Uncovering the Genetic Profiles Underlying the Intrinsic Organization of the Human Cerebellum

Abstract

Decoding the genetic profiles underlying the cerebellar functional organization is critical for uncovering the essential role of the human cerebellum in various high-order functions and malfunctions in neuropsychiatric disorders. However, no effort has been made to systemically address this. By combining transcriptome data with the intrinsic functional connectivity of the human cerebellum, we not only identified 443 network-specific genes but also discovered that their gene co-expression pattern correlated strongly with intra-cerebellar functional connectivity. Of these genes, 90 were also differentially expressed in the cerebral cortex and linked the cortico-cerebellar cognitive-limbic networks. To further discover the biological functions of these genes, we performed a virtual gene knock-out by observing the change in the coupling between gene co-expression and functional connectivity and divided the genes into two subsets, i.e., a positive gene contribution indicator (GCI+) and a negative gene set (GCI-). GCI+ is mainly involved in cerebellar neurodevelopment, while GCI- is related to neurotransmission and is significantly enriched in various neurological and neuropsychiatric disorders that are closely linked the cerebellar functional abnormalities. Collectively, our results provide new insight into the genetic substrates behind the functional organization of the human cerebellum with relevance to the possible mechanism of cerebellar contributions to related neurological and psychiatric disorders.

Cortical morphometric vulnerability to generalised epilepsy reflects chromosome‐ and cell type‐specific transcriptomic signatures

“…Differences in sample characteristics, for example, between the AHBA donors and the participants of our Chinese neuroimaging study, may furthermore require additional caution in interpreting imaging‐genetic findings. Finally, because the significant genes were not identified based on correlations with spatially defined phenotypes but obtained by PLS correlation analyses, the newly proposed strategy [90] that mitigates the bias of leveraging gene enrichment approach in the spatial transcriptomic data could not be directly used [91]. In addition, we used a multi‐gene‐list meta‐analysis to identify the shared and specific pathways between GGE‐related risk genes from GWAS and PLS1 significant genes, which could not be performed by the newly proposed strategy [90].…”

Multimodal Gradient Mapping of Rodent Hippocampus

“…It is possible a GCE variation along the long axis of the hippocampus exists, gradual or parcellated, but is driven by a small number of genes or a specific subset of genes that is not captured in our analysis. A recent study examining the human cerebellum combined the Allen Human Brain Atlas (AHBA) transcriptome data with a cerebellar functional parcellation atlas and found that a majority of the 443 network specific genes were specific in the limbic (n = 170) and visual (n = 221) networks (Wang et al, 2021). Another recent study found that the location of human tissue samples extracted along the hippocampus long axis could be predicted within 2 mm using the expression pattern of less than 100 genes (Vogel et al, 2020), while our analysis included 4376 genes mapped in the AGEA dataset.…”