Includes a list of genes unique to autism, bipolar disorder, and schizophrenia, their corresponding enriched biological processes and pathways based on the functional enrichment analysis results (similar to the S2 Table) and select terms for their corresponding interactions network.

Includes a list of genes unique to autism, bipolar disorder, and schizophrenia, their corresponding enriched biological processes and pathways based on the functional enrichment analysis results (similar to the S2 Table) and select terms for their corresponding interactions network.</p

Data accompanying our Jupyter notebook code to produce the main and supplementary figures in the manuscript, the data should be copied in a folder called input and the path should be added to the notebook file.

Data accompanying our Jupyter notebook code to produce the main and supplementary figures in the manuscript, the data should be copied in a folder called input and the path should be added to the notebook file.</p

Cell type profile of autism, bipolar, and schizophrenia in human MTG.

(A) Significant cell type-specific covariation of gene expression across MTG for 3 major psychiatric disorders (Methods). All 75 cell types from [15] with magnification of 24 excitatory types shown in (B), color coded by disease combinations. Autism (Aut, cyan), bipolar disorder (Bip, purple), and schizophrenia (Scz, yellow) show interactions unique to these diseases, Aut-Bip (blue), Aut-Scz (green), and Bip-Scz (red) unique to pairs, Aut-Bip-Scz (black) for all. Excitatory cell types (IT, ET,NP, CT, L6b) and dendrogram taxonomy from [15]. (C) Cell type-specific genes unique to excitatory interactions (Aut, Bip, Scz) from (B) and representative enriched biological processes and pathways. NN = non-neuronal. Underlying data for Fig 4 can be found in S1 and S7 Tables, and the data from S1 Data/Three_psychiatric_disorders. Raw data available at https://portal.brain-map.org/atlases-and-data/rnaseq under MTG SMART-seq(2018). Code available as a notebook at https://github.com/yasharz/human-brain-disease-transcriptomics. MTG, middle temporal gyrus.</p

Disease-based cell type expression in mouse and human.

(A) Alignment of transcriptomic cell types obtained in [15] of human MTG to 2 distinct mouse cortical areas, primary visual cortex (V1) and a premotor area, the ALM cortex, each square represents a mouse (orange) or human (blue) cell type cluster mapped to the homologous consensus cell type. (B) Histogram of mouse and human EWCE values [74] over subclass level of 20 aligned cell types. K-S goodness of fit test (Methods) shows that the distributions are marginally distinct (D = 0.091, p = 0.035). (C) Simultaneous clustering of mouse and human using EWCE disease signatures at subclass level 6 inhibitory, 9 excitatory, 5 non-neuronal (orange: mouse, blue: human) shows similarity of most diseases between species. (D) Similar clustering of mouse and human using average expression levels shows species-specific expression profiles while retaining GBD disease associations. Annotation top major cell classes, side disease GBD phenotype and ADG membership. Underlying data for Fig 5 can be found in S1 Table and the data from S1 Data (using EWCE_subclass as well as Cell_subclass expression files). Raw data available at https://portal.brain-map.org/atlases-and-data/rnaseq under MTG SMART-seq (2018). Code for EWCE available through https://github.com/NathanSkene/EWCE. Code available as a notebook at https://github.com/yasharz/human-brain-disease-transcriptomics. ALM, anterior lateral motor; EWCE, expression-weighted cell type enrichment; GBD, Global Burden of Disease; MTG, middle temporal gyrus.</p

Includes 30 genes associated with brain disorders included in the current study that overlap with the 142 marker genes used to differentially distinguish the MTG cell types in Hodge and colleagues [15].

These genes form a highly differentially stable group, indicating strong cell type specificity, several uniquely associated with a disease. (CSV)</p

Includes the aggregated transcriptomic disease profile for each disorder.

Each sheet includes the aggregated gene expression for genes associated with a given disease across the brain structures listed in S3 Table. (XLSX)</p

Reproducible transcription patterns in human brain diseases.

(A) Expression profile for gene GRIA2 with error bars shown over 56 structures (S3 Table, human.brain-map.org). DS measures reproducible expression patterns from the AHBA [13]. (B) Canonical eigengenes for M1 telencephalic (language development, epilepsy) and M12 substantia nigra (Parkinson’s disease, dementia), with module correlation for representative genes. (C) Map of canonical expression modules M1-M32 mapping diseases to anatomic patterns. Disease genes are correlated with each module independently and normalized (Methods), disease ordering is the same as in Fig 1. Modules M1-M32 are ordered based on their neuronal, astrocyte, oligodendrocyte cell type content derived in [13]. Arrows and boxes indicate diseases overrepresented in M1 and M12. Other disease representative modules are described in Fig M in S1 Text. Underlying data for Fig 2 can be found in S1 and S5 Tables and the data from S1 Data disease module file. Raw data available at http://human.brain-map.org/. The information for canonical expression modules are available as S6 Table at https://www.nature.com/articles/nn.4171. Code available as a notebook at https://github.com/yasharz/human-brain-disease-transcriptomics. AHBA, Allen Human Brain Atlas; DS, differential stability.</p

Supporting Figures: Fig A in S1 Text.

Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular-based signature, based on differential co-expression, that is often unique to that disease. Brain diseases can be compared and aggregated based on the similarity of their signatures which often associates diseases from diverse phenotypic classes. Analysis of 40 common human brain diseases identifies 5 major transcriptional patterns, representing tumor-related, neurodegenerative, psychiatric and substance abuse, and 2 mixed groups of diseases affecting basal ganglia and hypothalamus. Further, for diseases with enriched expression in cortex, single-nucleus data in the middle temporal gyrus (MTG) exhibits a cell type expression gradient separating neurodegenerative, psychiatric, and substance abuse diseases, with unique excitatory cell type expression differentiating psychiatric diseases. Through mapping of homologous cell types between mouse and human, most disease risk genes are found to act in common cell types, while having species-specific expression in those types and preserving similar phenotypic classification within species. These results describe structural and cellular transcriptomic relationships of disease risk genes in the adult brain and provide a molecular-based strategy for classifying and comparing diseases, potentially identifying novel disease relationships.</div

Disease genes and cell types of middle temporal gyrus.

Coronal reference plate from the AHBA (http://human.brain-map.org) containing MTG region. (A) Mean cell type expression (CPM) of 24 cortex-related brain diseases (Methods) of 15,928 MTG nuclei over 75 cell types identified in [15]. Diseases and cell types are clustered and identify 4 cell type groups CTG 1–4 based on cell type expression enrichment. Left annotation: ADG group membership determined by Fig 1, and GBD phenotypic classification. Top annotation: Major cell type classes (excitatory, inhibitory, non-neuronal) and subclass level inhibitory (Lamp5, Sncg, Vip, Sst Chodl, Sst, Pvalb), excitatory (L2/3 IT, L4 IT, 5 IT, L6 IT, L6 IT Car3, L5 ET, L5/6 NP, L6 CT, L6b), and non-neuronal (OPC, Astrocyte, Oligodendrocyte, Endothelial, Micro-glial/perivascular macrophages). Color coding is by class (e.g., excitatory) and subclass types. Arrows indicate increasing and decreasing cell type expression gradients. (B) Cell type specificity τ measure pooled to phenotypic GBD categories shows psychiatric and movement classes as most cell type specific. Bar: mean specificity over all cells, p-values of each phenotype group show significance. (C) UMAP combining mesoscale and cell type disease relationships color coded by phenotype (Methods). Numbers show original ADG membership with primary cell type annotation and excitatory gradient. Underlying data for Fig 3 can be found in S1 and S6 Tables, and the data from S1 Data Disease Cell-type cluster level and correlation matrices. Raw data available at https://portal.brain-map.org/atlases-and-data/rnaseq under MTG SMART-seq(2018). Code available as a notebook at https://github.com/yasharz/human-brain-disease-transcriptomics. ADG, Anatomic Disease Group; AHBA, Allen Human Brain Atlas; GBD, Global Burden of Disease; MTG, middle temporal gyrus.</p

Includes the differential stability and associated canonical module, as defined in Hawrylycz and colleagues [13], for each gene included in the current study, sorted by the disease–gene pair name.

Includes the differential stability and associated canonical module, as defined in Hawrylycz and colleagues [13], for each gene included in the current study, sorted by the disease–gene pair name.</p