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Canonical genetic signatures of the adult human brain
Open accessAbstract
The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.
Overview
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TL;DR
The paper applies a correlation-based “differential stability” (DS) metric to Allen Human Brain Atlas expression data across 132 structures in six adult human brains to identify conserved transcriptional organization. It reports 32 reproducible co-expression modules, links high-DS genes to brain function, disease, and drug targets, compares module conservation with mouse, and finds that conserved cortical gene expression correlates with resting-state functional connectivity.
Key findings
- DS ranged from ΔBR=0.970 to −0.057 across 17,348 uniquely annotated human transcripts; the highest-DS gene was FOXG1 (ΔBR=0.970), and PCDH8 had ΔBR=0.931. The top 10% DS genes (n=1735) were enriched for neuronal functional categories, drug interactions (first decile had 4651 small-molecule/chemical interactions, more than 30 times the third decile), and disease gene sets including mental disorders (p<8.06e-31), schizophrenia (p<9.14e-30), autism (p<3.45e-17), epilepsy (p<1.00e-11), bipolar disorder (p<4.94e-14), and major depression (p<4.60e-10).
- A consensus WGCNA network built from the 50% highest DS genes (ΔBR>0.5284, g=8674) identified 32 modules; 90.1% (15,627) of genes correlated with these patterns at kME>0.4. Modules ranged from largely neuronal (M1–M15) to essentially non-neuronal (M16–M32), with examples including M6 in cortex, M10 in striatum, M11 in thalamus, M12 in substantia nigra, M14 in hypothalamus, M16 in dentate gyrus, and M17 in cerebellum; M25 was associated with immune response (q<3.71e-35) and M30 with myelination/glial ensheathment (q<1.48e-06).
- In human-mouse comparison using 53 matched mouse structures and 2651 genes, neuron-associated modules such as M1, M6, and M7 were better preserved than many non-neuronal modules (M25–M32), though individual genes within even preserved modules sometimes shifted patterning between species.
- In cortex, the top 5th percentile of cortical DS genes (n=867) had ΔCTX>0.357 versus ΔBR>0.854 for whole brain, and only 31% of the top 5% cortical DS genes were in the top 5% of brain-wide DS. Higher cortical DS predicted stronger correlation between functional connectivity and gene expression (ρ=0.46, p<2.2e-16); 136 genes whose polymorphisms affect resting-state functional connectivity had higher expression-connectivity correlation (μ=0.12, p<2.2e-192) and higher cortical DS (ΔCTX=0.40, p<1.2e-325).
Methods
- Data came from the Allen Human Brain Atlas: six neurotypical adult whole brains (3 Caucasian males, 2 African American males, 1 Caucasian woman), with 345–911 samples per brain spanning one or both hemispheres, 232 discrete brain structures sampled at least once, and 132 structures used for the main analysis; expression was profiled with whole-genome Agilent microarrays.
- DS was defined as the average Pearson correlation across 15 pairs of the six brains over a set of anatomic regions; WGCNA was used to construct a consensus co-expression network from the top 50% DS genes, with modules assigned by kME>0.4 and functionally annotated using ToppGene and related databases.
- Cross-species comparison used Allen Mouse Brain Atlas in situ hybridization expression energy for 2651 genes across 53 matched mouse structures; functional connectivity analysis used Human Connectome Project resting-state fMRI data, including a dense connectome from 468 subjects and parcellated connectomes from 447 subjects across 52 left-hemisphere parcels, then correlated gene co-expression matrices with the connectome matrix.
Limitations
- The paper states possible ascertainment bias in regional transcriptional patterns because they may be preferentially annotated in available studies, and notes that approximately 9% of the most conserved gene set has no functional annotation to date.
- The paper states that the mouse comparison used 2651 genes initially chosen because they were potentially biologically interesting, making that set biased; specific proportions of cross-species agreement may not represent the whole transcriptome, though gene assignments as conserved or not should reflect actual conservation in these datasets.
- The paper states that functional connectivity from fMRI is an indirect measure and should not be considered a surrogate for direct anatomical connectivity; it also notes that anatomical sampling was not cell type-specific, and that direct comparisons with previous studies are challenging due to differences in analysis strategies and experimental design.
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In the paper
“Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely-patterned genes displayed dramatic shifts in regulation between species.”
§ Canonical Genetic Signatures of the Adult Human Brain > Abstract
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In the paper
“We applied a correlation-based metric of “differential stability” (DS) to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing meso-scale genetic organization.”
§ Canonical Genetic Signatures of the Adult Human Brain > Abstract
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In the paper
“Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders.”
§ Canonical Genetic Signatures of the Adult Human Brain > Abstract
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“Large transcriptional differences are seen between major structures.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Conserved transcriptional patterning in adult human brain
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“Using the six brains now available, we identified a consensus network22 common to all brains (Fig. 3a, panel 1), using the 50% highest DS genes (ΔBR>0.5284, g=8674, Supplementary Methods).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
What the sources say
- Not checked yetcites [22] Langfelder, P., Luo, R., Oldham, M. & Horvath, S. Is my network module preserved and reproducible? PLoS Comput. Biol. 7, e1001057 (2011). source
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In the paper
“This network identified 32 major transcriptional patterns, or modules, each represented by a characteristic expression pattern across brain structures, the module eigengene (ME), in each brain (Fig. 3a, panel 2).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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In the paper
“In addition to globally conserved differential relationships, the patterning for any given gene across structures in different individuals is often well conserved.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Conserved transcriptional patterning in adult human brain
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“This result was independently reproduced in gene sets from the Simons Foundation Autism Research Initiative Database (https://gene.sfari.org/autdb/Welcome.do; n=666; p<1.19e-38) and Alzheimer’s-related genes from the Alzheimer’s Forum (www.alzforum.org; n=630; p<3.55e-07).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“The top 10th percentile set of genes (n=1735) ranked by DS is significantly over-represented in many functional categories (Fig. 2d), including gene ontology (GO) molecular function, cellular component and biological processes associated with neuronal function, and transcription factor binding sites (Supplementary Table 4).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“Interestingly, each module also contained genes that were not only poorly correlated to the human module, but were instead very highly correlated (ρ > 0.8) to a different human module eigengene.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Differential gene module conservation from human to mouse
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In the paper
“The highest DS genes are highly biologically relevant, with enrichment for brain-related biological annotations, disease associations, drug targets, and literature citations.”
§ Canonical Genetic Signatures of the Adult Human Brain > Abstract
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“Interestingly, potassium channels (p<1.70e-12) are the most over-represented among high DS genes, exhibiting diverse and specific expression patterns (Supplementary Fig. 1).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“A smaller percentage of genes have high DS in cortex (Fig. 7b); in contrast to whole brain, the top 5th percentile (n=867) of DS cortex genes had ΔCTX>0.357 versus ΔBR>0.854 for whole brain. The rank ordering of genes by whole-brain DS vs cortex-only DS differs markedly, with only 31% of the top 5% of cortical DS genes in the top 5% of brain-wide DS, (Fig. 7b).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
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In the paper
“Further, we found that 136 genes whose polymorphisms significantly affect resting-state functional connectivity in a large sample of healthy adolescents28 have both higher correlation of expression with functional connectivity (μ=0.12, p<2.2e-192) and higher DS (ΔCTX=0.40, p<1.2e-325) in human cortex (red points, Fig. 7d), though they constitute only a minority (15%) of the highest cortical 5th p”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
What the sources say
- Not checked yetcites [28] Richiardi, J. et al. Correlated gene expression supports synchronous activity in brain networks. Science 348, 1241–1244 (2015). source
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“Finally, a small number (302) of high DS genes appear to have unique spatial expression patterns, and were not strongly correlated to any of the 32 module eigengenes. 50 of these genes are shown in Figure 5, illustrating the diversity of their expression patterns.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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In the paper
“From a global anatomical perspective, the 32 gene modules were predominantly enriched either in the telencephalon or in non-telencephalic deeper brain structures (Fig. 4a). Individual modules were enriched in distinct combinations of structures (Fig. 4b; Supplementary Figs. 5–8) and were associated with distinct functional pathways, disease and drug interactions (Table 1; Supplementary Fig. 9).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“In contrast, low DS genes with ubiquitous expression (lower 25th percentile in variability across brain regions, below the horizontal green line in Fig. 2b; Supplementary Table 3), such as the ubiquitin isoforms UBB and UBC, are typically not brain specific. Instead, they appear to provide the basal machinery common to all cell and are enriched for housekeeping functions such as RNA binding (p<3.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“While not a perfect comparison given the differences between species and in vivo versus in vitro, there was a clear ordering of modules that could be seen based on predominance of neuronal gene expression (Fig. 3c). These proportions ranged widely from those with largely neuronal signatures (M1-M15) to essentially non-neuronal (M16-M32).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“Some modules were well preserved (Fig. 6a), including the neuronal-enriched modules M1, M6 and M7, whereas many of the most non-neuronal modules (M25-M32) were poorly preserved.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Differential gene module conservation from human to mouse
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“Fig. 7d shows that higher cortical DS of a gene is predictive of a stronger correlation between functional connectivity and cortical gene expression pattern (ρ = 0.46, p<2.2e-16; the correlation with brain-wide DS alone was much weaker (ρ=0.17), indicating that the conserved cortical genes correlate most strongly with cortical functional connectivity.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
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“Genes sets associated with mental disorders (p<8.06e-31) are significantly enriched in the top 10% of DS genes (Fig. 2f; Supplementary Table 5), in particular those for schizophrenia (p<9.14e-30), autism (p<3.45e-17), epilepsy (p<1.00e-11), bipolar disorder (p<4.94e-14), and major depression (p<4.60e-10).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“In agreement with known function, M12 is uniquely associated with dopamine biosynthesis (q<8.39e-06) and cocaine addiction (q<5.64e-05). Other modules showed more complex anatomical patterning, such as non-telencephalic expression (M19), the inverse of M1. M19 is associated with mitochondria (q<5.50e-82) and demyelination (q<2.57e-04), and has strong disease associations with Alzheimer’s (q<3.98e-”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“Despite this variation in the overall strength of correlation across species, individual genes with matching anatomical and cellular patterns could be found for each module (left 2 ISH panels in Fig. 6c–g). On the other hand, for each module there were genes whose pattern fundamentally shifts between species (far right ISH panels), for example from thalamic to cerebellar in M11 or from glial to”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Differential gene module conservation from human to mouse
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“The great majority of all genes (90.1%, 15,627) are correlated with this relatively small set of patterns (Supplementary Table 6), and the MEs derived from these genes are highly stable (Fig. 3b).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“Interestingly, over 96% of all annotations were associated with just 17 of the 32 modules (left-most in Fig. 3e) including those restricted to the highly studied nigro-striatal pathway structures associated with Parkinson’s disease (M10 and M12) as well as a set of predominantly non-neuronal modules (M24, M23, M25, M30; Table 1).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“Furthermore, the top DS genes have a disproportionate number of drug interactions and a monotonically decreasing association with miRNA targets.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Genes with conserved patterning relate to brain function
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“Despite massive differences in size and measurement techniques of these two data modalities, many of the modules had very highly correlated expression across specific anatomical regions (Fig. 6c–g). For example, the forebrain-enriched and neuron-associated M6, striatal M10, thalamic M11 and cerebellar M17 had nearly identical patterning. In contrast, the module eigengenes for the non-neuronal mod”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Differential gene module conservation from human to mouse
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“Interestingly, approximately 9% of this most conserved gene set has no functional annotation to date, thus representing a set of rich targets for future research into human brain function.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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“Remarkably, the highest 10% of brain-wide DS genes are substantially overrepresented for known drug targets and are highly significantly enriched for functional annotations of many cellular functions and biological pathways.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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“The final set of networks were more difficult to interpret, showing consistent but more complex distributed anatomical patterning and enriched in genes associated with organelles or cellular machinery such as mitochondria, the proteasome, ribonucleoprotein complexes and chromatin.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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“Significant ontological categories of this highest cortical 5th percentile DS genes include main axon (p<7.84e-09), neuron projection (p<2.2e-04), calcium and sodium channel activity (p<3.46e-11), and axon guidance Reactome pathway (p<2.22e-04).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
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“Surprisingly, many of those genes are well studied as markers of specific cell types (e.g. VIP and SST for GABAergic interneurons) or developmental zones (homeobox genes) and are not representative of the patterning of the great majority of genes.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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In the paper
“Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders.”
§ Canonical Genetic Signatures of the Adult Human Brain > Abstract
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“Recent work has revealed that functional brain networks determined using resting-state functional magnetic resonance imaging (fMRI) can be recapitulated using correlated gene expression in postmortem brain tissue28.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
What the sources say
- Not checked yetcites [28] Richiardi, J. et al. Correlated gene expression supports synchronous activity in brain networks. Science 348, 1241–1244 (2015). source
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In the paper
“Furthermore, these patterns are likely to be representative of a larger population as they are highly consistent across all six individuals, and patterns identified using any five brains could be found reproducibly in the sixth (Supplementary Methods; Supplementary Fig. 3).”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > A canonical brain transcription co-expression network
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“Despite its relative homogeneity compared to other brain regions, human neocortex shows variations in transcriptional patterns that are consistent across individuals and are correlated with topographical position across the cortical sheet3.”
§ Canonical Genetic Signatures of the Adult Human Brain > RESULTS > Functional connectivity relates to transcription in cortex
What the sources say
- Not checked yetcites [3] Hawrylycz, M.J. et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391–399 (2012). source
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In the paper
“This may represent a mechanism for species differentiation where mutations lead to dramatic shifts in gene regulation across brain regions.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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In the paper
“These networks may represent core intracellular pathways that tend to be co-expressed and also differentially enriched in particular brain regions.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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In the paper
“Despite similarities in data type and methodology, these differences in analysis strategies and experimental design make direct comparisons with previous studies challenging.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
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“a study of ~700 genes in human versus mouse cortex by in situ hybridization found approximately 25% of genes having at least subtle differences in areal or cellular patterning39”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
What the sources say
- Not checked yetcites [39] Zeng, H. et al. Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures. Cell 149, 483–496 (2012). source
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In the paper
“Functional connectivity as measured using fMRI is a powerful but indirect measure of network organization that can provide high spatial resolution but should not be considered a surrogate for direct anatomical connectivity29, 30.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
What the sources say
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In the paper
“major differences in glial structure and function between human and mice have been described38”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
What the sources say
- Not checked yetcites [38] Oberheim, N.A., Wang, X., Goldman, S. & Nedergaard, M. Astrocytic complexity distinguishes the human brain. Trends Neurosci. 29, 547–553 (2006). source
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“Topological overlap has been shown to be a more biologically relevant metric than adjacency in many cases10.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > WGCNA consensus network construction
What the sources say
- Not checked yetcites [10] Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, 17 (2005). source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This suggests that these genes represent a functionally critical set whose transcriptional regulation is tightly controlled.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Within each batch, array-specific biases characterized by probe GC content, location in the chip, and experiment-wise mean intensity are corrected.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > AHBA data and normalization
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A second set of networks show striking enrichment in specific brain regions such as the striatum, thalamus, cerebellum and substantia nigra, presumably reflecting unique and coherent expression signatures responsible for the functions of specific neuronal types in these regions.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Adjustment is made due to the bias introduced in sample quality and expression level by different dissection methods.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > AHBA data and normalization
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“ToppGene (https://toppgene.cchmc.org) portal24 was used to access an extensive list of databases, and to calculate p-values from hypergeometric tests, corrected for multiple comparisons.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Annotation
What the sources say
- Not checked yetcites [24] Chen, J., Bardes, E.E., Aronow, B.J. & Jegga, A.G. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 37, W305–W311 (2009). source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The same control samples are included in all batches to serve this purpose.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > AHBA data and normalization
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Within a brain, cross-batch correction is done so that the mean expression levels of control samples in the batches may be aligned.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > AHBA data and normalization
Strength:plain· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“the frequency of differences appears to vary as a function of evolutionary distance37”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
What the sources say
- Not checked yetcites [37] Morris, J.A. et al. Divergent and nonuniform gene expression patterns in mouse brain. Proc. Natl. Acad. Sci. USA 107, 19049–19054 (2010). source
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This study builds upon and complements our initial results in two important ways: first, we sample brain regions at relatively equal depth by decreasing representation of cortex and cerebellum in the analysis, and second, we perform a consensus network analysis, which exclusively identifies common patterns across brains.”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“a meta-analysis of microarray studies which showed better preservation of neuronal gene co-expression compared to glial and disease-related genes36”
§ Canonical Genetic Signatures of the Adult Human Brain > DISCUSSION
What the sources say
- Not checked yetcites [36] Miller, J.A., Horvath, S. & Geschwind, D.H. Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc. Natl. Acad. Sci. USA 107, 12698–12703 (2010). source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Across brains, brain-wise mean expressions as well as control samples’ mean expression are aligned.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > AHBA data and normalization
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This method is entirely automated, resulting in an unbiased collection of distinct, yet well-defined modules.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > WGCNA consensus network construction
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“these genes were distributed across all of the human modules and therefore represent a fairly complete set of expression patterns at the whole-brain level.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Comparison with mouse ISH data
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The mouse ISH expression energy values are comparable to human microarray intensities for between-species correlations and network statistics.
- Rests on an assumption: Genes in mouse can be assigned to the same modules as their human orthologs.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We also obtained a significance value for each gene-connectivity comparison using the randomized gene co-expression matrices.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Differential stability in cortex and resting state network analysis
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“While the specific proportions of genes that agree between species may not be representative of the transcriptome as a whole, the assignment of genes as either conserved or not conserved in the text should accurately reflect their actual conservation based on these two data sets.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Comparison with mouse ISH data
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
- Rests on an assumption: The mouse ISH expression energy values are comparable to human microarray intensities for between-species correlations and network statistics.
- Rests on an assumption: Genes in mouse can be assigned to the same modules as their human orthologs.
None of the sources cited for this claim have been checked yet.
In the paper
“Each of four 15-min resting state runs for each subject in the group was cleaned (denoised) using 24-parameter motion regression followed by ICA+FIX denoising30, 48.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Differential stability in cortex and resting state network analysis
What the sources say
- Not checked yetcites [30] Smith, S.M. et al. Functional connectomics from resting-state fMRI. Trends Cogn. Sci. 17, 666–682 (2013). source
- Not checked yetcites [48] Salimi-Khorshidi, G. et al. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. Neuroimage 90, 449–468 (2014). source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To the best of our knowledge, statistical tests were chosen such that the data meet assumptions of the specific statistical test.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Statistics of the methods
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“these 2651 genes were initially chosen to be run in coronal section because they were potentially biologically interesting in some way, and therefore represent a biased set of genes.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Comparison with mouse ISH data
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The mouse ISH expression energy values are comparable to human microarray intensities for between-species correlations and network statistics.
- Rests on an assumption: Genes in mouse can be assigned to the same modules as their human orthologs.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All p-values in this analysis were Bonferroni corrected for multiple hypergeometric test comparisons.”
§ Canonical Genetic Signatures of the Adult Human Brain > ONLINE METHODS > Module enrichment analysis
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
The structure and function of the human brain are highly stereotyped.
“The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure, and function.”
The paper relies on this without support.
The general anatomical positioning of and connectivity between brain regions is highly stereotyped between individuals.
“Despite a range of brain sizes across individuals and variation in sulcal patterning in the neocortex, the general anatomical positioning of and connectivity between regions is highly stereotyped between individuals, suggesting that a significant proportion of the transcriptional coding for this common architecture is conserved across the human population.”
The paper relies on this without support.
A significant proportion of the transcriptional coding for the common brain architecture is conserved across the human population.
“Despite a range of brain sizes across individuals and variation in sulcal patterning in the neocortex, the general anatomical positioning of and connectivity between regions is highly stereotyped between individuals, suggesting that a significant proportion of the transcriptional coding for this common architecture is conserved across the human population.”
The paper relies on this without support.
The mouse ISH expression energy values are comparable to human microarray intensities for between-species correlations and network statistics.
“These values were treated the same way as microarray intensities for between-species correlations and network statistics.”
The paper relies on this without support.
Genes in mouse can be assigned to the same modules as their human orthologs.
“Genes in mouse were assigned to the same modules as their human orthologs.”
The paper relies on this without support.
The AHBA tissue samples can be mapped to the HCP 52 region parcellation such that gene expression can be compared to functional connectivity.
“The next step is to map the Allen Human Brain Atlas (AHBA) tissue samples to the HCP 52 region parcellation so that comparison can be made.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“high differential stability appears to be a hallmark of genes with considerable biological relevance40.”
From Oxytocin pathway gene networks in the human brain (2019) · cites this paper as [40]
In the citing paper
“which is indicative of highly consistent patterning across donor brains40.”
From Oxytocin pathway gene networks in the human brain (2019) · cites this paper as [40]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Mouse regional expression is described as averaged over different voxel sets
MajorOne methods section says mouse expression energy was averaged across all voxels in each matched structure. Another says it was averaged over only the 250 most highly expressed voxels, except in regions with fewer than 250 voxels.
“For each of 53 human structures, average expression energy was calculated across all voxels in matched mouse structures.”
“In mouse, the data was processed by finding the average expression energy (see web documentation above) of the 250 most highly expressed voxels in each of the 53 regions (or all voxels if fewer than 250 in a region)”
Autworks disease-set count differs between sections
MinorThe results give 2,289 Autworks gene sets, while the methods describe the same database as listing 2,288 disease states. The text does not explain the one-set difference.
“based on 2289 gene sets from the Autworks database”
“For disease annotations we used the Autworks database (http://autworks.hms.harvard.edu), listing genes associated with 2,288 disease states, including Autism.”
Citations
Cites
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Self-citation
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Research works printed but not linked: 1
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Metadata
- Authors
- Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., Jegga, A. G., Aronow, B. J., Lee, C.-K., Bernard, A., Glasser, M. F., Dierker, D. L., Menche, J., Szafer, A., Collman, F., Grange, P., Berman, K. A., Mihalas, S., Yao, Z., Stewart, L., Barabási, A.-L., Schulkin, J., Phillips, J., Ng, L., Dang, C., Haynor, D. R., Jones, A., Van Essen, D. C., Koch, C., & Lein, E.
- Affiliations
- Allen Institute for Brain Science (US)
- Cincinnati Children's Hospital Medical Center (US)
- Washington University in St. Louis (US)
- Northeastern University (US)
- Xi’an Jiaotong-Liverpool University (CN)
- University of Cincinnati (US)
- University of Washington (US)
- Georgetown University (US)
- Corresponding author
- Hawrylycz, Michael
- Lein, Ed
- ORCID
- Hawrylycz, Michael
- Miller, Jeremy A
- Menon, Vilas
- Feng, David
- Dolbeare, Tim
- Guillozet-Bongaarts, Angela L
- Jegga, Anil G
- Aronow, Bruce J
- Lee, Chang-Kyu
- Bernard, Amy
- Glasser, Matthew F
- Dierker, Donna L
- Menche, Jörg
- Szafer, Aaron
- Collman, Forrest
- Grange, Pascal
- Yao, Zizhen
- Stewart, Lance
- Schulkin, Jay
- Phillips, John
- Ng, Lydia
- Haynor, David R
- Lein, Ed
- Venue
- Nature Neuroscience
- Published
- 2015-11-16
- Volume
- 18
- Issue
- 12
- Pages
- 1832-1844
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC4700510
- OpenAlex
- W2260830658
- Semantic Scholar
- e3aa43b55cdd5d733360a178d938565fa201667a
- Cited by
- 663
- References
- 49
- Citations by year
- 2026: 53 · 2025: 84 · 2024: 83 · 2023: 70 · 2022: 72 · 2021: 74 · 2020: 66 · 2019: 38 · 2018: 46 · 2017: 44 · 2016: 29 · 2015: 1
- FWCI
- 24.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (5r33da027644-04, 5u54mh091657-05)
- National Institute of Mental Health (1U54 MH091657, U54-MH091657)
- National Institute on Drug Abuse (R33 DA027644, 4R33DA027644)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- differential stability, brain cell types, resting-state functional connectivity, neocortex, neurodevelopmental disorders, neurodegenerative diseases, therapeutic target, gene expression signatures
- MeSH terms
- Adult, Animals, Brain, Humans, Nerve Net, Mice, Gene Regulatory Networks, Transcriptome
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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