Advances in molecular diagnosis and therapeutics in nephrotic syndrome and focal and segmental glomerulosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: The widespread adoption of next-generation sequencing by research and clinical laboratories has begun to uncover the previously unknown genetic basis of many diseases. In nephrology, one of the best examples of this is seen in focal and segmental glomerulosclerosis (FSGS) and nephrotic syndrome. We review advances made in 2017 as a result of human and molecular genetic studies as it relates to FSGS and nephrotic syndrome. RECENT FINDINGS: There are more than 50 monogenic genes described in steroid-resistant nephrotic syndrome and FSGS, with seven reported in 2017. In individuals presenting with FSGS or nephrotic syndrome before or at the age of 18 years, the commonest genes in which a mutation is found continues to be limited to only a few including NPHS1 and NPHS2 based on multiple studies. For FSGS or nephrotic syndrome that presents after 18 years, mutations in COl4A3/4/5, traditionally associated with Alport syndrome, are increasingly being reported. Despite the extensive genetic heterogeneity in FSGS, there is evidence that some of these genes converge onto common pathways. There are also reports of in-vivo models exploring apolipoprotein 1 biology, variants in which account for part of the increased risk of nondiabetic kidney disease in African-Americans. Finally, genetic testing has several clinical uses including clarification of diagnosis and treatment; identification of suitable young biologic relatives for kidney donation; and preimplantation genetic diagnosis. CRISPR gene editing is currently an experimental tool only, but the recent reports of excising mutations in embryos could be a therapeutic option for individuals with any monogenic disorder in the future. SUMMARY: Sequencing efforts are bringing novel variants into investigation and directing the efforts to understand how these lead to disease phenotypes. Expanding our understanding of the genetic basis of health and disease processes is the necessary first step to elaborate the repertoire of therapeutic agents available for patients with FSGS and nephrotic syndrome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".