Biallelic MADD variants cause a phenotypic spectrum ranging from developmental delay to a multisystem disorder
Bibliographic record
Abstract
In pleiotropic diseases, multiple organ systems are affected causing a variety of clinical manifestations. Here, we report a pleiotropic disorder with a unique constellation of neurological, endocrine, exocrine, and haematological findings that is caused by biallelic MADD variants. MADD, the mitogen-activated protein kinase (MAPK) activating death domain protein, regulates various cellular functions, such as vesicle trafficking, activity of the Rab3 and Rab27 small GTPases, tumour necrosis factor-α (TNF-α)-induced signalling and prevention of cell death. Through national collaboration and GeneMatcher, we collected 23 patients with 21 different pathogenic MADD variants identified by next-generation sequencing. We clinically evaluated the series of patients and categorized the phenotypes in two groups. Group 1 consists of 14 patients with severe developmental delay, endo- and exocrine dysfunction, impairment of the sensory and autonomic nervous system, and haematological anomalies. The clinical course during the first years of life can be potentially fatal. The nine patients in Group 2 have a predominant neurological phenotype comprising mild-to-severe developmental delay, hypotonia, speech impairment, and seizures. Analysis of mRNA revealed multiple aberrant MADD transcripts in two patient-derived fibroblast cell lines. Relative quantification of MADD mRNA and protein in fibroblasts of five affected individuals showed a drastic reduction or loss of MADD. We conducted functional tests to determine the impact of the variants on different pathways. Treatment of patient-derived fibroblasts with TNF-α resulted in reduced phosphorylation of the extracellular signal-regulated kinases 1 and 2, enhanced activation of the pro-apoptotic enzymes caspase-3 and -7 and increased apoptosis compared to control cells. We analysed internalization of epidermal growth factor in patient cells and identified a defect in endocytosis of epidermal growth factor. We conclude that MADD deficiency underlies multiple cellular defects that can be attributed to alterations of TNF-α-dependent signalling pathways and defects in vesicular trafficking. Our data highlight the multifaceted role of MADD as a signalling molecule in different organs and reveal its physiological role in regulating the function of the sensory and autonomic nervous system and endo- and exocrine glands.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".