**Author Listing - Lead/ Submitting Author (we will be communicating with this individual): Name, Institution, City and State where the work was done. Co-authors will be added in a separate section.**
Alice Nevone
Department of Molecular Medicine, University of Pavia, Amyloidosis Research and Treatment Center, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

**Main Body of the Abstract**
N-glycosylation of monoclonal light chains (LCs) is a risk factor for MGUS progression, particularly towards AL amyloidosis. We have recently reported that N-glycosylation of κ clonal LCs within the DE loop of framework region 3 (FR3-DE) is significantly associated with AL amyloidosis. This observation might refine current amyloidogenicity prediction tools, possibly facilitating early diagnosis.
Having encountered rare cases where the widely employed prediction tool NetNGlyc failed to detect an N-glycosylation site, we benchmarked available N-glycosylation prediction tools for their ability to identify N-glycosylation in clonal LCs.
Through a systematic research, we identified all currently available, sequence-based N-glycosylation prediction tools (n=7). We analyzed a cohort of 147 patients with monoclonal gammopathy (n=123 AL, n=1 MGUS, n=23 MM): clonal LCs were sequenced through SMaRT M-Seq, N-glycosylation was predicted in silico with all available tools and the N-glycosylation status was verified biochemically through Western blotting on urine samples.
Overall, N-glycosylation prediction accuracy ranged from 95.2% to 98.6%, with 4 tools displaying the highest accuracy level.
Then, using published and new AL and non-AL clonal κ LC sequences and considering the presence of an N-glycosylation site anywhere or within FR3-DE as a risk factor for AL, we confirmed that the spatial knowledge of the putative N-glycosylation site significantly increases the ability to detect amyloidogenic LCs, in terms of positive predictive value and Matthew Correlation Coefficient.
Overall, these data reinforce the notion that the N-glycosylation hotspot of clonal κ LCs is associated with AL amyloidosis and could help identifying pathogenic LCs through sequence-based prediction tools.



**Author Listing - Lead/ Submitting Author (we will be communicating with this individual): Name, Institution, City and State where the work was done. Co-authors will be added in a separate section.**
Alice Nevone
Department of Molecular Medicine, University of Pavia, Amyloidosis Research and Treatment Center, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

**Main Body of the Abstract**
N-glycosylation of monoclonal light chains (LCs) is a risk factor for MGUS progression, particularly towards AL amyloidosis. We have recently reported that N-glycosylation of κ clonal LCs within the DE loop of framework region 3 (FR3-DE) is significantly associated with AL amyloidosis. This observation might refine current amyloidogenicity prediction tools, possibly facilitating early diagnosis.
Having encountered rare cases where the widely employed prediction tool NetNGlyc failed to detect an N-glycosylation site, we benchmarked available N-glycosylation prediction tools for their ability to identify N-glycosylation in clonal LCs.
Through a systematic research, we identified all currently available, sequence-based N-glycosylation prediction tools (n=7). We analyzed a cohort of 147 patients with monoclonal gammopathy (n=123 AL, n=1 MGUS, n=23 MM): clonal LCs were sequenced through SMaRT M-Seq, N-glycosylation was predicted _in silico_ with all available tools and the N-glycosylation status was verified biochemically through Western blotting on urine samples.
Overall, N-glycosylation prediction accuracy ranged from 95.2% to 98.6%, with 4 tools displaying the highest accuracy level.
Then, using published and new AL and non-AL clonal κ LC sequences and considering the presence of an N-glycosylation site anywhere or within FR3-DE as a risk factor for AL, we confirmed that the spatial knowledge of the putative N-glycosylation site significantly increases the ability to detect amyloidogenic LCs, in terms of positive predictive value and Matthew Correlation Coefficient.
Overall, these data reinforce the notion that the N-glycosylation hotspot of clonal κ LCs is associated with AL amyloidosis and could help identifying pathogenic LCs through sequence-based prediction tools.



N-glycosylation of clonal immunoglobulin light chains as a risk factor for AL amyloidosis: Benchmarking N-glycosylation prediction tools PA45 (#463)

We invite you to attend the XIX International Symposium on Amyloidosis to be held in Rochester, MN.

This symposium is organized as a hybrid meeting (with the focus on in-person) held from Sunday, May 26 through Thursday, May 30, 2024.

Together with the ISA Board and members of Mayo Clinic, a very attractive scientific hybrid program is being planned. The program will cover a variety of types of systemic amyloidosis: ATTR (hereditary and wild-type), AL (light-chain), AA and less frequent forms. There will be key lectures, specific symposia including those company sponsored, oral presentations and poster sessions of accepted abstracts.

COURSE DESCRIPTION
This program will provide a comprehensive review of state-of-the-art education in systemic amyloidosis: basic science, pathophysiology, diagnosis, current and emerging treatments. Scientific presentations will include competitive oral and poster abstracts. The rapid evolution of scientific discovery and expanding treatment options has created tremendous interest in the field and this meeting will fill and important gap in educating scientists and clinicians.