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Background <p>Methylation capture sequencing (MC-seq), which relies on next-generation sequencing technology, offers advantages over the widely used array-based approach that Illumina Inc. developed regarding both resolution and comprehensiveness for detecting DNA methylation changes across genomes. In the present study, MC-seq was employed for the first time to identify DNA methylation markers for Alzheimer’s disease (AD).</p> Results <p>We compared DNA methylation in the blood of 12 AD patients with brain amyloidosis and 12 cognitively normal elderly Japanese individuals without brain amyloidosis. Candidate methylation differences were validated in the two cohorts using bisulfite amplicon sequencing. Significant differentially methylated regions were identified in the <i>ANKH</i>, <i>MARS</i>, <i>ANKFY1</i>, <i>LINC00908</i>, and <i>KLF2</i> genes and a slight methylation change in <i>CHRNE</i> (<i>p</i> = 0.061). Furthermore, our AD diagnostic prediction model showed that combining the methylation levels of <i>ANKH</i> and <i>MARS</i> with the <i>APOE</i> genotype provided diagnostic accuracy, achieving AUCs of 0.90 and 0.81 in the discovery and validation datasets, respectively.</p> Conclusions <p>The present results suggest the potential of combining these markers for diagnosing AD and support the validity of our approach for identifying disease-related DNA methylation markers using next-generation sequencing.</p>

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Identification of diagnostic DNA methylation markers in the blood of Japanese Alzheimer’s disease patients using methylation capture sequencing

  • 期刊论文

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  • 发表日期：

    2025年6月20日

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  • Risa Mitsumori,
  • Kayoko Sawamura,
  • Kimi Yamakoshi,
  • Akinori Nakamura,
  • Yutaka Arahata,
  • Shumpei Niida,
  • Daichi Shigemizu,
  • Kouichi Ozaki,
  • Nobuyoshi Shimoda

摘要

Background

Methylation capture sequencing (MC-seq), which relies on next-generation sequencing technology, offers advantages over the widely used array-based approach that Illumina Inc. developed regarding both resolution and comprehensiveness for detecting DNA methylation changes across genomes. In the present study, MC-seq was employed for the first time to identify DNA methylation markers for Alzheimer’s disease (AD).

Results

We compared DNA methylation in the blood of 12 AD patients with brain amyloidosis and 12 cognitively normal elderly Japanese individuals without brain amyloidosis. Candidate methylation differences were validated in the two cohorts using bisulfite amplicon sequencing. Significant differentially methylated regions were identified in the ANKH, MARS, ANKFY1, LINC00908, and KLF2 genes and a slight methylation change in CHRNE (p = 0.061). Furthermore, our AD diagnostic prediction model showed that combining the methylation levels of ANKH and MARS with the APOE genotype provided diagnostic accuracy, achieving AUCs of 0.90 and 0.81 in the discovery and validation datasets, respectively.

Conclusions

The present results suggest the potential of combining these markers for diagnosing AD and support the validity of our approach for identifying disease-related DNA methylation markers using next-generation sequencing.