Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease.

paper Cited Public

Authors: Bryois, Julien; Skene, Nathan G; Hansen, Thomas Folkmann; Kogelman, Lisette J A; Watson, Hunna J; Liu, Zijing; Eating Disorders Working Group of the Psychiatric Genomics Consortium; International Headache Genetics Consortium; 23andMe Research Team; Brueggeman, Leo; Breen, Gerome; Bulik, Cynthia M; Arenas, Ernest; Hjerling-Leffler, Jens; Sullivan, Patrick F
Year: 2020
Journal: Nature genetics
PMID: 32341526
DOI: 10.1038/s41588-020-0610-9
PMCID: PMC7930801

Figure 1:

Study design and tissue-level associations. Heat map of trait – tissue/cell types associations (−log10P) for the selected traits. (A) Trait – tissue/cell types associations were performed using MAGMA and LDSC (testing for enrichment in genetic association of the top 10% most specific genes in each tissue/cell type). (B) Tissue – trait associations for selected brain related traits. (C) Tissue – trait associations for selected non-brain related traits. (D) The mean strength of association (−log10P) of MAGMA and LDSC is shown and the bar color indicates whether the tissue is significantly associated with both methods, one method or none (significance threshold: 5% false discovery rate).

LLM interpretation

This figure presents a study design and results for trait-tissue associations using MAGMA and LDSC. Panel A is a workflow diagram illustrating the analysis of 18 brain and 8 non-brain traits across 37 tissues and 39 cell types. Panels B, C, and D are bar charts showing the mean $-\log_{10}(P\text{-value})$ of associations for brain-related traits (Schizophrenia, Intelligence, MDD, Parkinson) and non-brain traits (IBD, Type 2 diabetes, Hemoglobin A1c, Stroke), with bar colors indicating whether the association was significant in both, one, or neither method based on a 5% FDR threshold.

Figure 2:

Association of selected brain related traits with cell types from the entire nervous system. 841 Associations of the top 10 most associated cell types are shown. (A) Conditional analysis results for 842 Parkinson’s disease using MAGMA. The label indicates the cell type the association analysis is being 843 conditioned on. (B) The mean strength of association (−log10P) of MAGMA and LDSC is shown and 844 the bar color indicates whether the cell type is significantly associated with both methods, one method 845 or none (significance threshold: 5% false discovery rate).

LLM interpretation

Figure A consists of four horizontal bar charts showing the mean strength of association ($-log_{10}p\text{-value}$) between various cell types and four traits: Schizophrenia, Intelligence, Parkinson’s disease, and Stroke. Bars are color-coded to indicate significance based on a 5% FDR threshold, distinguishing whether the association was found by both MAGMA and LDSC, only one of the methods, or neither. Figure B displays four horizontal bar charts for Parkinson’s disease, comparing the original association strengths against results conditioned on three specific cell types (Cholinergic and monoaminergic neurons, Enteric neurons, and Oligodendrocytes), with bars colored by significance.

Figure 3:

Replication of cell type – trait associations in mouse datasets. Tissue – trait associations are shown for the 10 most association cell types among 88 cell types from 9 different brain regions. (A) Tissue – trait associations are shown for the 10 most association cell types among 24 cell types from 5 different brain regions. (B) The mean strength of association (−log10P) of MAGMA and LDSC is shown and the bar color indicates whether the cell type is significantly associated with both methods, one method or none (significance threshold: 5 % false discovery rate).

LLM interpretation

This figure consists of two sets of horizontal bar charts (A and B) showing the strength of association between cell types and various traits (Schizophrenia, Bipolar, Intelligence, Autism, MDD, and Intracranial volume). The x-axis represents the mean strength of association as $-\log_{10}(p\text{-value})$. Bars are color-coded to indicate statistical significance based on a 5% FDR threshold: orange for both MAGMA and LDSC methods, blue for MAGMA only, yellow for LDSC only, and grey for none.

Figure 4:

Human replication of cell type – trait associations. Cell type - trait associations for 15 cell types (derived from single-nuclei RNA-seq) from 2 different brain regions (cortex, hippocampus). (A) Cell type - trait associations for 31 cell types (derived from single-nuclei RNA-seq) from 3 different brain regions (frontal cortex, visual cortex and cerebellum). (B) The mean strength of association (−log10P) of MAGMA and LDSC is shown and the bar color indicates whether the cell type is significantly associated with both methods, one method or none (significance threshold: 5% false discovery rate). INT (intelligence), SCZ (schizophrenia), EDU (educational attainment), NEU (neuroticism), BMI (body mass index), BIP (bipolar disorder), MDD (Major depressive disorder), MEN (age at menarche), ASD (autism spectrum disorder), MIG (migraine), PAR (Parkinson’s disease), ADHD (attention deficit hyperactivity disorder), ICV (intracranial volume), HIP (hippocampal volume), AN (anorexia nervosa), ALZ (Alzheimer’s disease), ALS (amyotrophic lateral sclerosis), STR (stroke).

LLM interpretation

This figure consists of two heat-map style bar charts (A and B) showing the mean strength of association ($-log_{10}P$) between various brain cell types (y-axis) and human traits (x-axis). The bars are color-coded to indicate statistical significance based on a 5% FDR threshold: orange for both MAGMA and LDSC methods, blue for MAGMA only, light blue for LDSC only, and yellow for none. Panel A displays 15 cell types from the cortex and hippocampus, while Panel B displays 31 cell types from the frontal cortex, visual cortex, and cerebellum.

Figure 5:

Enrichment of Parkinson’s disease differentially expressed genes in cell types from the substantia nigra. Enrichment of the 500 most up/down regulated genes (Braak stage 0 vs Braak stage 1—2, 3—4 and 5—6, as well as cases vs controls) in postmortem human substantia nigra gene expression samples. The enrichments were obtained using EWCE11. A star shows significant enrichments after multiple testing correction (P<0.05/(25*6).

LLM interpretation

This figure consists of six horizontal bar charts showing the enrichment of differentially expressed genes (upregulated in red, downregulated in blue) across various cell types in the substantia nigra. The y-axis represents the number of standard deviations from the mean, and the rows compare different disease states (Braak stages 1–2, 3–4, 5–6) and external datasets (Lesnick et al. 2007, Moran et al. 2006 Lateral and Medial SNc). Asterisks denote statistically significant enrichments (P < 0.05 after correction), with notable patterns of downregulation in dopaminergic neurons and upregulation in various oligodendrocyte and glial cell types.

#	Section	Preview
0	Introduction	Understanding the genetic basis of complex brain disorders is critical for identifying individuals…
1	Introduction	Functional genomic studies from brain are now seen as critical for interpretation of GWAS findings…
2	Introduction	Multiple groups have developed strategies to identify tissues associated with complex traits…
3	Introduction	Here, we integrate a wider range of gene expression data – tissues across the human body and…
4	Results — Genetic correlations among complex traits	Our goal was to use GWAS results to identify relevant tissues and cell types. Our primary focus was…
5	Results — Genetic correlations among complex traits	We estimated the genetic correlations (rg) between these 26 traits. We confirmed prior reports 21,22…
6	Results — Association of traits with tissues using bulk-tissue RNA-seq	We first aimed to identify the human tissues showing enrichment for genetic associations using…
7	Results — Association of traits with tissues using bulk-tissue RNA-seq	Examination of non-brain traits found, as expected, associations with salient tissues. For example,…
8	Results — Association of traits with tissues using bulk-tissue RNA-seq	For brain-related traits (Figure 1C, S4 and Table S2), 13 of 18 traits were significantly associated…
9	Results — Association of traits with tissues using bulk-tissue RNA-seq	In conclusion, we show that tissue-level gene expression allows identification of relevant tissues…
10	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	We leveraged gene expression data from 39 broad categories of cell types from the mouse central and…
11	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	As in our previous study of schizophrenia based on a small number of brain regions 12, we found the…
12	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	Neurological disorders generally implicated fewer cell types, possibly because neurological GWAS had…
13	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	Stroke was significantly associated with vascular smooth muscle cells (Figure 2A) consistent with an…
14	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	We found that Parkinson’s disease was significantly associated with cholinergic and monoaminergic…
15	Results — Association of brain phenotypes with cell types from the mouse central and peripheral nervous system	Parkinson’s disease (Figure 2A), which is consistent with Braak’s hypothesis, which postulates…
16	Results — Neuronal prioritization in the mouse central nervous system	A key goal of this study was to prioritize specific cell types for follow-up experimental studies.…
17	Results — Neuronal prioritization in the mouse central nervous system	Using the CNS neuron gene expression specificity metrics, we observed a reduction in the number of…
18	Results — Neuronal prioritization in the mouse central nervous system	Altogether, these results suggest that specific types of CNS neurons can be prioritized for…
19	Results — Cell type-specific and trait-associated genes are enriched in specific biological functions	Understanding which biological functions are dysregulated in different cell types is a key component…

Name	Type
1000 Genomes Project	cohort
19 brain regions local	anatomy
23andMe	cohort
5 different brain regions local	anatomy
9 brain regions local	anatomy
ACTE* local	drug
adolescent mice	cohort
age at menarche	phenotype
age at menopause	phenotype
ALS	phenotype
Alzheimer’s case-control cohort local	cohort
Alzheimer's disease	phenotype
Alzheimer’s disease	phenotype
amygdala	anatomy
amyotrophic lateral sclerosis	phenotype
anorexia nervosa	phenotype
anterior cingulate cortex	anatomy
anthropometric traits	phenotype
apoE	gene
astrocyte local	cell_type
attention deficit hyperactivity disorder	phenotype
autism	phenotype
bipolar disorder	phenotype
BMI	phenotype
body mass index	phenotype
Braak stage 1–2 local	phenotype
Braak stage 3–4 local	phenotype
Braak stage 5–6 local	phenotype
brain	anatomy
Brain cell types local	anatomy
brain circuits	anatomy
Brain Complex Traits local	phenotype
brain immune cell types local	anatomy
brain-related phenotypes	phenotype
brain related traits local	phenotype
Brodmann area 10	anatomy
Cajigas et al. local	cohort
cell type local	anatomy
cell types local	cell_type
central nervous system	anatomy
central nervous system neuron local	anatomy
cerebellum	anatomy
cholinergic neuron local	anatomy
cholinergic neurons	phenotype
Cholinergic neurons local	cell_type
cingulum	anatomy
cognitive phenotypes	phenotype
cognitive trait local	phenotype
cognitive traits	phenotype
complex traits	phenotype
Core dataset local	cohort
coronary artery disease	phenotype
cortex	anatomy
cortical excitatory neurons local	anatomy
cortical inhibitory neurons local	anatomy
dentate gyrus	anatomy
dentate gyrus granule neurons local	anatomy
Disjkstra dataset 50 local	cohort
dopaminergic adult neurons local	anatomy
Dopaminergic defects local	phenotype
dopaminergic neurons	anatomy
dorsolateral prefrontal cortex	anatomy
downregulated genes in Parkinson’s disease local	gene
DRD2	gene
educational attainment	phenotype
enteric neurons local	anatomy
Enteric neurons local	anatomy
Enteric neurons local	cell_type
European population	cohort
frontal cortex	anatomy
functional genomic studies local	drug
GABA	phenotype
GAD1	gene
GAD2	gene
gene expression	phenotype
gene expression levels local	drug
General Psychopathy Factor local	phenotype
glutamatergic neurons	phenotype
GSE49036 local	cohort
GSE7621 local	cohort
GSE8397 local	cohort
GTEx	cohort
GTEx consortium	cohort
GWAS	cohort
GWAS datasets local	cohort
Habib replication dataset local	cohort
height	phenotype
hemoglobin A1c local	phenotype
hemoglobin A1C local	phenotype
hindbrain	anatomy
hindbrain neurons local	anatomy
hippocampal CA1 region	anatomy
Hippocampal volume	anatomy
hippocampus	anatomy
Homo sapiens	cohort
human disorders local	phenotype
human single-nuclei RNA-seq dataset local	cohort
Human single-nuclei RNA-seq dataset local	cohort
hypothalamus	anatomy
immune cells local	anatomy
immune function	phenotype
independent RNA-seq datasets local	cohort
inflammatory bowel disease	phenotype
intelligence	phenotype
interneuron	phenotype
Interneurons local	cell_type
intracranial volume	anatomy
IQ	phenotype
KI dataset local	cohort
Lake dataset local	cohort
lateral substantia nigra local	anatomy
lateral substantia nigra cohort (7 controls, 9 cases) local	cohort
Lesnick dataset 46 local	cohort
Lewy bodies local	phenotype
MAGMA	drug
Main dataset local	cohort
major depressive disorder	phenotype
medial substantia nigra local	anatomy
medial substantia nigra cohort (8 controls, 15 cases) local	cohort
medium spiny neurons	anatomy
medium spiny neurons from the striatum local	anatomy
medulla	anatomy
MGL* local	drug
microglia local	cell_type
microglia	phenotype
midbrain	anatomy
migraine	phenotype
monoaminergic neuron local	anatomy
monoaminergic neurons local	anatomy
Monoaminergic neurons local	cell_type
mood disorders	phenotype
Moran dataset 47 local	cohort
Mouse nervous system local	cohort
Multiple system atrophy	phenotype
mural cells local	anatomy
Mus musculus	cohort
Nalls et al. local	cohort
neocortex	anatomy
neural progenitors local	anatomy
neuroblasts	anatomy
neurological disorders	phenotype
neurological phenotypes local	phenotype
neurons	phenotype
neuroticism	phenotype
non-neuronal cells	phenotype
oligodendrocyte lineage local	anatomy
Oligodendrocyte lineage cells local	anatomy
oligodendrocyte precursor local	cell_type
oligodendrocytes	phenotype
Oligodendrocytes local	cell_type
OPC local	drug
parietal cortex	anatomy
Parkinsonism local	phenotype
Parkinson's disease	phenotype
Parkinson’s disease	phenotype
peripheral nervous system	anatomy
peripheral sensory neurofilament neurons local	anatomy
Peripheral sensory neurofilament neurons local	anatomy
pons	anatomy
Post-mortem human brains local	cohort
prefrontal cortex	anatomy
primary visual cortex	anatomy
psychiatric and cognitive traits local	phenotype
psychiatric disorders	phenotype
psychiatric traits	phenotype
pyramidal CA1 local	anatomy
pyramidal neuron local	cell_type
pyramidal neurons	anatomy
Pyramidal neurons local	cell_type
pyramidal neurons from the CA1 region of the hippocampus local	anatomy
pyramidal neurons from the somatosensory cortex local	anatomy
raphe nucleus local	anatomy
Replication dataset 1 local	cohort
Replication dataset 2 local	cohort
Replication dataset 3 local	cohort
S1 local	anatomy
Saunders dataset	cohort
schizophrenia	phenotype
Skene dataset local	cohort
Slc17a7	gene
somatosensory cortex	anatomy
spinal cord	anatomy
striatum	anatomy
stroke	phenotype
substantia nigra	anatomy
substantia nigra cohort (9 controls, 16 cases) local	cohort
TEGLU* local	drug
TEINH* local	drug
telencephalon	anatomy
telencephalon inhibitory neurons local	anatomy
thalamus	anatomy
tissue-level gene expression local	drug
trait enrichment local	phenotype
Twin cohort	cohort
type 2 diabetes	phenotype
type 2 diabetes adjusted for BMI local	phenotype
upregulated genes in Parkinson’s disease local	gene
Vagus nerve local	anatomy
vascular cells local	anatomy
vascular smooth muscle cells	anatomy
ventral midbrain	anatomy
waist-hip ratio adjusted for BMI	phenotype
waist to hip ratio local	phenotype
Watanabe et al. local	cohort
Zeisel 2018 dataset local	cohort
Zeisel dataset	cohort
Zeisel et al. dataset local	cohort
α-synuclein	drug
α-synuclein aggregates local	drug

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In this knowledge base

Title	Year	PMID
Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder.	2025	40360802
Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry.	2024	38769152
Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders.	2022	34719691
Genetic diversity fuels gene discovery for tobacco and alcohol use.	2022	36477530

External

Title	Authors	Journal	Year	Link
Benchmarking of single nuclei RNA-seq methods on human post-mortem brain tissue.	Nikouei K et al.	—	2026	→
Complement receptor 3 (CR3)-dependent microglial synapse elimination drives Parkinson's disease pathogenesis in systemic inflammation.	Cai L et al.	—	2026	→
Cross-ancestry genetic architecture reveals shared biological pathways of major psychiatric disorders.	Feng Y et al.	—	2026	→
Genome-wide investigation of prosody perception: Shared genetic influences between speech rhythm, musical rhythm, and reading traits.	Scartozzi AC et al.	—	2026	→
Integrating polygenic signals and single-cell multiomics identifies cell-type-specific regulomes critical for immune- and aging-related diseases.	Ma Y et al.	—	2026	→
Multi-Network Co-expression Analysis Enhances Biological Insights from Single-Cell Gene Expression.	Gómez-Pascual A et al.	—	2026	→
Old enough to be a model? On the role of maturity in stem cell-based models for neuropsychiatric disorders.	He B et al.	—	2026	→
Personality Genomics.	Schwaba T et al.	—	2026	→
Progress in understanding the biological basis of polygenic disorders.	Wray NR et al.	—	2026	→
Testing an inverse link between limbic alpha-synucleinopathy and myelin markers in mice and humans.	Clark RN et al.	—	2026	→
The brain neurovascular epigenome and its association with dementia.	Ziegler KC et al.	—	2026	→
A burden of rare copy number variants in obsessive-compulsive disorder.	Halvorsen MW et al.	—	2025	→
A genome-wide association study integrated with single-cell and bulk profiles uncovers susceptibility genes for nasopharyngeal carcinoma involved in tumorigenesis via regulation of T cells.	Wang TM et al.	—	2025	→
Are oligodendrocytes bystanders or drivers of Parkinson's disease pathology?	Salazar Campos JM et al.	—	2025	→
Cell-weighted polygenic risk scores are associated with β-amyloid and tau biomarkers in Alzheimer's disease.	Kumar A et al.	—	2025	→
CHAS infers cell type-specific signatures in bulk brain histone acetylation studies of neurological and psychiatric disorders.	Murphy KB et al.	—	2025	→
Connecting genomic results for psychiatric disorders to human brain cell types and regions reveals convergence with functional connectivity.	Yao S et al.	—	2025	→
Copy number variants and the tangential expansion of the cerebral cortex.	Liao Z et al.	—	2025	→
Cortical Single-Cell Primers of Abnormal Brain Activity in Parkinson's Disease.	Mirzac D et al.	—	2025	→
Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression.	Li Y et al.	—	2025	→
Decoding crops one cell at a time: from cell atlases to single-cell genetics.	Zhang H et al.	—	2025	→
Determinants of pleiotropy and monotonic gene dosage responses across human traits	Kazem S et al.	—	2025	—
Disentangling associations between complex traits and cell types with seismic.	Lai Q et al.	—	2025	→
Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease.	Trenkwalder T et al.	—	2025	→
Dysregulated synaptic gene expression in oligodendrocytes of spinal and bulbar muscular atrophy.	Iida M et al.	—	2025	→
Evidence for divergent cortical organisation in Parkinson's disease and Lewy Body Dementia.	Zarkali A et al.	—	2025	→
Functional genomics of human skeletal development and the patterning of height heritability.	Richard D et al.	—	2025	→
Gene-level analysis reveals the genetic aetiology and therapeutic targets of schizophrenia.	Dang X et al.	—	2025	→
Genetic Analysis of Retinal Cell Types in Neuropsychiatric Disorders.	Boudriot E et al.	—	2025	→
Genetic risk for neurodegenerative conditions is linked to disease-specific microglial pathways.	Askarova A et al.	—	2025	→
Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder.	Strom NI et al.	—	2025	→
Genome-Wide Association Study Meta-Analysis of 9619 Cases With Tic Disorders.	Strom NI et al.	—	2025	→
Glial cell crosstalk in Parkinson's disease: Mechanisms, implications, and therapeutic strategies.	Wang N et al.	—	2025	→
Integrating microbial GWAS and single-cell transcriptomics reveals associations between host cell populations and the gut microbiome.	Li J et al.	—	2025	→
Integrative multi-omics data from early development to identify the genes and cell types underlying attention-deficit/hyperactivity disorder.	Jiao S et al.	—	2025	→
Interactions of Oligodendrocyte Precursor Cells and Dopaminergic Neurons in the Mouse Substantia Nigra.	Fitzgerald JC et al.	—	2025	→
Mapping striatal functional gradients and associated gene expression in Parkinson's disease with continuous cognitive impairment.	Li X et al.	—	2025	→
Mapping the cellular etiology of schizophrenia and complex brain phenotypes.	Duncan LE et al.	—	2025	→
Mapping the neural and molecular basis underlying fatigue in Parkinson's disease.	Yang F et al.	—	2025	→
Mitochondrial FIS1 As a Novel Drug Target for the Treatment of Erectile Dysfunction: A Multi-Omic and Epigenomic Association Study.	Zhu T et al.	—	2025	→
Modulation of OPC Mitochondrial Function by Inhibiting USP30 Promotes Their Differentiation.	Soung AL et al.	—	2025	→
Neuropathological stages of neuronal, astrocytic and oligodendrocytic alpha-synuclein pathology in Parkinson's disease.	Otero-Jimenez M et al.	—	2025	→
Oligodendrocytes drive neuroinflammation and neurodegeneration in Parkinson's disease via the prosaposin-GPR37-IL-6 axis.	Ma Q et al.	—	2025	→
Oligodendroglia in Ageing and Age-Dependent Neurodegenerative Diseases.	Niu J et al.	—	2025	→
Oligodendroglia vulnerability in the human dorsal striatum in Parkinson's disease.	Barba-Reyes JM et al.	—	2025	→
Polygenic enrichment analysis in multi-omics levels identifies cell/tissue specific associations with schizophrenia based on single-cell RNA sequencing data.	Cheng B et al.	—	2025	→
Population-scale cross-disorder atlas of the human prefrontal cortex at single-cell resolution.	Fullard JF et al.	—	2025	→
Protocol for pooled FACS-based CRISPR knockout screening in human iPSC-derived microglia.	Washer SJ et al.	—	2025	→
Rare Copy Number Variants Reveal Critical Cell Types and Periods of Brain Development in Neurodevelopmental Disorders.	Malwade S et al.	—	2025	→
Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus.	Guo X et al.	—	2025	→
Single-cell analysis of Barrett's esophagus and carcinoma reveals cell types conferring risk via genetic predisposition.	Wenzel MC et al.	—	2025	→
Single-Cell and Spatial Multiomics: Applications for Diseases.	Li W et al.	—	2025	→
The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia xenografted into a mouse model of Alzheimer's disease.	Murphy KB et al.	—	2025	→
Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies.	Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Electronic address: andrew.mcintosh@ed.ac.uk et al.	—	2025	→
White matter lesions contribute to motor and non-motor disorders in Parkinson's disease: a critical review.	Jiang YQ et al.	—	2025	→
Wrap it up: myelination of transplanted neurons for repair.	Martínez-Reza MF et al.	—	2025	→
A multi-region single nucleus transcriptomic atlas of Parkinson's disease.	N M P et al.	—	2024	→
Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry.	Benjamin KJM et al.	—	2024	→
An Overview of Epigenetic Changes in the Parkinson's Disease Brain.	Klokkaris A et al.	—	2024	→
A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson's disease-associated glial changes.	Adams L et al.	—	2024	→
Automatic substantia nigra segmentation with Swin-Unet in susceptibility- and T2-weighted imaging: application to Parkinson disease diagnosis.	Wang T et al.	—	2024	→
Axonal Lysosomal Assays for Characterizing the Effects of LRRK2 G2019S.	Bhatia P et al.	—	2024	→
Contrasting Iron Metabolism in Undifferentiated Versus Differentiated MO3.13 Oligodendrocytes via IL-1β-Induced Iron Regulatory Protein 1.	Yang J et al.	—	2024	→
Decoding the mosaic of inflammatory bowel disease: Illuminating insights with single-cell RNA technology.	Liu L et al.	—	2024	→
Dissecting the shared genetic architecture between endometriosis and polycystic ovary syndrome.	Tan H et al.	—	2024	→
Distinct biological signature and modifiable risk factors underlie the comorbidity between major depressive disorder and cardiovascular disease.	Bergstedt J et al.	—	2024	→
Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions.	Pak V et al.	—	2024	→
Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes.	Huguet G et al.	—	2024	→
Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions.	Choi HK et al.	—	2024	→
FANS Unfixed: Isolation and Proteomic Analysis of Mouse Cell Type-Specific Brain Nuclei.	Bedwell L et al.	—	2024	→
From genetic associations to genes: methods, applications, and challenges.	Qi T et al.	—	2024	→
Functional classes of SNPs related to psychiatric disorders and behavioral traits contrast with those related to neurological disorders.	Reimers MA et al.	—	2024	→
Genetic Implication of Prenatal GABAergic and Cholinergic Neuron Development in Susceptibility to Schizophrenia.	Cameron D et al.	—	2024	→
Genetic Implication of Specific Glutamatergic Neurons of the Prefrontal Cortex in the Pathophysiology of Schizophrenia.	Tume CE et al.	—	2024	→
Genetic variants for head size share genes and pathways with cancer.	Knol MJ et al.	—	2024	→
High-resolution omics of vascular ageing and inflammatory pathways in neurodegeneration.	Kwok AJ et al.	—	2024	→
Interpretation of Neurodegenerative GWAS Risk Alleles in Microglia and their Interplay with Other Cell Types.	Holtman IR et al.	—	2024	→
Investigating the mechanisms of inflammation and immune alterations in Parkinson's disease using spatial transcriptomics techniques.	Zhang S et al.	—	2024	→
Leucine-Rich Repeat Kinase-2 Controls the Differentiation and Maturation of Oligodendrocytes in Mice and Zebrafish.	Filippini A et al.	—	2024	→
Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.	Kim SS et al.	—	2024	→
Molecular profiling of human substantia nigra identifies diverse neuron types associated with vulnerability in Parkinson's disease.	Wang Q et al.	—	2024	→
Nerve-Glial antigen 2: unmasking the enigmatic cellular identity in the central nervous system.	Bottero M et al.	—	2024	→
Primary cartilage transcriptional signatures reflect cell-type-specific molecular pathways underpinning osteoarthritis.	Katsoula G et al.	—	2024	→
Schizophrenia genomics: genetic complexity and functional insights.	Sullivan PF et al.	—	2024	→
Single-cell sequencing insights into the transcriptional landscape of Parkinson's disease.	Su Y et al.	—	2024	→
Single-cell transcriptomics analysis of cellular heterogeneity and immune mechanisms in neurodegenerative diseases.	He Z et al.	—	2024	→
SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.	Liu W et al.	—	2024	→
⍺-Synuclein levels in Parkinson's disease - Cell types and forms that contribute to pathogenesis.	Sagredo GT et al.	—	2024	→
The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases.	Koebbe LL et al.	—	2024	→
Transcriptomic changes in oligodendrocytes and precursor cells associate with clinical outcomes of Parkinson's disease.	Dehestani M et al.	—	2024	→
Unveiling the Genetic Mechanism of Meat Color in Pigs through GWAS, Multi-Tissue, and Single-Cell Transcriptome Signatures Exploration.	Liu C et al.	—	2024	→
150 risk variants for diverticular disease of intestine prioritize cell types and enable polygenic prediction of disease susceptibility.	Wu Y et al.	—	2023	→
Alpha-Synuclein Contribution to Neuronal and Glial Damage in Parkinson's Disease.	Saramowicz K et al.	—	2023	→
An analytical framework for decoding cell type-specific genetic variation of gene regulation.	Xiao Y et al.	—	2023	→
Association between the LRP1B and APOE loci and the development of Parkinson's disease dementia.	Real R et al.	—	2023	→
Blood transcriptomic signatures associated with molecular changes in the brain and clinical outcomes in Parkinson's disease.	Irmady K et al.	—	2023	→
Brain Proteome-Wide and Transcriptome-Wide Asso-ciation Studies, Bayesian Colocalization, and Mendelian Randomization Analyses Reveal Causal Genes of Parkinson's Disease.	Zhou S et al.	—	2023	→
CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation.	Li P et al.	—	2023	→
Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease.	Yang HS et al.	—	2023	→
Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing.	Kim B et al.	—	2023	→
Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes.	Warrier V et al.	—	2023	→
Genetic insights into immune mechanisms of Alzheimer's and Parkinson's disease.	Nott A et al.	—	2023	→
Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses.	Wu Y et al.	—	2023	→
Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population.	Xue H et al.	—	2023	→
Identification of brain cell types underlying genetic association with word reading and correlated traits.	Price KM et al.	—	2023	→
<i>In vitro</i> modeling of the neurobiological effects of glucocorticoids: A review.	Bassil K et al.	—	2023	→
Insights into Neurodegeneration in Parkinson's Disease from Single-Cell and Spatial Genomics.	Kamath T et al.	—	2023	→
Integrative genetic and single cell RNA sequencing analysis provides new clues to the amyotrophic lateral sclerosis neurodegeneration.	Liu H et al.	—	2023	→
Iron Overload Causes Ferroptosis But Not Apoptosis in MO3.13 Oligodendrocytes.	Li Y et al.	—	2023	→
Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease.	Tsalenchuk M et al.	—	2023	→
Locus for severity implicates CNS resilience in progression of multiple sclerosis.	International Multiple Sclerosis Genetics Consortium et al.	—	2023	→
mBAT-combo: A more powerful test to detect gene-trait associations from GWAS data.	Li A et al.	—	2023	→
Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression.	Guintivano J et al.	—	2023	→
Modeling tissue co-regulation estimates tissue-specific contributions to disease.	Amariuta T et al.	—	2023	→
Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus.	Khunsriraksakul C et al.	—	2023	→
Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing.	Chen F et al.	—	2023	→
Neurodegeneration cell per cell.	Balusu S et al.	—	2023	→
Neuropathology of incidental Lewy body & prodromal Parkinson's disease.	Koeglsperger T et al.	—	2023	→
Pathological potential of oligodendrocyte precursor cells: terra incognita.	Yi C et al.	—	2023	→
Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data.	Ma Y et al.	—	2023	→
Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues.	Zhao X et al.	—	2023	→
PRSet: Pathway-based polygenic risk score analyses and software.	Choi SW et al.	—	2023	→
Sex, myelin, and clinical characteristics of Parkinson's disease.	Cai J et al.	—	2023	→
Sex Significantly Impacts the Function of Major Depression-Linked Variants In Vivo.	Mulvey B et al.	—	2023	→
Single-Cell Sequencing in Neurodegenerative Disorders.	Pozojevic J et al.	—	2023	→
Single-Nuclei RNA Sequencing of 5 Regions of the Human Prenatal Brain Implicates Developing Neuron Populations in Genetic Risk for Schizophrenia.	Cameron D et al.	—	2023	→
The Brain Cells That Make Us Uniquely Human.	Abrams Z	—	2023	→
The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism.	Bressan E et al.	—	2023	→
The molecular cytoarchitecture of the adult mouse brain.	Langlieb J et al.	—	2023	→
Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches.	Chehimi SN et al.	—	2023	→
White matter changes in Parkinson's disease.	Yang K et al.	—	2023	→
A Multi-sequence MRI Study in Parkinson's Disease: Association Between Rigidity and Myelin.	Cai J et al.	—	2022	→
Association of a common genetic variant with Parkinson's disease is mediated by microglia.	Langston RG et al.	—	2022	→
Cell-Cell Communication Alterations <i>via</i> Intercellular Signaling Pathways in Substantia Nigra of Parkinson's Disease.	Huang M et al.	—	2022	→
Cell transcriptomic atlas of the non-human primate Macaca fascicularis.	Han L et al.	—	2022	→
Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders.	Olislagers M et al.	—	2022	→
Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways.	Ferraro F et al.	—	2022	→
CRISPR/Cas9-Based Functional Genomics in Human Induced Pluripotent Stem Cell-Derived Models: Can "the Stars Align" for Neurodegenerative Diseases?	Chen Y et al.	—	2022	→
Dissection of the polygenic architecture of neuronal Aβ production using a large sample of individual iPSC lines derived from Alzheimer's disease patients.	Kondo T et al.	—	2022	→
EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing.	Wang R et al.	—	2022	→
Ferroptosis in Parkinson's disease: glia-neuron crosstalk.	Wang ZL et al.	—	2022	→
Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants.	Schilder BM et al.	—	2022	→
From cradle to grave: neurogenesis, neuroregeneration and neurodegeneration in Alzheimer's and Parkinson's diseases.	Wakhloo D et al.	—	2022	→
Fucoxanthin Prevents Long-Term Administration l-DOPA-Induced Neurotoxicity through the ERK/JNK-c-Jun System in 6-OHDA-Lesioned Mice and PC12 Cells.	Liu J et al.	—	2022	→
Functions and dysfunctions of oligodendrocytes in neurodegenerative diseases.	Han S et al.	—	2022	→
Gene expression changes following chronic antipsychotic exposure in single cells from mouse striatum.	Abrantes A et al.	—	2022	→
Genetic diversity fuels gene discovery for tobacco and alcohol use.	Saunders GRB et al.	—	2022	→
Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.	Trpchevska N et al.	—	2022	→
Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects.	Krohn L et al.	—	2022	→
Genome-wide association study of the human brain functional connectome reveals strong vascular component underlying global network efficiency.	Bell S et al.	—	2022	→
Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis.	Zhang S et al.	—	2022	→
Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics.	Jagadeesh KA et al.	—	2022	→
Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19.	Ma Y et al.	—	2022	→
Integration of Distinct Analysis Strategies Improves Tissue-Trait Association Identification.	Yang Z et al.	—	2022	→
Mapping genomic loci implicates genes and synaptic biology in schizophrenia.	Trubetskoy V et al.	—	2022	→
Mesoscale connections and gene expression empower whole-brain modeling of α-synuclein spread, aggregation, and decay dynamics.	Dadgar-Kiani E et al.	—	2022	→
Mitochondrial dysfunction is a key pathological driver of early stage Parkinson's.	Toomey CE et al.	—	2022	→
Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms.	Schilder BM et al.	—	2022	→
Myelin-associated oligodendrocyte basic protein rs616147 polymorphism as a risk factor for Parkinson's disease.	Siokas V et al.	—	2022	→
Oligodendrocytes and myelin: Active players in neurodegenerative brains?	Chen JF et al.	—	2022	→
Parkinson's disease and multiple system atrophy patient iPSC-derived oligodendrocytes exhibit alpha-synuclein-induced changes in maturation and immune reactive properties.	Azevedo C et al.	—	2022	→
Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data.	Zhang MJ et al.	—	2022	→
Recent Developments in Autism Genetic Research: A Scientometric Review from 2018 to 2022.	Lim M et al.	—	2022	→
Redefining the hypotheses driving Parkinson's diseases research.	Farrow SL et al.	—	2022	→
scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies.	Jia P et al.	—	2022	→
Similarities and differences between nigral and enteric dopaminergic neurons unravel distinctive involvement in Parkinson's disease.	Chalazonitis A et al.	—	2022	→
Single-cell analysis of gene expression in the substantia nigra pars compacta of a pesticide-induced mouse model of Parkinson's disease.	Khan AH et al.	—	2022	→
Single-Cell Chromatin Accessibility Data Combined with GWAS Improves Detection of Relevant Cell Types in 59 Complex Phenotypes.	Das AC et al.	—	2022	→
Single-cell genomic profiling of human dopamine neurons identifies a population that selectively degenerates in Parkinson's disease.	Kamath T et al.	—	2022	→
Single-cell sequencing of human midbrain reveals glial activation and a Parkinson-specific neuronal state.	Smajić S et al.	—	2022	→
Single-cell transcriptomics defines an improved, validated monoculture protocol for differentiation of human iPSC to microglia.	Washer SJ et al.	—	2022	→
Single-nucleus chromatin accessibility profiling highlights distinct astrocyte signatures in progressive supranuclear palsy and corticobasal degeneration.	Briel N et al.	—	2022	→
The Emerging Role of Central and Peripheral Immune Systems in Neurodegenerative Diseases.	Zang X et al.	—	2022	→
Transcription factor protein interactomes reveal genetic determinants in heart disease.	Gonzalez-Teran B et al.	—	2022	→
Transcriptomic architecture of nuclei in the marmoset CNS.	Lin JP et al.	—	2022	→
Transient regulation of focal adhesion via Tensin3 is required for nascent oligodendrocyte differentiation.	Merour E et al.	—	2022	→
Ultra-rare and common genetic variant analysis converge to implicate negative selection and neuronal processes in the aetiology of schizophrenia.	Akingbuwa WA et al.	—	2022	→
Understanding Regulatory Mechanisms of Brain Function and Disease through 3D Genome Organization.	Liu W et al.	—	2022	→
Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.	Sandor C et al.	—	2022	→
Virtual Ontogeny of Cortical Growth Preceding Mental Illness.	Patel Y et al.	—	2022	→
What have we learned from genome-wide association studies (GWAS) in Parkinson's disease?	Fernández-Santiago R et al.	—	2022	→
A bioinformatic study revealed serotonergic neurons are involved in the etiology and therapygenetics of anxiety disorders.	Liu HK et al.	—	2021	→
Adult-onset CNS myelin sulfatide deficiency is sufficient to cause Alzheimer's disease-like neuroinflammation and cognitive impairment.	Qiu S et al.	—	2021	→
A Multilevel View of the Development of Alzheimer's Disease.	Avila J et al.	—	2021	→
Amyotrophic Lateral Sclerosis (ALS): Stressed by Dysfunctional Mitochondria-Endoplasmic Reticulum Contacts (MERCs).	Chen J et al.	—	2021	→
Cerebrospinal fluid proteomics targeted for central nervous system processes in bipolar disorder.	Göteson A et al.	—	2021	→
Cross-platform transcriptional profiling identifies common and distinct molecular pathologies in Lewy body diseases.	Feleke R et al.	—	2021	→
Dissecting the non-neuronal cell contribution to Parkinson's disease pathogenesis using induced pluripotent stem cells.	Pons-Espinal M et al.	—	2021	→
Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation.	Rao S et al.	—	2021	→
Effect of TO901317 on GF to promote the differentiation of human bone marrow mesenchymal stem cells into dopamine neurons on Parkinson's disease.	Li M et al.	—	2021	→
Enabling reproducible re-analysis of single-cell data.	Skinnider MA et al.	—	2021	→
Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture.	Chia R et al.	—	2021	→
Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia.	Liu J et al.	—	2021	→
Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.	Mullins N et al.	—	2021	→
Genome-Wide Meta-Analysis Identifies Two Novel Risk Loci for Epilepsy.	Song M et al.	—	2021	→
GP2: The Global Parkinson's Genetics Program.	Global Parkinson's Genetics Program	—	2021	→
Integration of functional genomics data to uncover cell type-specific pathways affected in Parkinson's disease.	Volpato V	—	2021	→
Investigating the shared genetic architecture between multiple sclerosis and inflammatory bowel diseases.	Yang Y et al.	—	2021	→
Ion mobility-based sterolomics reveals spatially and temporally distinctive sterol lipids in the mouse brain.	Li T et al.	—	2021	→
Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity.	Ho D et al.	—	2021	→
Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights.	Sánchez JA et al.	—	2021	→
Molecular Mechanisms Underlying Synaptic and Axon Degeneration in Parkinson's Disease.	Gcwensa NZ et al.	—	2021	→
NANOTECHNOLOGY-MEDIATED THERAPEUTIC STRATEGIES AGAINST SYNUCLEINOPATHIES IN NEURODEGENERATIVE DISEASE.	Schlichtmann BW et al.	—	2021	→
Oligodendrocytes, a New Player in the Etiology of Parkinson's Disease.	Errea O et al.	—	2021	→
Oxidative stress and impaired oligodendrocyte precursor cell differentiation in neurological disorders.	Spaas J et al.	—	2021	→
Single-Cell RNA Sequencing in Parkinson's Disease.	Ma SX et al.	—	2021	→
Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain.	Tran MN et al.	—	2021	→
The dark side of the brain, myelinating glia in central and peripheral nervous systems.	Chrast R et al.	—	2021	→
Total genetic contribution assessment across the human genome.	Li T et al.	—	2021	→
Transcriptome-Wide Association Study Provides Insights Into the Genetic Component of Gene Expression in Anxiety.	Su X et al.	—	2021	→
Utilising Induced Pluripotent Stem Cells in Neurodegenerative Disease Research: Focus on Glia.	Albert K et al.	—	2021	→
Variation on a theme: mapping microglial heterogeneity.	Washer SJ et al.	—	2021	→
Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.	Writing Committee for the Attention-Deficit/Hyperactivity Disorder et al.	—	2021	→
A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders.	Agarwal D et al.	—	2020	→
Cerebral small vessel disease genomics and its implications across the lifespan.	Sargurupremraj M et al.	—	2020	→
Comparative proteomic analysis highlights metabolic dysfunction in α-synucleinopathy.	Sarkar S et al.	—	2020	→
Dementia risk in Parkinson's disease is associated with interhemispheric connectivity loss and determined by regional gene expression.	Zarkali A et al.	—	2020	→
Differences in network controllability and regional gene expression underlie hallucinations in Parkinson's disease.	Zarkali A et al.	—	2020	→
Dysfunction of the Microbiota-Gut-Brain Axis in Neurodegenerative Disease: The Promise of Therapeutic Modulation With Prebiotics, Medicinal Herbs, Probiotics, and Synbiotics.	Peterson CT	—	2020	→
Genetic mapping of etiologic brain cell types for obesity.	Timshel PN et al.	—	2020	→
Genetic Risk Profiling in Parkinson's Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways.	Hall A et al.	—	2020	→
Genomics at cellular resolution: insights into cognitive disorders and their evolution.	Berto S et al.	—	2020	→
Large-scale pathway specific polygenic risk and transcriptomic community network analysis identifies novel functional pathways in Parkinson disease.	Bandres-Ciga S et al.	—	2020	→
Molecular neuroanatomy of anorexia nervosa.	Howard D et al.	—	2020	→
Patient-Derived Midbrain Organoids to Explore the Molecular Basis of Parkinson's Disease.	Galet B et al.	—	2020	→
The genetic architecture of Parkinson's disease.	Blauwendraat C et al.	—	2020	→
Informing disease modelling with brain-relevant functional genomic annotations.	Reynolds RH et al.	—	2019	→
Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration.	Menon M et al.	—	2019	→
Uncovering the Genetic Architecture of Major Depression.	McIntosh AM et al.	—	2019	→