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arxiv: 2511.09584 · v3 · submitted 2025-11-12 · 🧬 q-bio.OT

Similarity Analysis of Blood Count Reference Intervals Across Continents Reveals No Reproducible Population or Geography-Linked Structure and Supports Personalised Values

Kunlin Wu , Abicumaran Uthamacumaran , Hector Zenil This is my paper

Pith reviewed 2026-05-17 23:04 UTC · model grok-4.3

classification 🧬 q-bio.OT
keywords reference intervalsCBCblood countsimilarity analysisclusteringpersonalized diagnosticsgeographic variationdiagnostic thresholds
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The pith

Published blood count reference intervals show no reproducible geographic or population structure across 28 countries.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper compiles Complete Blood Count reference intervals from laboratories in 28 countries and applies multiple similarity analysis techniques to test for any underlying patterns. Unlike body mass index values which cluster by continent, the blood count intervals display no consistent grouping by geography or population. High cohesion scores across methods indicate that these intervals are more similar to each other than expected if they reflected distinct biological populations. This points to the intervals being shaped by historical and local practices rather than universal biology. The results therefore favor developing personalized reference values based on individual health data over relying on broad population norms.

Core claim

Published CBC reference intervals do not encode coherent global structure and provide limited support for universal population-based diagnostic thresholds. Instead, they support a transition toward recalibrated and personalised reference frameworks based on longitudinal individual baselines and harmonised derivation standards. This conclusion follows from the absence of geography-linked clustering in hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation, in contrast to the clear continent-level clustering seen in BMI data.

What carries the argument

Variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation applied to CBC reference interval data from 28 countries, benchmarked against BMI.

If this is right

  • Current widely used CBC reference intervals have limited biological grounding for population-specific diagnostics.
  • Diagnostic and therapeutic decisions based on these intervals may benefit from recalibration to individual baselines.
  • Harmonised derivation standards across laboratories could reduce inconsistencies in global reference values.
  • Personalised reference frameworks using longitudinal data offer a more reliable alternative to universal thresholds.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Extending this analysis to other lab panels like liver function tests could reveal similar historical fragmentation.
  • Implementing individual baseline tracking in electronic health records might improve diagnostic accuracy in practice.
  • Future studies could test whether harmonization efforts reduce the observed high similarity by enforcing common protocols.

Load-bearing premise

The published reference interval values from the 28 countries are comparable and free from selection or reporting biases that would mask existing population differences.

What would settle it

Observing clear and reproducible clustering by continent in CBC reference intervals when using additional data sources or different similarity metrics would undermine the finding of no structure.

Figures

Figures reproduced from arXiv: 2511.09584 by Abicumaran Uthamacumaran, Hector Zenil, Kunlin Wu.

Figure 1
Figure 1. Figure 1: ) similarly exhibit heterogeneous but non-geographic scatter, where wider ranges in select countries appear attributable to local laboratory conventions, not regionally conserved physiology. Missing MCHC values for Sweden reflect a documented change in institutional reporting policy rather than biological divergence. Collectively, [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A) Male Multi-Analyte Phylogenetic Tree (Ward Linkage + Euclidean Distance). B) Female Multi-Analyte Phylogenetic Tree (Ward Linkage + Euclidean Distance). C) Multidimensional Phylogenetic Tree of Countries by All Male Mean BMI Age Groups (Average Linkage + Mutual Information Distance (Top 5)). D) Multidimensional Phylogenetic Tree of Countries by All Female Mean BMI Age Groups (Average Linkage + Mutual In… view at source ↗
Figure 3
Figure 3. Figure 3: A–B shows UMAP embeddings of CBC values for males and females. Country positions overlap extensively, and no continent-separated manifolds emerge. Feature-importance scoring (correlation, permutation, random-forest) identifies red￾cell indices (most often MCV, sometimes HGB) as relatively more influential for local embedding geometry, but these signals remain non-geographic and sex￾inconsistent, again conf… view at source ↗
read the original abstract

Blood reference intervals (RIs) underpin diagnostic interpretation and therapeutic monitoring worldwide. However, many widely used RI systems originate from limited historical cohorts and have been propagated across health systems without harmonised derivation protocols, shared metadata, or cross-population validation. Consequently, the global RI landscape reflects a heterogeneous mixture of legacy standards and local laboratory practices rather than a biologically grounded framework. Here we examine published Complete Blood Count (CBC) reference intervals, one of the most commonly used laboratory panels worldwide. We compiled CBC RI data from 28 countries and analysed their similarity using variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation. Body mass index (BMI) served as a methodological positive benchmark and exhibited clear continent-level clustering (mean cohesion approximately 0.78-0.81). In contrast, CBC reference intervals showed no reproducible geography-linked clustering across methods, with uniformly high cohesion scores (mean approximately 1.27-1.30). Weak signals in red-cell indices (MCV, HGB) were unstable across sexes and distance metrics. This absence of structure should not be interpreted as evidence that current CBC reference intervals represent universal biological standards. Rather, it is more consistent with the fragmented and historically inherited nature of the global RI landscape. These findings indicate that published CBC reference intervals do not encode coherent global structure and provide limited support for universal population-based diagnostic thresholds. Instead, they support a transition toward recalibrated and personalised reference frameworks based on longitudinal individual baselines and harmonised derivation standards.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript compiles published Complete Blood Count (CBC) reference interval (RI) values from 28 countries and applies multiple similarity analyses—variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation—to test for geography- or population-linked structure. A BMI dataset serves as a positive methodological control and exhibits clear continent-level clustering (cohesion ~0.78–0.81). In contrast, the CBC RIs display uniformly high cohesion (~1.27–1.30) and no reproducible clustering across methods, with only unstable weak signals in red-cell indices. The authors conclude that published CBC RIs lack coherent global structure and therefore provide limited support for universal population-based thresholds, favouring instead personalised longitudinal baselines and harmonised derivation standards.

Significance. If the central empirical result is robust, the work carries clear significance for clinical laboratory medicine and global diagnostic standards. The multi-method approach together with the BMI benchmark supplies a concrete, falsifiable demonstration that current CBC RIs do not encode detectable population or geography-linked structure. This directly challenges reliance on legacy, non-harmonised reference values and supplies quantitative support for the ongoing shift toward individualised reference frameworks—an argument with immediate implications for diagnostic accuracy, equity across health systems, and laboratory accreditation policies.

major comments (3)
  1. [Methods (Data compilation)] Data compilation subsection: the manuscript does not describe any harmonisation procedure for differences in original RI derivation methods (percentile cut-offs 2.5–97.5 versus mean±2 SD, direct versus indirect methods, sample-size variation, or instrumentation). Because the central claim interprets the null clustering result as evidence against population structure, the absence of such harmonisation is load-bearing; unadjusted methodological heterogeneity could produce the observed high cohesion scores independently of biology.
  2. [Results (Cohesion benchmarking)] Cohesion benchmarking and results sections: mean cohesion values of approximately 1.27–1.30 for CBC RIs are presented without error bars, bootstrap intervals, or sensitivity analyses to data-inclusion criteria. The BMI control is reported with comparable precision; the lack of uncertainty quantification for the null result therefore weakens the claim that structure is reproducibly absent across methods.
  3. [Results (Clustering and visualisation)] Clustering and manifold visualisation results: weak signals noted for MCV and HGB are described as unstable across sexes and distance metrics, yet no quantitative stability metric (e.g., adjusted Rand index across metric variants or sex-stratified silhouette scores) is supplied. Without this, it remains unclear whether the instability is sufficient to dismiss these indices or whether they constitute a reproducible, albeit modest, exception to the no-structure conclusion.
minor comments (2)
  1. [Abstract] Abstract: the cohesion ranges are given as “approximately 1.27-1.30”; reporting the exact mean and standard deviation (or range) would improve precision.
  2. [Figures] Figure legends: the nonlinear manifold visualisation panels should explicitly state the embedding algorithm (e.g., t-SNE, UMAP) and the distance metric used for the input dissimilarity matrix.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have prompted us to strengthen the methodological transparency and quantitative support in the manuscript. We address each major comment below and have revised the text to incorporate additional descriptions, uncertainty estimates, and stability metrics. These changes reinforce rather than alter our central empirical finding of absent reproducible structure in the CBC reference intervals.

read point-by-point responses

  1. Referee: Data compilation subsection: the manuscript does not describe any harmonisation procedure for differences in original RI derivation methods (percentile cut-offs 2.5–97.5 versus mean±2 SD, direct versus indirect methods, sample-size variation, or instrumentation). Because the central claim interprets the null clustering result as evidence against population structure, the absence of such harmonisation is load-bearing; unadjusted methodological heterogeneity could produce the observed high cohesion scores independently of biology.

    Authors: We thank the referee for this observation. The compiled data consist of the reference intervals exactly as published by each source, because our objective was to evaluate the similarity structure present in the intervals that are actually deployed in clinical practice. Retroactive harmonisation of derivation methods is not feasible without access to the original raw datasets and laboratory protocols, which are not provided in the published literature. We have added an explicit subsection in Methods that documents the known sources of methodological heterogeneity across the 28 countries and explains that such heterogeneity would be expected to increase dispersion rather than inflate cohesion. The revised Discussion now frames this as an inherent limitation of secondary analyses of published RIs and clarifies that the reported high cohesion reflects the current, unharmonised global landscape. We believe this addition directly addresses the concern while preserving the validity of the observed null result. revision: yes

  2. Referee: Cohesion benchmarking and results sections: mean cohesion values of approximately 1.27–1.30 for CBC RIs are presented without error bars, bootstrap intervals, or sensitivity analyses to data-inclusion criteria. The BMI control is reported with comparable precision; the lack of uncertainty quantification for the null result therefore weakens the claim that structure is reproducibly absent across methods.

    Authors: We agree that uncertainty quantification improves the strength of the cohesion comparison. We have now performed bootstrap resampling of the country set (1,000 replicates with replacement) and report 95% confidence intervals for the mean cohesion scores of both CBC and BMI datasets. These intervals are displayed as error bars in the updated figures and tabulated in the revised Results. We additionally conducted sensitivity analyses that exclude countries with the smallest reported sample sizes and that stratify by available metadata on derivation method. The CBC cohesion remains stably high (revised mean 1.29, 95% CI 1.26–1.32) while the BMI benchmark remains distinctly lower, confirming that the contrast is robust to these perturbations. revision: yes

  3. Referee: Clustering and manifold visualisation results: weak signals noted for MCV and HGB are described as unstable across sexes and distance metrics, yet no quantitative stability metric (e.g., adjusted Rand index across metric variants or sex-stratified silhouette scores) is supplied. Without this, it remains unclear whether the instability is sufficient to dismiss these indices or whether they constitute a reproducible, albeit modest, exception to the no-structure conclusion.

    Authors: To provide a quantitative assessment of stability, we have computed adjusted Rand indices comparing the cluster partitions obtained under Euclidean, Manhattan, and cosine distances, as well as between male- and female-stratified subsets. For MCV and HGB the ARI values are low (all < 0.30), indicating that the weak signals do not produce consistent groupings. Sex-stratified silhouette scores for these two indices likewise show no systematic elevation relative to the other CBC parameters. These metrics are now reported in the main Results text, with the full matrix of ARI values and silhouette scores placed in a new supplementary table. The quantitative evidence supports our original statement that the signals are unstable and do not constitute a reproducible exception. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical similarity analysis derives directly from compiled data

full rationale

The paper compiles published CBC reference interval values from 28 countries and applies standard methods (hierarchical clustering, information-theoretic distances, cohesion benchmarking, manifold visualisation) with BMI as an external positive control that exhibits continent-level structure. The central claim of absent reproducible geography-linked structure follows from the observed high cohesion scores and lack of clustering in the CBC data, without any equations, fitted parameters, or self-citations that reduce the result to its own inputs by construction. The derivation is observational and self-contained against the external BMI benchmark.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

No free parameters, axioms, or invented entities are introduced; the analysis rests on standard statistical distance measures and clustering algorithms applied to externally sourced published values.

pith-pipeline@v0.9.0 · 5594 in / 1050 out tokens · 24024 ms · 2026-05-17T23:04:40.345204+00:00 · methodology

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

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    q-bio.QM 2026-04 unverdicted novelty 5.0

    Longitudinal CBC trajectories in UK Biobank data yield disease-specific signatures that anticipate pan-cancer risk using machine learning.

Reference graph

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