire dedicated flux analyses.”\nRemove from Discussion: “These events might predispose to excessive lipogenesis and the\ndevelopment of metabolic syndrome”\nNew version: “Altogether, our multi-omics and physiological analyses identify ACBP as a\npromising target for mitigating metabolic manifestations in Alms1⁻/⁻ mice”.\nFigure 7 revised to avoid mechanistic overstatement of lipogenesis: We have revised Figure\n7 to use the neutral descriptor “lipid storage”, thus representing a shift in lipid balance without\nconclusive induction of de novo lipogenesis.\n2"}, {"round": 3, "reviewer_comments": {"reviewer_1": "I appreciate the authors’ efforts to address my earlier concerns, and I find that the manuscript has generally improved. However, I remain skeptical about the 13C-palmitate data presented (Figure 4, panel o). From the data shown, it is not possible for me to determine whether the findings are statistically significant, and the results would be considerably more convincing if additional data points were provided."}, "author_response": "Manuscript number: NCOMMS-23-62105C-Z\nTitle: Identification of ACBP as a potential target in ciliopathic obesity through multi-omics\nnetwork analysis\nFirst author: Yaiza Corral Nieto\nLead author: José Manuel Bravo-San Pedro\nRe-submission date: 10/10/2025\nGeneral response to the reviewers\nWe sincerely thank the reviewers and the editorial team for their constructive comments during\nthe review rounds. Thanks to their work, the article has been significantly improved, and the\nconclusions and results have been considerably refined.\nPoint-by-point reply to Reviewer No. 1.\nRemark No. 1 by reviewer No. 1: I appreciate the authors’ efforts to address my earlier\nconcerns, and I find that the manuscript has generally improved. However, I remain skeptical\nabout the 13C-palmitate data presented (Figure 4, panel o). From the data shown, it is not\npossible for me to determine whether the findings are statistically significant, and the results\nwould be considerably more convincing if additional data points were provided.\nOur response: After rigorously analyzing the data, we observed that, although the increase in\nAlms1-/- mice compared to Alms1 WT mice was significantly directional, we were unable to\nconfirm this in multiple comparisons when analyzing the treatment effect. Therefore, we thank\nthe reviewer for their accurate assessment and have definitively removed any statements about\nexacerbated lipogenesis from the entire text, in addition to tempering the interpretation of the\ntracers. The abstract, results, discussion, figure 4 and the new Figure 7 have been updated\naccordingly:\nRemoved from Abstract: ”These conditions triggered a lipogenic response and changes in the\nbacterial microbiota, which were observed in adult male AöS mice with obesity”.\nNew version: “These conditions are consistent with the obesogenic phenotype and with\nalterations in the gut microbiota that become manifest as the mice age and develop obesity”.\nRemoved from Results: “supporting the idea that ACBP neutralization prevents obesity in\nAlms1-/- mice through an effect on lipogenesis. In conclusion, ACBP neutralization normalizes\nlipid metabolism both in isolated hepatocytes from Alms1-/- mice and in vivo, in mice with this\ngenotype, even without restoring impaired autophagy”\nNew version: “In contrast, hepatic ¹³C-palmitate enrichment 2 h after ¹³C-glucose injection was\ndirectionally higher in obese Alms1-/- than in WT mice (unpaired two-sided Student’s t-test;\nnominal P value = 0.049; exact values showed in Source Data) and positively correlated with\nbody weight, but this difference did not remain significant after correction for multiple-\ncomparisons (Figure 4j–k). Collectively these tracer data are consistent with lipid-anabolic\n1\nsignatures, but do not establish causal changes in de novo lipogenesis rates, which would\nrequire dedicated flux analyses.”\nRemove from Discussion: “These events might predispose to excessive lipogenesis and the\ndevelopment of metabolic syndrome”\nNew version: “Altogether, our multi-omics and physiological analyses identify ACBP as a\npromising target for mitigating metabolic manifestations in Alms1⁻/⁻ mice”.\nFigure 7 revised to avoid mechanistic overstatement of lipogenesis: We have revised Figure\n7 to use the neutral descriptor “lipid storage”, thus representing a shift in lipid balance without\nconclusive induction of de novo lipogenesis.\n2"}]

Decision letter
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