Acsl1 mediated FA Synthesis Impairs Osseointegration in type I diabetes

Diabetes mellitus is considered a relative contraindication for oral implant therapy, as hyperglycemia frequently precipitates vascular and osseous pathologies. Although clinicians routinely prioritize glycemic control before initiating implant-related treatment plans, diabetic patients often exhibit impaired osseointegration. However, the specific mechanisms remain to be elucidated. Emerging evidence suggests that this refractory bone loss is mediated by trained immunity, a process in which innate immune cells retain an epigenetic memory of prior inflammatory stimuli and mount an exaggerated response upon secondary challenge such as the invasive implantation process or inflammatory insult. Here, integrating RNA-seq, metabolomics, and ATAC-seq analyses, we demonstrate that stringent glycemic control in type I diabetes fails to normalize fatty-acid biosynthetic process, which remain persistently activated and potentiate macrophage-mediated inflammation and osteoclastogenesis when experiencing the secondary challenge. Mechanistically, prior hyperglycemic exposure enhances chromatin accessibility and sustaining Acsl1 transcription by H3K4me1 epigenetic modification at the Acsl1 locus in macrophages. This epigenetic imprint augments fatty-acid anabolism, amplifies pro-inflammatory cytokine production, and accelerates osteoclastic differentiation, ultimately compromising osseous repair. Collectively, our findings reveal that diabetes-induced H3K4me1 modification at Acsl1 drives metabolic reprogramming underpinning trained immunity and consequent bone damage. Targeting H3K4me1 or Acsl1 therefore represents a promising therapeutic strategy to improve implant osseointegration and skeletal regeneration in diabetic patients. Overall design: This in vitro model was adapted from Edgar et al.(Edgar et al. 2021) to mimic diabetic-trained and untrained BMDM states. Male C57BL/6J mice (8 weeks old) from the Laboratory Animal Center of National Bioindustry (Chongqing, China) were randomly allocated to control or diabetic groups. For diabetes induction, mice received low-dose streptozotocin (42-45 mg/kg/d; Solarbio, China) via intraperitoneal injection after a 12h fast, repeated daily for 5 days. One week post-final injection, mice with nonfasted blood glucose >16.9 mmol/L were deemed type 1 diabetic. After 6 weeks of hyperglycemia, bone marrow progenitors from both groups were isolated and cultured in 5 mmol/L glucose DMEM with recombinant murine M-CSF for 7 days (rest phase). RNA samples were thermally denatured and mRNA enriched using oligo (dT) beads. The mRNA was fragmented, followed by synthesis of first- and second-strand cDNA. The cDNA ends were repaired, adenine bases added, and adapters ligated. PCR amplification was then performed. The sequencing library was quality checked, and the PCR product was denatured and circularized, with linear DNA digested. Finally, rolling circle replication generated DNA nanoballs (DNBs) for sequencing using combinatorial probe-anchor synthesis (cPAS) technology on a high-density nanochip. The raw data were processed with SOAPnuke (version 1.5.6) to filter out sequences. This step eliminated reads that included adapter sequences, indicating contamination, as well as those with more than 5% unknown base 'N' content or that were low-quality quality (defined as reads with more than 20% of their total bases having quality values below 15). The result of this filtering process was clean data. The clean data were aligned to the reference genome (https://hgdownload.soe.ucsc.edu/goldenPath/mm10/) using HISTA2 software (v2.1.0). Subsequently, gene fusion detection was performed using Ericscript (v0.5.5), and alternative splicing and differential alternative splicing analysis were conducted using rMATS (V3.2.5). Differential gene expression analysis was conducted using limma (v3.66.0) with the criteria of P value < 0.05. KEGG and GO enrichment analysis were performed using DAVID functional annotation clustering tool (https://david.ncifcrf.gov/summary.jsp).