AL amyloidosis: untangling new therapies

Systemic light chain (AL) amyloidosis is a protein misfolding disorder characterized by the deposition of abnormal immunoglobulin light chains in fibrillary aggregates, resulting in end-organ damage. Several unique challenges face treating physicians, including delayed diagnosis, advanced vital organ involvement, and morbidity with treatment. Aggressive supportive care and risk-adapted application of plasma cell–directed therapies are the cornerstones of management. The therapeutic revolution in multiple myeloma will likely further expand the arsenal against plasma cells. Careful investigation of these agents will be critical to establish their role in this fragile population. The promise of fibril-directed therapies to restore organ function remains despite early disappointments. In this review, we discuss new therapies to tackle AL amyloidosis using a case-based approach.

Free Immunoglobulin Light Chains in Patients with Tick-Borne Encephalitis: Before and after Treatment

Background: Tick-borne encephalitis (TBE) is inflammation of the central nervous system (CNS) caused by a viral infection which may be associated with increased synthesis of immunoglobulins. It can lead to inter alia, breakdown of the blood-brain barrier (BBB), or even death and, unfortunately, treatment is only symptomatic. Therefore, the aim of the present study was assessment of the concentrations of free light chains (FLC) kappa (κ) and lambda (λ in the cerebrospinal fluid (CSF) and serum of patients with TBE. Methods: A total of 58 cerebrospinal fluid and serum sample pairs were analyzed. Samples were collected from patients with TBE before and after treatment. FLC were measured using the turbidimetric method. The values of κIgG-index, λIgG-index, κFLC-index and λFLC-index were calculated using relevant formulas. Results: Pre-treatment serum λFLC concentrations were higher in comparison to post-treatment levels. Moreover, it was observed that CSF λFLC, TBEV IgM, TBEV IgG, and serum TBEV IgG, as well as the values of λFLC-index, κFLC-index, and λIgG-index were elevated after treatment. In the total study group, the concentrations of CSF κFLC and λFLC, and values of four indexes: κFLC-index, λFLC-index, κIgG-index, and λIgG-index correlated with each other and with CSF TBEV IgM and IgG antibodies. The CSF level of TBEV IgG was also associated with serum IgG TBEV and CSF IgM TBEV antibodies. Additionally, serum κFLC correlated with serum and CSF λFLC. Conclusion: This is the first study that demonstrates statistically significant differences in serum and CSF λFLC, as well as in the calculated values of three algorithms: λIgG-index, κFLC-index, and λIgG-index prior to and following treatment of TBE. Our findings may indicate that these differences reflect the intrathecal synthesis of immunoglobulins and increased permeability of BBB in patients with TBE. Moreover, it could provide the basis for developing new therapeutic strategies.

Universal amyloidogenicity of patient-derived immunoglobulin light chains

The deposition of immunoglobulin light chains (IgLCs) in the form of amorphous aggregates or amyloid fibrils in different tissues of patients can lead to severe and potentially fatal organ damage, requiring transplantation in some cases. There has been great interest in recent years to elucidate the origin of the very different in vivo solubilities of IgLCs, as well as the molecular determinants that drive either the formation of ordered amyloid fibrils or disordered amorphous aggregates. It is commonly thought that the reason of this differential aggregation behaviour is to be found in the amino acid sequences of the respective IgLCs, i.e. that some sequences display higher intrinsic tendencies to form amyloid fibrils. Here we perform in depth Thermodynamic and Aggregation Fingerprinting (ThAgg-Fip) of 9 multiple myeloma patient-derived IgLCs, the amino acid sequences of all of which we have solved by de novo protein sequencing with mass spectrometry. The latter technique was also used for one IgLc from a patient with AL amyloidosis. We find that all samples also contain proteases that fragment the proteins under physiologically relevant mildly acidic pH conditions, leading to amyloid fibril formation in all cases. Our results suggest that while every pathogenic IgLC has a unique ThAgg fingerprint, all sequences have comparable amyloidogenic potential. Therefore, extrinsic factors, in particular presence of, and susceptibility to, proteolytic cleavage is likely to be a strong determinant of in vivo aggregation behaviour. The important conclusion, which is corroborated by systematic analysis of our sequences, as well as many sequences of IgLCs from amyloidosis patients reported in the literature, challenges the current paradigm of the link between sequence and amyloid fibril formation of pathogenic light chains.

De Novo Sequencing of Antibody Light Chain Proteoforms from Patients with Multiple Myeloma

<p>In multiple myeloma diseases, monoclonal immunoglobulin light chains (LC) are abundantly produced, with the consequence in some cases to form deposits affecting various organs, such as kidney, while in other cases to remain soluble up to concentrations of several g.L^-1 in plasma. The exact factors crucial for the solubility of light chains are poorly understood, but it can be hypothesized that their amino acid sequence plays an important role. Determining the precise sequences of patient-derived light chains is therefore highly desirable. We establish here a novel <i>de novo</i> sequencing workflow for patient-derived LCs, based on the combination of bottom-up and top-down proteomics without database search. This pipeline is then used for the complete <i>de novo</i> sequencing of LCs extracted from the urine of 10 patients with multiple myeloma. We show that for the bottom-up part, digestions with trypsin and Nepenthes fluid extract are sufficient to produce overlapping peptides able to generate the best sequence candidates. For the sequencing of intact LC proteoforms, combining activation methods is key to achieve single amino acid resolution.</p>

De Novo Sequencing of Antibody Light Chain Proteoforms from Patients with Multiple Myeloma

<p>In multiple myeloma diseases, monoclonal immunoglobulin light chains (LC) are abundantly produced, with the consequence in some cases to form deposits affecting various organs, such as kidney, while in other cases to remain soluble up to concentrations of several g.L^-1 in plasma. The exact factors crucial for the solubility of light chains are poorly understood, but it can be hypothesized that their amino acid sequence plays an important role. Determining the precise sequences of patient-derived light chains is therefore highly desirable. We establish here a novel <i>de novo</i> sequencing workflow for patient-derived LCs, based on the combination of bottom-up and top-down proteomics without database search. This pipeline is then used for the complete <i>de novo</i> sequencing of LCs extracted from the urine of 10 patients with multiple myeloma. We show that for the bottom-up part, digestions with trypsin and Nepenthes fluid extract are sufficient to produce overlapping peptides able to generate the best sequence candidates. For the sequencing of intact LC proteoforms, combining activation methods is key to achieve single amino acid resolution.</p>

Alteration of the Gut Microbiome in Chronic Kidney Disease Patients and Its Association With Serum Free Immunoglobulin Light Chains

ObjectivesGut dysbiosis is associated with chronic kidney disease (CKD), and serum free immunoglobulin light chains (FLCs) are biomarkers for CKD. This study aims to assess the CKD gut microbiome and to determine its impact on serum FLC levels.MethodsTo control for confounders, 100 patients and sex- and age-matched healthy controls (HCs) were recruited. The gut microbiome was assessed by sequencing 16S rRNA gene V3-V4 hypervariable regions. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States was applied to infer functional metabolic pathways. When observing group differences in the microbiome and predicted metabolic pathways, demographic confounders were adjusted using binary logistic regression; when examining impacts of the gut microbiome and metabolic pathways on serum FLCs, factors influencing FLC levels were adjusted using multiple regression.ResultsPrincipal coordinate analysis revealed a significantly different bacterial community between the CKD and HC groups (P &lt; 0.05). After adjusting for confounders, lower Chao 1, observed species and Shannon indices based on binary logistic regression predicted CKD prevalence. Actinobacteria, Alistipes, Bifidobacterium and Bifidobacterium longum enrichment, upregulation of metabolic pathways of bacterial toxin, chloroalkane and chloroalkene degradation, and Staphylococcus aureus infection also predicted CKD prevalence (P &lt; 0.05). Furthermore, depletion of Actinobacteria and Bifidobacterium and reduced chloroalkane and chloroalkene degradation predicted high levels of FLC λ (P &lt; 0.05).ConclusionsGut dysbiosis in CKD patients was confirmed by controlling for confounders in the present study. Additionally, the association between gut dysbiosis and FLC λ levels demonstrates the existence of crosstalk between the microbiome and immune response in CKD.