11 Regional Heterogeneity in Gene Expression, Regulation, and Coherence in the Frontal Cortex and Hippocampus across Development and Schizophrenia Leonardo Collado-Torres Staff Scientist II @fellgernon Data Science I with Andrew Jaffe

URGENT UNMET NEED Neuropsychiatric disorders cost the U.S. Economy > $80 billion/year. Neuropsychiatric conditions are the leading cause of disability in young people worldwide. 70% 70% of youth in the juvenile justice system are living with at least one mental health condition. Traumatic brain injury is the leading cause of long-term disability in children and adults younger than 35 years. 1 in 4 experience mental illness in a given year. More veterans die of suicide than in combat at rate of 20 suicides per day. 2

BrainSeq: A Human Brain Genomics Consortium DLPFC 495 samples BrainSeq Phase I polyA+ Jaffe et al., Nature Neuroscience, 2018 DLPFC 453 samples HIPPO 447 samples BrainSeq Phase II RiboZero Neuron, 2015 Collado-Torres et al, Neuron, 2019 551 individuals (286 with schizophrenia)

−6 −4 −2 0 2 4 −6 −4 −2 0 2 4 6 t−statistic HIPPO t−statistic DLPFC r = 0.276 4 SCZD expression regional heterogeneity 48 DE genes in hippocampus, 243 in DLPFC (FDR <5%) Amy Peterson Adjusting for: age, sex, chrM mapping, rRNA mapping, gene assignment rate, RIN, SNP PCs 1-5, quality surrogate variables (qSVA)

Gene Individual 1 Individual 2 A 10 15 B 5 22 C 7 9 D 100 50 DLPFC Gene Individual 1 Individual 2 A 10 17 B 6 16 C 9 30 D 120 80 HIPPO correlation( (10, 5, …), (10, 6, …) ) =~ 0.9 correlation( (15, 22, …), (17, 16, …) ) =~ 0.7 Individual 1 Individual 2 Control vs SCZD

p-values: Gene: 0.0164 Exon: 0.0499 Jxn: 1.72 * 10-5 Tx: 0.00992 Control SCZD 0.54 0.55 0.56 0.57 cleaned expr (keeping Dx) − jxnRp10m p−value: 1.72e−05 Correlation Decreased regional coherence in SCZD Control SCZD Correlation

7 HIPPO eQTLs 11,237,357 eQTL associations (FDR <1%) across genes, exons and junctions corresponding to 17,719 genes Emily E. Burke 2061 3183 2163 274 5945 2915 1178 gene exon jxn eQTLs grouped by gene id Includes 60 risk SNPs from PGC2 8 +,332 E 0 1 2 −1 0 1 2 3 4 chr2:5822204358229ï-[Q rs74563533:58250433:G:A r2:58 250 433 Residualized Expression ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 1 2 −1 0 1 2 3 4 chr2:5822204358229ï-[Q rs75575209:58138192:A:T r2:58 138 192 Residualized Expression ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● p=5.75e−34 p=3.82e−81 F

8 205,618 region-dependent eQTLs (FDR <1%) corresponding to 1,484 genes Emily E. Burke Bill Ulrich eQTL browser at http://eqtl.brainseq.org/

Analysis with PCG2 risk SNPs and proxies identifies eQTLs (FDR <1%) in risk loci HIPPO DLPFC # unique SNPs (unique index SNPs) 5510 (103) 6780 (116) # unique features 1731 2525 # Unique genes 123 171 # Unique transcripts 244 332 # Unique exons 857 1363 # Unique junctions 507 659 Emily E. Burke 21 8 95 DLPFC HIPPO In BSP2: 163/179 (91.1%) FDR <1%: 124/163 (76.6%)

Gusev et al, Nature Genetics, 2016 Transcriptome Wide Association Study (TWAS)

−5 0 5 −5 0 5 DLPFC HIPPO in_both FALSE TRUE FDR.5perc None DLPFC HIPPO Both TWAS Z by brain region Removed sex, SNP PCs 1-5, expression PCs Kept diagnosis jaffelab::cleaningY() TWAS Z scores are correlated among DLPFC & HIPPO GWAS: CLOZUK

rho=−1.26e−03 rho=−8.50e−03 rho=7.27e−03 rho=4.54e−02 DLPFC HIPPO Other Risk Locus −5 0 5 −5 0 5 −6 −3 0 3 6 −6 −3 0 3 6 TWAS Z score SCZD vs control t−statistic BEST GWAS p < 5e−08 FALSE TRUE TWAS vs SCZD differential expression Risk Loci by BEST GWAS TWAS and SCZD statistics are not related

Risk Loci Category HIPPO DLPFC Intersection Union With eQTLs <1% 103 116 95 124 With TWAS weights 86 (83.5%) 93 (80.2%) 78 (82.1%) 101 (81.5%) TWAS FDR <5% 79 (91.9%) 88 (93.5%) 73 (93.6%) 94 (93.1%) TWAS Bonferroni <5% 61 (70.9%) 68 (73.1%) 54 (69.2%) 75 (74.3%) TWAS results are complementary to eQTLs in risk loci ~80% of risk loci with eQTLs have TWAS weights, ~90% and ~70% of these are FDR or Bonferroni significant

doi.org/10.1016/j.neuron.2019.05.013 • Dorsolateral prefrontal cortex and hippocampus gene expression across development • Novel region-specific schizophrenia genetic risk features • Decreased regional functional coherence in schizophrenia • Public brain gene expression and eQTL resource at http://eqtl.brainseq.org/phase2 BrainSeq Phase II summary

Dentate Gyrus LCM-seq finds cell type specific eQTLs Jaffe, Hoeppner et al., bioRxiv, 2019

snRNA-seq for profiling cell types in brain & spatially [08] In [09] In [11] In [12] Ex+In [10] Ex [07] Ex [05] Ex [13] NPC [00] Oligo [02] Oligo [06] OPC [03] Astro [04] Micro [01] Ambig SNAP25 GAD1 CAMK2A SLC17A7 SOX11 FOXP2 MBP PDGFRA GFAP CD74 −2 −1 0 1 2 [00] Oligo [04] Micro [02] Oligo [06] OPC [11] In [03] Astro [05] Ex [08] In [10] Ex [12] Ex+In [13] NPC [09] In [01] Ambig [07] Ex −25 0 25 −50 −25 0 25 50 tSNE_1 tSNE_2 Nguyen & Maynard, In prep

Authors • Leonardo Collado-Torres o leo.collado@libd.org o @fellgernon • Emily E. Burke • Amy Peterson • Joo Heon Shin • Richard E. Straub • Anandita Rajpurohit • Stephen A. Semick • William S. Ulrich • Amanda J. Price • Cristian Valencia • Ran Tao • Amy Deep-Soboslay • Thomas M. Hyde • Joel E. Kleinman • Daniel R. Weinberger+ • Andrew E. Jaffe+ o andrew.jaffe@libd.org o @andrewejaffe 17 • BrainSeq Consortium • LIBD @lieberinstitute Funding github.com/LieberInstitute/brainseq_phase2 doi.org/10.1016/j.neuron.2019.05.013