FAM13A affects body fat distribution and adipocyte function

Excess adiposity contributes to insulin resistance, type 2 diabetes, dyslipidemia, and CVD. However, BMI alone does not predict metabolic health, as some obese individuals are metabolically healthy and some normal-weight individuals are metabolically unhealthy. GWAS have identified variants associated with lower adiposity but a worse cardiometabolic profile, including higher fasting insulin, higher triglycerides, and lower HDL cholesterol, reflecting a metabolically unhealthy normal-weight phenotype. These variants also associate with higher waist-to-hip ratio and a higher visceral-to-subcutaneous adipose tissue ratio, indicating a shift of fat from subcutaneous to visceral depots. Among these loci are variants in or near FAM13A. Non-coding variants at FAM13A associate with glycemic and anthropometric traits (e.g., rs3822072 with higher fasting insulin and lower HDL; rs9991328 with higher WHRadjBMI), but the biological role of FAM13A in adipose tissue remains unclear. Given FAM13A’s high expression in human adipose tissue, the authors hypothesized that human genetics integrated with in vitro and in vivo adipose-focused studies would reveal mechanisms linking FAM13A to body fat distribution. The study aimed to: (1) test whether FAM13A variants affect FAM13A expression in adipose depots and associate with insulin resistance-related traits; (2) assess cell-autonomous effects of FAM13A on adipocyte biology in human models; and (3) evaluate metabolic, histologic, and transcriptomic consequences of Fam13a knockout in mice.

Previous GWAS linked FAM13A variants to glycemic and metabolic traits including fasting insulin (rs3822072) and WHRadjBMI (rs9991328). FAM13A is also implicated in lung diseases (COPD, asthma, pulmonary fibrosis) and liver cirrhosis, but its function in adipose tissue is not fully defined. Background literature suggests the importance of fat distribution (VAT vs SAT) for metabolic health, with higher VAT/SAT ratio linked to greater cardiometabolic risk independent of total fat. Mechanisms favoring healthy SAT expansion (e.g., GLUT4 overexpression, mitoNEET overexpression, PPARγ agonists) improve insulin sensitivity. Signaling pathways potentially relevant to FAM13A’s function include Rho GTPase and WNT/β-catenin, both implicated in regulating adipogenesis. Other studies have suggested FAM13A negatively regulates adipogenesis in various cell models and observed correlations between adipose Fam13a expression and obesity-related phenotypes in mice.

Human genetics and transcriptomics:

• Fine-mapping: Bayesian fine-mapping with FINEMAP to identify likely causal variants for FAM13A eQTLs in adipose tissue (GTEx v7). Defined a 99% credible set using FINEMAP posterior probabilities.
• eQTL and colocalization: Assessed FAM13A expression quantitative trait loci (cis-eQTLs) in SAT and VAT (GTEx v7) and performed colocalization with seven insulin resistance-related GWAS traits (WHRadjBMI, triglycerides, HDL, fasting insulin, fasting insulin adjusted for BMI, fasting glucose, BMI) using eCAVIAR with a modified colocalization posterior probability (mCLPP) that incorporates LD between GWAS and eQTL signals.
• Epigenomic enrichment: Tested enrichment of credible-set variants in H3K27ac-marked regulatory regions in adipose nuclei using permutation-based analysis.
• PheWAS: Conducted a phenome-wide association study in 337,536 UK Biobank participants using rs1377290 (proxy for rs9991328; LD R2=1.0). Linear models adjusted for age, sex, array, and 10 principal components assessed associations with 278 predefined phenotypes.
• Cohort expression-trait correlations: Correlated SAT FAM13A expression (BMI-adjusted) with metabolic traits in METSIM (n=770 expression arrays) and performed pathway analyses using ConsensusPathDB. Also used STAGE multi-organ expression data for gene-by-gene and gene-by-trait correlations (5% FDR, WGCNA).

Human cell models:

• SGBS preadipocytes (human SAT-derived) were cultured and differentiated. FAM13A knockdown was performed via siRNA (early and late differentiation stages) and CRISPR interference (dCas9-KRAB with three independent sgRNAs). Assessed adipogenic marker expression (CEBPA, PPARG, and beige markers PGC1A, UCP1), adipokines (ADIPOQ, LEP), lipolysis (glycerol release), and glucose uptake ([3H]-2-deoxyglucose) under basal and insulin-stimulated conditions.

Mouse models:

• Whole-body Fam13a knockout (KO) mice on C57BL/6 background; WT controls. Diets: standard chow or high-fat diet (HFD, 45% kcal fat) from 8 to 22 weeks of age (12–14 weeks HFD exposure). Both sexes studied; many analyses focused on males.
• Phenotyping: Body weight tracking; fasting plasma glucose, insulin, free fatty acids, triglycerides; glucose tolerance tests (GTT) and insulin tolerance tests (ITT).
• Adipose depots: Dissected inguinal WAT (iWAT, SAT) and gonadal WAT (gWAT, VAT) for weights and histology (H&E). Quantified adipocyte size distribution (Adiposoft), mean diameter, and calculated adipocyte number per depot from tissue weight and mean adipocyte volume (assuming triglyceride density 0.915 g/L).
• SVF isolation and adipogenesis: Isolated stromal vascular fraction (SVF) from SAT, induced adipogenesis in vitro (IBMX, dexamethasone, insulin, rosiglitazone). Assessed adipogenic markers (Pparg, Cebpa, Fabp4), Oil Red O staining, intracellular triglycerides, and glucose uptake in differentiated adipocytes. Evaluated beige markers (Pgcla, Ucp1). Performed ex vivo glucose uptake in SAT explants.
• RNA sequencing: RNA-seq of VAT, SAT, and liver from WT and KO mice on chow and HFD (n=4/group). STAR alignment to GRCm38; counts by STAR; differential expression with edgeR (FDR 10%), adjusting for diet, depot, RNA quality, and PEER factors. Pathway enrichment with ConsensusPathDB.
• Additional datasets: Used BTBR ob/ob mouse data to correlate adipose Fam13a expression with obesity and adipose cell proliferation (deuterium labeling). Flow cytometry of SVF to quantify APC and endothelial subsets (CD45-, Sca1+, CD31- or CD31+).

Statistics:

• Group comparisons by two-tailed t-tests or ANOVA with appropriate multiple comparison corrections. Kolmogorov–Smirnov tests for adipocyte diameter distribution curves. eQTL mapping via two-sided t-tests. Significance thresholds: typically p<0.05; FDR thresholds for expression analyses (5% or 10% as specified).

Human genetic and transcriptomic evidence:

• Fine-mapping of SAT FAM13A eQTLs identified rs9991328 as the most likely causal variant (fine-mapping posterior probability 0.66), associating with increased FAM13A expression (β=0.22±0.03, p=1e-08). The commonly reported rs3822072 had posterior probability 0.06. rs9991328 showed robust cis-eQTL effects in SAT (P≤1e-08) but not in VAT (P>1e-05), and was not a cis-eQTL for other nearby genes nor a trans-eQTL in adipose.
• Colocalization (mCLPP >0.8) between SAT FAM13A expression (lead rs9991328) and multiple GWAS traits: fasting insulin adjusted for BMI, WHRadjBMI, triglycerides, and HDL cholesterol. No comparable colocalizations in VAT, liver, or skeletal muscle.
• PheWAS in UK Biobank (n=337,536) using rs1377290 (proxy for rs9991328, LD R2=1.0) showed associations with increased waist-to-hip ratio and decreased trunk/body fat percentage, mean platelet volume, and BMI (significant at 10% FDR). No other phenome-wide significant associations.
• In METSIM, SAT FAM13A expression (BMI-adjusted) correlated positively with fasting insulin (bicor=0.388, p=5.9e-21) and WHR (bicor=0.453, p=4.2e-19), and negatively with fat mass percentage (bicor=-0.231, p=2.9e-05). Pathways correlated with FAM13A included TCA cycle, lipid metabolism, cell cycle, and Wnt signaling.

Human adipocyte models:

• FAM13A expression increases during SGBS adipocyte differentiation. Knockdown of FAM13A by siRNA or CRISPRi in preadipocytes enhanced early adipogenesis, increasing CEBPA and PPARG expression at Day 5; beige markers (PGC1A, UCP1) were also induced. In mature adipocytes (siRNA at Day 8), FAM13A knockdown showed a trend toward increased basal and insulin-stimulated glucose uptake without significant changes in adipokines or lipolysis.

Mouse phenotyping:

• On chow diet, male KO vs WT showed similar body weight, fasting metabolites, GTT/ITT responses, adipose depot masses, and VAT/SAT ratio. However, SAT showed a shift toward more small adipocytes in KO, with a corresponding modest increase in larger adipocytes in VAT; mean adipocyte diameters were not significantly different (SAT WT 40.4±17.6 µm vs KO 36.1±12.1 µm; VAT WT 51.7±24.7 µm vs KO 56.5±22.8 µm; n=7).
• Under HFD (12–14 weeks), male KO mice gained slightly more weight than WT yet had significantly lower VAT mass and reduced VAT/SAT mass ratio (n=6/group), despite similar fasting metabolites and GTT/ITT responses.

Adipogenesis and glucose uptake in mouse cells:

• SVFs from SAT of KO mice displayed a consistent trend toward enhanced adipogenesis (higher adipogenic marker expression, Oil Red O staining, and triglyceride content) though not always statistically significant, and marginally higher beige marker expression. Newly differentiated KO adipocytes showed a non-significant trend of increased basal and insulin-stimulated glucose uptake; SAT explants from KO exhibited a similar directional increase.

Adipose transcriptomics:

• Across SAT and VAT (male mice, n=32 total), 122 genes were differentially expressed (FDR <10%) between KO and WT, including genes involved in fat cell biology (e.g., Klf14 up 2.3-fold; Agpat2 down to 0.51-fold; Slc7a10 down to 0.65-fold; Vegfa; Celsr2 up 2.14-fold; Fgfr2 down to 0.49-fold). Genes overexpressed in KO were enriched for adipogenesis pathways; underexpressed genes were enriched for NAD+ salvage pathways. In SAT specifically (sex-adjusted analysis), 288 DE genes were identified vs 22 in VAT (FDR <10%), with overrepresentation of fatty acid β-oxidation and TCA cycle pathways in SAT of KO, indicating larger transcriptomic impact in SAT.

Additional observations:

• In WT mice, Fam13a expression decreased in VAT, SAT, and liver in response to HFD. In BTBR ob/ob models, adipose Fam13a expression negatively correlated with obesity and with adipose cell proliferation; KO mice had increased percentages of CD45- SVF subsets (APCs and endothelial cells), and KO APCs tended to differentiate better into adipocytes. Overall, data support that lower Fam13a favors SAT adipogenesis and healthier fat distribution.

The integrated human genetics, cellular, and mouse data indicate that FAM13A regulates adipocyte differentiation and body fat distribution predominantly through effects in subcutaneous adipose tissue. SAT-specific FAM13A eQTLs colocalize with insulin resistance-related traits and associate with a metabolically unhealthy normal-weight phenotype. In human and mouse adipocyte models, lowering FAM13A enhances adipogenesis (including beige-like programs) and tends to improve glucose uptake, suggesting improved adipocyte function. In male mice, Fam13a deficiency under HFD reduces VAT mass and lowers the VAT/SAT ratio despite slightly greater overall weight gain, consistent with a shift of lipid storage toward SAT and away from VAT. Transcriptomic changes in KO SAT further support enhanced adipogenesis and mitochondrial metabolism (β-oxidation, TCA cycle). Collectively, higher FAM13A expression in SAT appears detrimental for healthy adipose expansion, limiting SAT’s capacity to store lipids and potentially diverting lipids to visceral depots. These findings align with the GWAS-based model whereby carriers of risk alleles (higher SAT FAM13A expression) exhibit higher WHR and fasting insulin, and lower fat mass. Potential mechanisms may involve FAM13A’s RhoGAP domain and crosstalk with WNT/β-catenin signaling that inhibits adipogenesis. Sex-specific effects were observed (human GWAS stronger in women; mouse HFD effects prominent in males), highlighting complexity in translating between species and sexes.

This study identifies FAM13A as a regulator of adipocyte differentiation and body fat distribution, acting primarily within subcutaneous adipose tissue. Human genetic analyses show that variants increasing SAT FAM13A expression colocalize with insulin resistance-related traits and unfavorable fat distribution. Functional perturbations demonstrate that reducing FAM13A promotes adipogenesis and trends toward improved glucose handling in adipocytes, while Fam13a knockout in mice lowers VAT/SAT ratio under HFD and induces SAT gene programs for adipogenesis and mitochondrial metabolism. These findings suggest that elevated FAM13A expression impairs healthy SAT expansion and contributes to a lipodystrophy-like fat distribution. Future work should elucidate the molecular mechanisms (e.g., RhoGAP, WNT/β-catenin pathways), determine causal effects with adipose depot–specific knockouts, and explore therapeutic modulation of FAM13A to favor healthier fat distribution and metabolic outcomes.

• The whole-body Fam13a knockout produced subtle metabolic phenotypes overall; depot- and cell type–specific contributions cannot be definitively assigned without adipose-specific (and depot-specific) knockouts.
• Some observed trends (e.g., enhanced adipogenesis and glucose uptake in mouse SVFs) did not reach statistical significance, limiting conclusions about effect sizes.
• Sex dimorphism was evident: key in vivo fat distribution effects under HFD were observed in male mice, with minimal changes in females, complicating generalization.
• Differences between rodent and human adipose depot anatomy and function limit translational inference.
• Discrepancies between this and other studies (e.g., insulin sensitivity outcomes) may reflect variations in mouse sex, diet composition, duration, and age at HFD initiation; standardized conditions across studies are needed.
• The mechanistic link between FAM13A and adipogenesis (e.g., involvement of RhoGAP activity or WNT signaling) remains to be fully elucidated.