Nasim Wiegley’s research while affiliated with University of California, Davis and other places

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Publications (33)


CTLA-4 Haploinsufficiency Presenting with IgA Nephropathy: TH-PO708
  • Poster

October 2024

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1 Read

Journal of the American Society of Nephrology

Andrea Broka

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Brian Y. Young

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Hiba Hamdan

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[...]

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Nasim Wiegley






Representative multiplexed immunofluorescence image showing protein expression in a kidney section with DKD. (a) A human kidney cortical tissue section from a patient with DKDIIB, showing the basement membrane (collagen IV, white), macrophages (CD68, purple), broad immune cells (CD45, yellow), smooth muscle and interstitial cells (αSMA, red), glomerular endothelial and peritubular capillary cells (CCR6, orange), all tubules (CXCR3, turquoise) and the distal nephron (MUC1, green). The scale bar below the image represents 500 μm. (b, c) Two zoomed-in regions from this sample show areas with increased immune cells and fibrosis (b), and a blood vessel and glomerular compartments (c). The scale bars below the images in (b) and (c) represent 100 μm. (d–i) Nestin (red), CCR6 (orange) (d), αSMA (red) (e), CD45 (yellow) (f), CXCR3 (turquoise), MUC1 (green) (g), collagen IV (white) (h) and CD68 (purple) (i) highlight podocytes, GEC, blood vessels, inflammatory cells, all tubules, the distal nephron, basement membrane and macrophages, respectively. COL4, collagen IV; C1QC, complement C1q C chain; EpCAM, epithelial cell adhesion molecule; MUC1, mucin 1, also known as CD227; SPP1, secreted phosphoprotein 1, also known as osteopontin (OPN); TFAM, transcription factor A, mitochondrial; vWF, von Willebrand factor
Classification of kidney cell types and tissue compartments. (a) Heatmap of protein expression by phenotype showing unique expression profiles for the cell populations identified in this study, as well as the low-expressing cells. (b) A uniform manifold approximation and projection (UMAP) representation of all cells in the study, coloured by cell type. (c) A Voronoi representation of cortical sections from a healthy kidney sample and one from a donor with DKDIIA–B, coloured by cell type (top panels), compared with expression of compartment-identifying proteins in the same tissue sections (bottom panels). ‘R’ denotes the region number, e.g. 1-R1 for region (section) 1 from individual 1. (d) Cell types identified from unsupervised clustering were validated by overlaying cell annotations (white dots) with cell type-specific marker protein channels. BM, bone marrow; COLIV, collagen IV; C1QC, complement C1q C chain; DM, diabetes mellitus; DN, distal nephron; EC, endothelial cell; EpCAM, epithelial cell adhesion molecule; LAMP, lysosome-associated membrane protein; MUC1, mucin 1, also known as CD227; OPN, osteopontin; PT, proximal tubule; PTC, peritubular capillary endothelial cell; TFAM, transcription factor A, mitochondrial; TM, thrombomodulin; vWF, von Willebrand factor
Global and compartment-wise changes in cell-type proportions and protein expression from diabetes to DKD. (a) Bar graph of cell frequency showing global change in fraction of cell types when the data are aggregated by DKD class. (b) Compartment-wise change in the distribution of cellular composition in glomeruli, proximal tubules, distal nephron, blood vessels, interstitium and basement membrane with DKD progression. Sections of the bars from top to bottom correspond to the cell types/segments depicted in the legend from left to right. (c) Hierarchical clustering based on cell-type frequency in the cortical tissue sections, where the columns represent cell types identified from unsupervised clustering, and the rows represent individual tissue sections. Cell-type frequencies are represented as z scores per column (cell type) and values are normalised by column. The heatmap shows coarse segregation of cortical sections from people with diabetes mellitus and DKD, but with overlap between classes. (d) Volcano plot of cell-type frequency showing enrichment of all inflammatory cell types in DKD, compared with healthy kidneys, with significant increases in CD11b⁺ and CD45⁺ cells after Bonferroni adjustment for multiple testing. (e) Boxplots of cell-type frequency, grouped by DKD class, showing that the increase in immune cells is continuous from diabetes mellitus to DKDIII. Each dot represents a single individual within each DKD class. COL4, collagen IV; DM, diabetes mellitus; PTC, peritubular capillary endothelial cell
Representative multiplex immunofluorescence images showing protein expression across the spectrum from healthy kidneys to progressive DKD. (a) Staining for basement membrane (collagen IV, red), broad inflammatory cells (CD45⁺, yellow) and macrophages (CD68⁺, blue) shows that disease progression, manifested by basement membrane (collagen IV) thickening, is patchy. In addition, inflammatory cells, including macrophages, coincide with areas of greater collagen IV deposition. (b) The expression of compartment-identifying proteins (CXCR3, turquoise; CCR6, orange; MUC1, green; collagen IV, white; αSMA, red) differs between DKD classes. The scale bars represents 250 μm. DM, diabetes mellitus
DKD is patchy. (a) Representative multiplex immunofluorescence images showing DKD heterogeneity (sample 10-R1, right) in terms of alteration of protein expression compared with normal tissue (sample 4-R1, left); ‘R’ denotes the region number, e.g. 4-R1 for region (section) 1 from individual 4; scale bar, 250 μm. Regions with variable DKD severity are manually outlined. (b) Multidimensional scaling (MDS) plot of 20 cortical sections (omitting the three medullary sections), coloured by disease class, as well as the three manually outlined sub-regions. (c) Representative images of manually outlined glomeruli in two DKDIIB sections from patients 10 and 11. (d) Boxplot comparing normalised CCR6 expression in glomeruli from the two sections. Each dot represents CCR6 expression in a single outlined glomerulus. C1QC, complement C1q C chain; DM, diabetes mellitus; EpCAM, epithelial cell adhesion molecule; SPP1, secreted phosphoprotein 1, also known as osteopontin (OPN); TFAM, transcription factor A, mitochondrial; vWF, von Willebrand factor

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Spatial proteomics of human diabetic kidney disease, from health to class III
  • Article
  • Publisher preview available

July 2024

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67 Reads

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3 Citations

Diabetologia

Aims/hypothesis Diabetic kidney disease (DKD) is the leading cause of chronic and end-stage kidney disease in the USA and worldwide. Animal models have taught us much about DKD mechanisms, but translation of this knowledge into treatments for human disease has been slowed by the lag in our molecular understanding of human DKD. Methods Using our Spatial TissuE Proteomics (STEP) pipeline (comprising curated human kidney tissues, multiplexed immunofluorescence and powerful analysis tools), we imaged and analysed the expression of 21 proteins in 23 tissue sections from individuals with diabetes and healthy kidneys (n=5), compared to those with DKDIIA, IIA-B and IIB (n=2 each) and DKDIII (n=1). Results These analyses revealed the existence of 11 cellular clusters (kidney compartments/cell types): podocytes, glomerular endothelial cells, proximal tubules, distal nephron, peritubular capillaries, blood vessels (endothelial cells and vascular smooth muscle cells), macrophages, myeloid cells, other CD45⁺ inflammatory cells, basement membrane and the interstitium. DKD progression was associated with co-localised increases in inflammatory cells and collagen IV deposition, with concomitant loss of native proteins of each nephron segment. Cell-type frequency and neighbourhood analyses highlighted a significant increase in inflammatory cells and their adjacency to tubular and αSMA⁺ (α-smooth muscle actin-positive) cells in DKD. Finally, DKD progression showed marked regional variability within single tissue sections, as well as inter-individual variability within each DKD class. Conclusions/interpretation Using the STEP pipeline, we found alterations in protein expression, cellular phenotypic composition and microenvironment structure with DKD progression, demonstrating the power of this pipeline to reveal the pathophysiology of human DKD. Graphical Abstract

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Figure 1: Pathophysiological mechanisms of membranous nephropathy. Bregs: Regulatory B-cells, GBM: Glomerular basement membrane, Tfh: Follicular T helper cells, Th2: T helper 2, Th 17: T helper 17, Treg: Regulatory T-cells.
Figure 2: Timeline of identification of target antigens in membranous nephropathy. BSA: Bovine serum albumin, CD206: Cluster of differentiation 206, CNTN1: Contactin 1, EEA1: Early endosome antigen 1, EXT1/EXT2: Exostosin 1/2 complex, FAT1: Protocadherin FAT1, FCN3: Ficolin 3, HTRA1: Serine protease HTRA1, MST1: Macrophage stimulating 1, NCAM1: Neural cell adhesion molecule 1, NDNF: Neuron-derived neurotrophic factor, NELL-1: Neural epidermal growth factor-like 1, NPR3: Natriuretic peptide receptor 3, NTNG1: Netrin G1, PCDH7: Protocadherin 7, PCSK6: Proprotein convertase subtilisin/kexin type 6, PLA2R: Phospholipase A2 receptor, Sema3B: Semaphorin 3B, SEZ6L2: Seizure-related 6 homolog like 2, TGFBR3: Type III transforming growth factor-beta receptor, THSD7A: Thrombospondin type 1 domain-containing 7A, VASN: Vasorin.
Figure 3: Etiological association of target antigens in membranous nephropathy. CDIP: Chronic inflammatory demyelinating polyneuropathy, HSCT: Hematopoietic stem cell transplant, BSA: bovine serum albumin; CNTN1: contactin 1; EXT1/EXT2: exostosin 1/2 complex; FAT1: protocadherin FAT1; NCAM1: neural cell adhesion molecule 1; NDNF: neuron-derived neurotrophic factor; NELL-1: neural epidermal growth factor-like 1; PCDH7: protocadherin 7; PCSK6: proprotein convertase subtilisin/kexin type 6; PLA2R: phospholipase A2 receptor; Sema3B: semaphorin 3B; TGFBR3: type III transforming growth factor-beta receptor; THSD7A: thrombospondin type 1 domain-containing 7A, NSAID: Non-steroidal anti-inflammatory drug.
Figure 5: Risk stratification and treatment options in membranous nephropathy. Modified from KDIGO 2021 Glomerular Disease Guideline. 73 CNI: Calcineurin inhibitor, CYC: Cyclophosphamide, eGFR: Estimated glomerular filtration rate, PLA2R: phospholipase A2 receptor; IgG: immunoglobulin G. *Calculated by clearance of IgG/clearance of albumin.
An Updated Review of Membranous Nephropathy

April 2024

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582 Reads

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3 Citations

Indian Journal of Nephrology

Membranous nephropathy (MN) is one of the most common causes of nephrotic syndrome in adults. The discovery of phospholipase A2 receptor (PLA2R) as a target antigen has led to a paradigm shift in the understanding and management of MN. At present, serum PLA2R antibodies are used for diagnosis, prognostication, and guiding treatment. Now, with the discovery of more than 20 novel target antigens, antigen mapping is almost complete. The clinical association of certain antigens provides clues for clinicians, such as the association of nerve epidermal growth factor-like 1 with malignancies and indigenous medicines. Serum antibodies are detected for most target antigens, except exostosin 1 and 2 and transforming growth factor-beta receptor 3, but their clinical utility is yet to be defined. Genome-wide association studies and studies investigating environmental factors, such as air pollution, shed more light on the underpinnings of MN. The standard therapy of MN diversified from cyclical cyclophosphamide and steroids to include rituximab and calcineurin inhibitors over the past decades. Here, we provide a cutting-edge review of MN, focusing on genetics, immune system and environmental factors, novel target antigens and their clinical characteristics, and currently available and emerging novel therapies in MN.


Figure 1. Summary of clinicopathological classification of focal segmental glomerulosclerosis (FSGS) based on the underlying cause. Created using biorender.com.
Figure 2. An algorithmic approach to genetic testing in patients with focal segmental glomerulosclerosis (FSGS). Created using biorender.com.
Figure 3. Implications of genetic testing in adults with focal segmental glomerulosclerosis (FSGS). Created using biorender. com.
A Review of Focal Segmental Glomerulosclerosis Classification With a Focus on Genetic Associations

April 2024

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44 Reads

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5 Citations

Kidney Medicine

Focal segmental glomerulosclerosis (FSGS) defines a distinct histologic pattern observed in kidney tissue that is linked to several distinct underlying causes, all converging on the common factor of podocyte injury. It presents a considerable challenge in terms of classification because of its varied underlying causes and the limited correlation between histopathology and clinical outcomes. Critically, precise nomenclature is key to describe and delineate the pathogenesis, subsequently guiding the selection of suitable and precision therapies. A proposed pathomechanism-based approach has been suggested for FSGS classification. This approach differentiates among primary, secondary, genetic, and undetermined causes, aiming to provide clarity. Genetic FSGS from monogenic mutations can emerge during childhood or adulthood, and it is advisable to conduct genetic testing in cases in which there is a family history of chronic kidney disease, nephrotic syndrome, or resistance to treatment. Genome-wide association studies have identified several genetic risk variants, such as those in apolipoprotein L1 (APOL1), that play a role in the development of FSGS. Currently, no specific treatments have been approved to treat genetic FSGS; however, interventions targeting underlying cofactor deficiencies have shown potential in some cases. Furthermore, encouraging results have emerged from a phase 2 trial investigating inaxaplin, a novel small molecule APOL1 channel inhibitor, in APOL1-associated FSGS.


Citations (10)


... Lupus nephritis is another significant kidney complication, occurring in approximately 60% of patients with systemic lupus erythematosus [5]. Collectively, all forms of kidney diseases are considered life-threatening, with poor diagnosis and ineffective therapies contributing to increased mortality and morbidity each year. ...

Reference:

Acyl-CoA Synthetase Long-Chain Isoenzymes in Kidney Diseases: Mechanistic Insights and Therapeutic Implications
A Comprehensive and Practical Approach to the Management of Lupus Nephritis in the Current Era
  • Citing Article
  • May 2024

Advances in Kidney Disease and Health

... Focal segmental glomerulosclerosis (FSGS) is a significant cause of nephrotic syndrome, particularly in adults [1,2]. It is characterized by segmental scarring of the glomeruli, leading to proteinuria and progressive loss of kidney function [3]. FSGS can arise primarily (idiopathic) or secondarily due to underlying conditions such as obesity, diabetes, infections, or nephrotoxic drugs [4]. ...

A Review of Focal Segmental Glomerulosclerosis Classification With a Focus on Genetic Associations

Kidney Medicine

... LN is a form of glomerulonephritis with deposition of immune complexes (ICs) and complement, which results in renal tissue damage in the kidneys of LN patients, endothelial damage, and microthrombi formation [17]. Although renal biopsy has long been considered the "gold standard" for diagnosis of LN [18], its invasive nature and limited scope of renal tissue analysis warrant a more advanced approach. The need for non-invasive and sensitive diagnostic and prognostic methods is evident. ...

Kidney Biopsy in Management of Lupus Nephritis: A Case-Based Narrative Review

Kidney Medicine

... Lupus nephritis (LN) is a glomerulonephritis arising from Systemic Lupus Erythematosus, a chronic autoimmune disease in which women of childbearing age are particularly implicated. In pregnancy, the disease results in increased risk to maternal health, including pre-eclampsia, hypertension, and thromboembolic events, as well as fetal risks, such as preterm birth, congenital heart block, and intrauterine growth restriction (11). Therefore, management of pregnancy in lupus nephritis patients requires careful planning and thorough monitoring for possible complications. ...

Approach to Pregnancy in Lupus Nephritis

Kidney Medicine

... [78] In addition, Flohr also gave insights into very promising ongoing clinical investigations of iptacopan for the treatment of kidney diseases such as IgA nephropathy (IgAN), [77c] C3 glomerulopathy (C3G), [77d] and Lupus Nephritis. [79] This further underlines the outstanding and pioneering work of the Novartis team, which made the therapeutic potential of FB inhibitors accessible to patients in various indications. ...

Novel Therapeutics for Management of Lupus Nephritis: What Is Next?

Kidney Medicine

... To examine the ability of SCGP to recognize known tissue structures, we assessed its performance on a cohort of 17 tissue sections from 12 individuals with diabetes and various stages of diabetic kidney disease (DKD). 40 Tissue samples were imaged using the mIF platform CODEX 9 and further annotated for four major kidney compartments: glomeruli, blood vessels, distal tubules, and proximal tubules. This cohort will be referred to as the DKD Kidney dataset (STAR Methods) in the subsequent text. ...

Spatial proteomics of human diabetic kidney disease, from health to class III

... These unexpected findings associated with SGLT2i and CV health were discovered after the US Food and Drug Administration (FDA) required evidence of CV safety involving the intake of new hypoglycemic agents [4][5][6][7][8][9]. Additionally, some evidence has also been attributed to them as likely retinal protective agents [10] and may also offer renal protection [11], thus placing them into a category of pleiotropic agents, as some authors say [12,13]. ...

SGLT2 Inhibitors and CKD: Are You a #Flozinator?

Kidney Medicine

... In 2021, Inker et al. developed two equations, namely CKD-EPI creatinine 2021 and CKD-EPI creatinine cystatin C 2021, which omit race and improve the accuracy of kidney function assessment [16]. Goodson et al. [28] evaluated the eGFR in 637 potential living kidney donors, comparing the accuracy of the MDRD formulas and CKD-EPI creatinine 2009 and CKD-EPI creatinine 2021 formulas with the mGFR assessed using iohexol. The results showed that the value calculated using the CKD-EPI creatinine 2021 formula was less biased and more accurate than those derived from previous creatinine-based estimated GFR equations, with a P30 value of 96.4% in Asian individuals. ...

GFR Estimation in Potential Living Kidney Donors: Race- and Nonrace-based Equations and Measured GFR

Kidney Medicine

... infection. The reason for this is unclear, but the urinary flow elevation related to the osmotic diuresis and natriuresis effects of SGLT2i may be a factor [11,27]. On the other hand, although a potential association of SGLT2i with musculoskeletal pain such as myopathy is a concern [14,15], our results did not show such an association. ...

Sodium-Glucose Cotransporter 2 Inhibitors and Urinary Tract Infection: Is There Room for Real Concern?
  • Citing Article
  • September 2022

Kidney360

... In kidney transplant recipients, BK virus causes nephropathy and urologic complications, such as hemorrhagic cystitis or ureteral stenosis. JC virus is known to cause progressive multifocal leukoencephalopathy (PML) in HIV patients, but its involvement in polyomavirus allograft nephropathy (PVAN) is rare [2]. Here we describe two cases of JC-related nephropathy occurring late after kidney transplantation and provide a review of the literature. ...

Clinicopathologic Characteristics of JC Virus Nephropathy in Kidney Transplant Recipients
  • Citing Article
  • June 2020

Transplantation