| Literature DB >> 32079308 |
Sadiq Mu'azu Maifata1,2,3, Rafidah Hod2, Fadhlina Zakaria4, Fauzah Abd Ghani1.
Abstract
Differentiating primary and secondary membranous glomerulonephritis (MGN) using biomarkers for MGN is essential in patients' diagnosis, treatment and follow-up. Although biopsy has been the primary tool in making the diagnosis, not all patients can withstand it due to its invasive nature, and it cannot be used to monitor treatment. Hence, there is the need for less invasive or even non-invasive biomarkers for effective diagnosis, treatment monitoring and prognostication. This study aimed at providing an alternative way of differentiating primary and secondary MGN using enzyme-linked immunosorbent assay (ELISA) technique for serum and urine biomarkers (M-type phospholipase A2 receptor (PLA2R) and thrombospondin type-1 domain-containing 7A (THSD7A)) for prompt diagnosis, treatment and prognosis. A total of 125 subjects, including 81 primary and 44 secondary MGN subjects, were diagnosed from January 2012 to October 2019 at Hospital Serdang and Hospital Kuala Lumpur from which 69 subjects consisting of 45 primary and 24 secondary MGN subjects participated in the study. Of these, 13 primary MGN subjects were positive for both serum and urine anti-PLA2R antibodies (Ab) whereas only one secondary MGN subject associated with hepatitis B virus was positive for both serum and urine anti-PLA2R Ab. At the same time, anti-THSD7A Ab was found positive in four primary MGN subjects and two secondary MGN subjects with malignancy.Entities:
Keywords: M-type phospholipase A2 receptor (PLA2R); membranous glomerulonephritis (MGN); prognostication; thrombospondin domain-containing protein 7A (THSD7A)
Mesh:
Substances:
Year: 2020 PMID: 32079308 PMCID: PMC7072431 DOI: 10.3390/biom10020319
Source DB: PubMed Journal: Biomolecules ISSN: 2218-273X
Figure 1Flow chart of events from ethical approval to data analysis.
Characteristics of subjects at the time of renal biopsy.
| Variable | Primary MGN ( | Secondary MGN ( | ||
|---|---|---|---|---|
|
| ||||
Estimated Glomerular Filtration Rate (eGFR) (high risk ≤ 60 mL/min/1.73m2, low risk ≥ 60 mL/min/1.73m2), Urine creatinine Index (UPCr Index) (normal ≤ 0.03 g/mmol, high ≥ 0.03 g/mmol), Categorical variables were expressed as frequency and percentage.
General characteristics of subjects at the end of the follow-up period.
| Variable | Primary MGN ( | Secondary MGN ( | ||
|---|---|---|---|---|
|
| ||||
|
| 39.0(17.5–59.5) | 27.5(13.0–49.8) | ||
|
| ||||
Categorical variables were expressed as frequency and percentage, continuous variables as interquartile.
Relationship between biomarkers and laboratory biomarkers.
| Covariate | R | |
|---|---|---|
| Albumin (g/L) | 0.056 | 0.647 |
| Albumin (g/L) | −0.069 | 0.574 |
eGFR = estimated glomerular filtration rate, UPCr index = urine protein creatinine index. Correlation (R) given as <0.25 as poor, 0.26–0.5 as fair, 0.51–0.75 as good, and >0.75 as excellent. Level of significance <0.05 *.
Simple logistic regression for the prognostic outcome of primary MGN using eGFR (CKD ≥ 3).
| Variables | B | SE | COR | CI (95%) | |
|---|---|---|---|---|---|
|
| 0.062 | 0.023 | 0.940 | 0.898-0.993 | 0.008 * |
|
| 0.111 | 0.077 | 1.117 | 0.961–1.299 | 0.149 |
|
| 0.178 | 0.068 | 1.195 | 1.046–1.316 | 0.009 * |
SE = Standard error, COR = Crude Odd Ratio, CI = Confidence Interval, level of significant p < 0.05 *.
Multiple logistic regression for the prognostic outcome of primary MGN using eGFR (CKD ≥ 3).
| Variables | B | SE | AOR | C.I. 95% | |
|---|---|---|---|---|---|
|
| −0.094 | 0.052 | 0.910 | 0.822–1.009 | 0.534 |
|
| 1.000 | ||||
|
| 1.000 |
SE = Standard Error, AOR= Adjusted Odd Ratio, C.I. = Confidence Interval, level of significance, p < 0.05 *.
Figure 2Receiver operating characteristics (ROC) curve was used to validate predictors of primary outcome using eGFR (CKD ≥ 3).
Simple logistic regression for the prognostic outcome of primary MGN using UPCr Index (Remission).
| Variable | B | SE | COR | 95% C.I. | |
|---|---|---|---|---|---|
| Age at diagnosis | 0.025 | 0.018 | 1.025 | 0.989–1.063 | 0.181 |
| Sex | 0.308 | 0.490 | 1.360 | 0.521–3.551 | 0.530 |
| Albumin(g/L) | −0.075 | 0.060 | 0.928 | 0.825–1.043 | 0.209 |
| Urea(mmol/L) | 0.257 | 0.136 | 1.293 | 0.991–1.686 | 0.058 |
| Creatinine (μmol/L) | 0.046 | 0.015 | 1.047 | 1.016–1.079 | 0.002 * |
| eGFR(mL/min/1.73m2) | −0.047 | 0.013 | 0.954 | 0.931–0.978 | <0.05 * |
| Serum anti-PLA2R Ab | 1.377 | 0.810 | 3.964 | 0.810–19.399 | 0.015 * |
| Urine anti-PLA2R Ab(ng/mL) | 2.472 | 1.249 | 11.845 | 1.025–136.924 | 0.05 * |
| Serum anti-THSD7A Ab(ng/mL) | −0.937 | 1.022 | 0.392 | 0.530–2.902 | 0.392 |
SE = Standard Error, COR = Crude Odd Ratio, C.I. = Confidence Interval, level of significance <0.05 *.
Multivariate logistic regression for the prognostic outcome of primary MGN using UPCr Index (Remission).
| Variable | B | SE | AOR | 95% C.I. | |
|---|---|---|---|---|---|
| Creatinine | 0.018 | 0.044 | 1.018 | 0.934–1.110 | 0.660 |
SE = Standard Error, AOR = adjusted odd ratio, C.I. = Confidence Interval, level of significance <0.05 *.
Figure 3ROC Curve was used to validate the predictors of outcome using UPCr Index (Remission).
| a | 0.2209 |
| b | −2.203 |
| c | 1.188 |
| d | 1.738 |
| MSE | 0.003579 |
| R² | 0.9886 |
| SS | 0.04294 |
| SYX | 0.07327 |
| a | 0.05272 |
| b | −1.051 |
| c | 0.2162 |
| d | 5.961 |
| MSE | 0.0003364 |
| R² | 0.9995 |
| SS | 0.002018 |
| SYX | 0.03177 |