Aging and youthful function / Observational data reanalysis
Read the composition challenge
Cell composition does not yet explain the age disagreement
The retained groups cover 99.55% of captured cells, but omitted RNA is unknown. This is not reconstructed whole tissue or a biological-age clock.
# Between-compartment composition does not resolve this age-direction conflict Computed 2026-10-19. This advances the persistent youthful-function goal by testing a specific possible explanation for the opposing gingival age directions. It extends the earlier two-fibroblast-subtype sensitivity to nine mutually exclusive captured-cell compartments, without changing genes. **Result:** the structural-ECM age slope remains positive in both the observed partial RNA mixture (**+0.213 per decade**) and a common-composition partial mixture (**+0.183**). These retain the positive same-donor fibroblast direction and oppose the negative earlier bulk-gingiva results. This particular mixture sensitivity changes numerical estimates but does not reproduce the bulk direction. It cannot exclude other mixture, cohort or assay explanations. ## Coverage: partial captured-cell mixture, never whole tissue The inputs are the already public raw fixed-gene pseudobulk counts, total raw UMIs, cell counts, donor/sample crosswalk and annotation-coverage receipt from the [earlier GSE164241 analysis](../../aging-state-2026-10-11/GINGIVAL_CELL_RESOLVED_CHALLENGE_REPORT.md). Original experiment: [Williams et al., Cell 2021](https://doi.org/10.1016/j.cell.2021.05.013), [GSE164241](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164241), using the pinned [curated periodontal atlas](https://cellxgene.cziscience.com/collections/71f4bccf-53d4-4c12-9e80-e73bfb89e398). No new source download or H5AD read was needed. The [coverage audit](derived/capture_coverage_audit.json) maps every source cell-set label to at most one chosen compartment. Combined fibroblast, epithelial and lymphoid parents are used; their child groups are never added again. The nine disjoint compartments cover **85,752 of 86,138 captured cells (99.5519%)**. Four excluded labels lack retained raw pseudobulk: | Omitted source label | Captured cells | | --- | ---: | | Cells in the cell cycle, mixed lineages | 222 | | Melanocytes | 119 | | Schwann cells | 26 | | Merkel cells | 19 | Those **386 omitted cells' total UMIs and selected-gene contributions are unknown**. A high captured-cell fraction therefore cannot establish high captured-RNA coverage or negligible marker effects. Each inferred donor's included cells are also checked against the original libraries; the counts never exceed that donor's capture. Single-cell capture frequencies are affected by dissociation, sampling and annotation and need not equal intact-tissue cell or RNA fractions. These outputs must remain labelled **partial captured-cell mixtures**, not reconstructed full gingiva or observed bulk RNA. All 18 inferred donors have all nine compartments with positive UMIs. Five of the 13 healthy donors have at least one minor compartment containing 9–19 cells. The primary analysis retains the same 13 healthy donors; a separately specified strict sensitivity requires at least 20 cells in every compartment. The latter leaves eight healthy donors aged **21, 21, 24, 28, 31, 32, 35 and 57**, with only one older donor. That changes the sampled population and makes the age contrast particularly sensitive to the 57-year donor. Repeated biopsies remain summed within the original inferred donor groups; none becomes an extra person. The exact healthy reference/fit set is `health:136, 143, 144, 147, 148, 169, 183, 184, 238, 241, 242, 283, 289`, ages 21–61 (ten women/three men). The five `periodontitis:134, 153, 161, 164, 170` groups are scored for transparency but enter neither reference-weight estimation nor healthy-age fitting. The source has 21 original libraries nested in these 18 groups. The [metadata table](derived/donor_compartment_metadata.tsv) preserves original sample-code membership and exact per-donor counts. ## Frozen common RNA composition The [plan](analysis_plan.json) was specified after reviewing earlier results and metadata, before this mixture analysis. It was not independently preregistered. A separate [metadata-only script](freeze_composition_reference.py) does not open selected-gene counts. It calculates each healthy donor's compartment RNA fractions, then takes their **unweighted mean across the 13 donors**. It uses neither disease donors nor age associations to optimize weights. Pooling all donors' UMI counts would overweight larger libraries; that is not this reference rule. The [frozen common weights](frozen_RNA_weights.json) are: | Captured compartment | Common RNA weight | | --- | ---: | | Fibroblasts | 26.2292% | | Epithelium | 12.5730% | | Endothelium | 38.3291% | | Perivascular support | 5.1410% | | Dendritic cells | 2.7521% | | Lymphoid cells | 11.2460% | | Neutrophils | 0.8170% | | Macrophages/monocytes | 1.3656% | | Mast cells | 1.5469% | These are RNA weights, **not equal cell weights**, biological target fractions or a tissue-engineering recipe. Within-compartment subpopulation composition still varies; fixing nine parent weights does not fix every underlying cell state. The strict 20-cell sensitivity uses these same weights. For each gene, observed weights mix compartment CPM before `log1p`; this must equal the direct sum of included counts divided by the sum of included UMIs. The maximum reconstruction error is **1.82 × 10⁻¹² CPM**. Common weights are then applied to each donor's unchanged compartment gene CPM, followed by `log1p` and averaging the six existing fixed panels. Logs or panel scores are never mixed directly. The comparison also reconstructs the relevant lineage panel in the same donor set: fibroblasts for five panels and epithelium for the barrier/identity panel. The unadjusted lineage slopes reproduce the earlier source analysis within 10⁻¹⁰. All **40 unique prespecified panel genes** are present at every donor × compartment key: 8 degradation, 3 inhibitor, 8 structural-ECM, 9 inflammation, 9 barrier/identity and 9 stromal-identity memberships, with shared genes counted once in the raw matrix. No missing-gene imputation, alias substitution or outcome-based feature selection is used. Coverage here differs from the historical bulk cohorts; numerical cross-study magnitudes are not pooled. ## Age-direction results and retained sensitivities The following slopes use all 13 healthy donors, with age as a linear predictor. Units are mean `log1p(CPM)` per ten chronological years. This is relative expression, not absolute RNA production, biological age or function. | Fixed panel | Observed partial RNA mixture | Common-RNA partial mixture | Same-donor lineage reference | | --- | ---: | ---: | ---: | | Matrix degradation | +0.151 | +0.163 | −0.033 | | Matrix inhibitors | +0.056 | +0.020 | −0.024 | | Structural ECM | +0.213 | +0.183 | +0.172 | | Inflammation | +0.013 | +0.028 | +0.088 | | Epithelial barrier/identity | −0.122 | −0.054 | −0.050 | | Fibroblast/stromal identity | +0.151 | +0.125 | +0.118 | Composition and measurement context affect panels differently. Inhibitor and degradation directions differ between lineage-only and aggregate partial mixtures; that is a change of estimand, not independent replication or proof of causality. The near-zero inflammatory estimates are fragile: the observed unadjusted direction changes sign in 3/13 donor omissions, and the common-RNA direction changes sign in 2/13. No inflammatory rejuvenation claim follows. The structural-ECM comparison remains positive in every specified model: | Healthy age model | Donors | Observed mixture | Common-RNA mixture | Lineage reference | | --- | ---: | ---: | ---: | ---: | | Age only | 13 | +0.213 | +0.183 | +0.172 | | Age, sex, processing version | 13 | +0.187 | +0.192 | +0.186 | | Women, age and processing version | 10 | +0.183 | +0.197 | +0.191 | | Every compartment ≥20 cells, age only | 8 | +0.279 | +0.106 | +0.075 | | Every compartment ≥20 cells, age/sex/version | 8 | +0.227 | +0.101 | +0.075 | The common-composition value is slightly **higher**, rather than lower, in the sex/version-adjusted models. A difference between these slopes must not be labelled a causal fraction attributable to composition. The strict subset's maximum design leverage reaches **0.943** in the fully adjusted fit; it is a small, strongly uneven age sample. Across the 13 unadjusted donor omissions, observed-mixture ECM slopes range from +0.150 to +0.272; common-RNA slopes range from +0.136 to +0.220. Both stay positive. The fully adjusted omission ranges also remain positive (+0.116 to +0.282 observed; +0.135 to +0.269 common). These are influence ranges, not confidence intervals. The frozen reference still contains each omitted donor's composition: omissions remove that donor only from the age fit. They therefore **are not donor-held-out validation**. All **90 model rows** and **468 individual donor omissions** are retained in the [model table](derived/healthy_age_effects.tsv) and [omission table](derived/healthy_age_donor_omissions.tsv). No fitting failures occurred in these specified models; the script retains rank/sample-size failures if they arise. Panels and score types share donors and genes and are not independent studies. ## Consequence for the bulk-versus-lineage conflict The earlier [GSE173078 bulk challenge](../../checklist-followup-2026-10-19/aging/REPORT.md) had a female/batch-adjusted structural-ECM slope of −0.246. The earlier [GSE83382 bulk group contrast](../../aging-state-2026-10-11/GINGIVAL_AGE_REFERENCE_REPORT.md) also declined with older group age. The current observed partial mixture and its common-RNA counterpart retain a positive direction. Thus this particular captured between-compartment mixture does not reproduce the negative bulk pattern. The [full direction table](derived/direction_challenge.tsv) preserves all six panel comparisons without pooling numerical scales or people. This is a failed explanation under the stated retained data and weights, not proof that composition is irrelevant. Omitted-label RNA, subpopulation mixtures, capture/site effects, sex/age distributions, clinical status and UMI-versus-bulk processing remain unresolved. No computational reweighting can establish that the different cohorts represent the same intact-tissue state. The next discriminating evidence is a matched-donor bulk and cell-resolved gingival dataset with spatial/site and health qualification, full donor-linked RNA/cell coverage, and external functional outcomes. It would distinguish assay/mixture differences from actual donor/tissue differences more directly than selecting a preferred age signature. For the restoration program, keep matrix organization, barrier, attachment mechanics and post-support durability as separate required measurements. This analysis supplies no intervention, clinical age change, restored tooth attachment or whole-body rejuvenation. ## Reproduction and checks ```powershell python studies/checklist-mechanisms-2026-10-19/aging/freeze_composition_reference.py python studies/checklist-mechanisms-2026-10-19/aging/analyze_compartment_mixture.py python -m unittest discover -s tests -p test_checklist_mechanisms_aging_mixture.py -v ``` The analysis/tests use NumPy; freezing uses only the standard library. Twelve new checks pass: parent/child overlap rejection, explicit omitted-RNA status, equal-donor versus pooled-count weights, disease exclusion from the reference, mixing before logs, raw-count reconstruction, donor units, rank failure, identical donor sets, omission units and receipt hashes. No new method package was added. Docker workbench remains stopped, and no successful doctor run is claimed. The [summary](derived/analysis_summary.json) pins the input/plan/reference and output hashes and software. Public outputs include the [donor-compartment metadata](derived/donor_compartment_metadata.tsv), [per-gene partial mixtures](derived/partial_mixture_gene_values.tsv) and [donor-panel scores](derived/partial_mixture_donor_scores.tsv). Text hashes use canonical UTF-8/LF. No new fetch/provenance record is manufactured for this local-table calculation; original source rights and attribution remain with the original study and curated data.