Beyond the Brain
Bibliographic record
Abstract
Background and Purpose: An important minority of cerebral small vessel disease (cSVD) is monogenic. Many monogenic cSVD genes are recognized to be associated with extracerebral phenotypes. We assessed the frequency of these phenotypes in existing literature. Methods: We performed a systematic review following the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), searching Medline/Embase for publications describing individuals with pathogenic variants in COL4A1/2 , TREX1 , HTRA1 , ADA2 , and CTSA genes (PROSPERO 74804). We included any publication reporting on ≥1 individual with a pathogenic variant and their clinically relevant phenotype. We extracted individuals’ characteristics and information about associated extracerebral phenotypes and stroke/transient ischemic attack. We noted any novel extracerebral phenotypes and looked for shared phenotypes between monogenic cSVDs. Results: After screening 6048 publications, we included 96 COL4A1 (350 individuals), 32 TREX1 (115 individuals), 43 HTRA1 (38 homozygous/61 heterozygous individuals), 16 COL4A2 (37 individuals), 119 ADA2 (209 individuals), and 3 CTSA (14 individuals) publications. The majority of individuals originated from Europe/North America, except for HTRA1 , where most were from Asia. Age varied widely, ADA2 individuals being youngest and heterozygous HTRA1/CTSA individuals oldest. Sex distribution appeared equal. Extracerebral phenotypes were common: 14% to 100% of individuals with a pathogenic variant manifested at least one extracerebral phenotype (14% COL4A2 , 43% HTRA1 heterozygotes, 47% COL4A1 , 57% TREX1 , 91% ADA2 , 94% HTRA1 homozygotes, and 100% CTSA individuals). Indeed, for 4 of 7 genes, an extracerebral phenotype was observed more frequently than stroke/transient ischemic attack. Ocular, renal, hepatic, muscle, and hematologic systems were each involved in more than one monogenic cSVD. Conclusions: Extracerebral phenotypes are common in monogenic cSVD with extracerebral system involvement shared between genes. However, inherent biases in the existing literature mean that further data from large-scale population-based longitudinal studies collecting health outcomes in a systematic unbiased way is warranted. The emerging knowledge will help to select patients for testing, inform clinical management, and provide further insights into the underlying mechanisms of cSVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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".