Improving the diagnostic yield of exome-sequencing, by predicting gene-phenotype associations using large-scale gene expression analysis

Deelen, Patrick; Dam, Sipko van; Herkert, Johanna C.; Karjalainen, Juha; Brugge, Harm; Abbott, Kristin M.; Diemen, Cleo C. van; Zwaag, Paul A. van der; Gerkes, Erica H.; Folkertsma, Pytrik; Gillett, Tessa; Velde, K. Joeri van der; Kanninga, Roan; Akker, Peter C van den; Jan, Sabrina Z.; Hoorntje, Edgar T; Rijdt, Wouter P. te; Vos, Yvonne J.; Jongbloed, Jan D. H.; Ravenswaaij-Arts, Conny M. A. van; Sinke, Richard J.; Sikkema‐Raddatz, Birgit; Kerstjens-Frederikse, Wilhelmina S.; Swertz, Morris A.; Franke, Lude

doi:10.1101/375766

Cited by 50 publications

(89 citation statements)

References 24 publications

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“…13). Furthermore, novel metrics based on gene co-regulation networks can predict whether 357 genes function within a disease relevant pathway 38 . As a cautionary note, including more 358 functional information in the gene-level weights may increase power to detect some novel 359 disorders while decreasing power for disorders with pathophysiology different from known 360 disorders.…”

Section: Modelling Reveals Hundreds Of Dd Genes Remain To Be Discovermentioning

confidence: 99%

Integrating healthcare and research genetic data empowers the discovery of 28 novel developmental disorders

Kaplanis

Samocha

Wiel

et al. 2019

Preprint

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1De novo mutations (DNMs) in protein-coding genes are a well-established cause of 2 developmental disorders (DD). However, known DD-associated genes only account for a 3 minority of the observed excess of such DNMs. To identify novel DD-associated genes, we 4 integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and 5 developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We 6 identified 299 significantly DD-associated genes, including 49 not previously robustly associated 7 with DDs. Despite detecting more DD-associated genes than in any previous study, much of the 8 excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that 9 over 500 novel DD-associated genes await discovery, many of which are likely to be less 10 penetrant than the currently known genes. Research access to clinical diagnostic datasets will 11 be critical for completing the map of dominant DDs. 12 13

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Section: Modelling Reveals Hundreds Of Dd Genes Remain To Be Discovermentioning

confidence: 99%

Integrating healthcare and research genetic data empowers the discovery of 28 novel developmental disorders

Kaplanis

Samocha

Wiel

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Due to the stringent Bonferroni-corrected significance, we relaxed the threshold for pathway analyses since Bonferroni-correction assumes independence and genes tend to be correlated due to co-expression. Gene clustering was done using the GeneNetwork v2.0 RNA sequencing database (N=31,499) 21 . Genes meeting a Bonferroni significance threshold of P= 2.98E-06 (0.30/100,572) was used.…”

Section: Gene-set Analysesmentioning

confidence: 99%

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Liao

Laporte

Spiegelman

et al. 2019

Preprint

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Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental psychiatric disorders. Previous studies have shown that the disorder is highly heritable and associated with several different risk-taking behaviors. Additionally, brain-imaging studies have identified various brain regions such as the cerebellum and frontal cortex to be altered in ADHD.Large genome-wide association studies (GWAS) have identified several loci associated with ADHD. However, understanding the biological relevance of these genetic loci has proven to be difficult. Here, we conducted the largest ADHD transcriptome-wide association study (TWAS) to date consisting of 19,099 cases and 34,194 controls and identified 9 transcriptome-wide significant hits. We successfully demonstrate that several previous GWAS hits can be largely explained by expression. Probabilistic causal fine-mapping of TWAS signals prioritized KAT2B with a posterior probability of 0.467 in the dorsolateral prefrontal cortex and TMEM161B with a posterior probability of 0.838 in the amygdala. Furthermore, pathway enrichments identified dopaminergic and norepinephrine pathways, which are highly relevant for ADHD. Finally, we used the top eQTLs associated with the TWAS genes to identify phenotypes relevant to ADHD and found an inverse genetic correlation with educational attainment and a positive correlation with "ever smoker", maternal smoking at birth, BMI, and schizophrenia. Overall, our findings highlight the power of TWAS to identify novel risk loci and prioritize putatively causal genes.

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“…In the 30-general tissue GTEx v7 and then looked at expression of all brain-relevant regions in GTEx 53 v7. Gene clustering was done using the GeneNetwork v2.0 RNA sequencing database (N=31,499) 25 . Pathway enrichment and gene ontology analyses were also done for GWGAS data.…”

Section: Methodsmentioning

confidence: 99%

Multi-omics integration of the phenome, transcriptome and genome highlights genes and pathways relevant to essential tremor

Liao

Sarayloo

Rochefort

et al. 2019

Preprint

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30The genetic factors predisposing to essential tremor (ET), of one of the most common movement 31 disorders, remains largely unknown. While current studies have examined the contribution of 32 both common and rare genetic variants, very few have investigated the ET transcriptome. To 33 understand pathways and genes relevant to ET, we used an RNA sequencing approach to 34 interrogate the transcriptome of two cerebellar regions, the dentate nucleus and cerebellar cortex, 35 in 16 cases and 16 age-and sex-matched controls. Additionally, a phenome-wide association 36 study (pheWAS) of the dysregulated genes was conducted, and a genome-wide gene association 37 study (GWGAS) was done to identify pathways overlapping with the transcriptomic data. We 38 identified several novel dysregulated genes including CACNA1A, a calcium voltage-gated 39 channel implicated in ataxia. Furthermore, several pathways including axon guidance, olfactory 40 loss, and calcium channel activity were significantly enriched. A subsequent examination of the 41 ET GWGAS data (N=7,154) also flagged genes involved in calcium ion-regulated exocytosis of 42 neurotransmitters to be significantly enriched. Interestingly, the pheWAS identified that the 43 dysregulated gene, SHF, is associated with a blood pressure medication (P=9.3E-08), which is 44 commonly used to reduce tremor in ET patients. Lastly, it is also notable that the dentate nucleus 45 and cerebellar cortex have different transcriptomes, suggesting that different regions of the 46 cerebellum have spatially different transcriptomes. 47

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Improving the diagnostic yield of exome-sequencing, by predicting gene-phenotype associations using large-scale gene expression analysis

Cited by 50 publications

References 24 publications

Integrating healthcare and research genetic data empowers the discovery of 28 novel developmental disorders

Integrating healthcare and research genetic data empowers the discovery of 28 novel developmental disorders

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Multi-omics integration of the phenome, transcriptome and genome highlights genes and pathways relevant to essential tremor

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