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Gain-of-function (GOF) variants give rise to increased/novel protein functions whereas loss-of-function (LOF) variants lead to diminished protein function. Experimental approaches for identifying GOF and LOF are generally slow and costly, whilst available computational methods have not been optimized to discriminate between GOF and LOF variants. We have developed LoGoFunc, a machine learning method for predicting pathogenic GOF, pathogenic LOF, and neutral genetic variants, trained on a broad range of gene-, protein-, and variant-level features describing diverse biological characteristics. LoGoFunc outperforms other tools trained solely to predict pathogenicity for identifying pathogenic GOF and LOF variants and is available at https://itanlab.shinyapps.io/goflof/ .

Over the last decade next generation sequencing (NGS) has been extensively used to identify new pathogenic mutations and genes causing rare genetic diseases. The efficient analyses of NGS data is not trivial and requires a technically and biologically rigorous pipeline that addresses data quality control, accurate variant filtration to minimize false positives and false negatives, and prioritization of the remaining genes based on disease genomics and physiological knowledge. This review provides a pipeline including all these steps, describes popular software for each step of the analysis, and proposes a general framework for the identification of causal mutations and genes in individual patients of rare genetic diseases.

Background Congenital heart disease (CHD) affects ~ 1% of live births and is the most common birth defect. Although the genetic contribution to the CHD has been long suspected, it has only been well established recently. De novo variants are estimated to contribute to approximately 8% of sporadic CHD. Methods CHD is genetically heterogeneous, making pathway enrichment analysis an effective approach to explore and statistically validate CHD-associated genes. In this study, we performed novel gene and pathway enrichment analyses of high-impact de novo variants in the recently published whole-exome sequencing (WES) data generated from a cohort of CHD 2645 parent-offspring trios to identify new CHD-causing candidate genes and mutations. We performed rigorous variant- and gene-level filtrations to identify potentially damaging variants, followed by enrichment analyses and gene prioritization. Results Our analyses revealed 23 novel genes that are likely to cause CHD, including HSP90AA1 , ROCK2 , IQGAP1 , and CHD4 , and sharing biological functions, pathways, molecular interactions, and properties with known CHD-causing genes. Conclusions Ultimately, these findings suggest novel genes that are likely to be contributing to CHD pathogenesis.

Gain-of-function (GOF) variants give rise to increased or novel protein functions whereas loss-of-function (LOF) variants lead to diminished protein function. GOF and LOF variants can result in markedly varying phenotypes, even when occurring in the same gene. However, experimental approaches for identifying GOF and LOF are generally slow and costly, whilst currently available computational methods have not been optimized to discriminate between GOF and LOF variants. We have developed LoGoFunc, an ensemble machine learning method for predicting pathogenic GOF, pathogenic LOF, and neutral genetic variants. LoGoFunc was trained on a broad range of gene-, protein-, and variant-level features describing diverse biological characteristics, as well as network features summarizing the protein-protein interactome and structural features calculated from AlphaFold2 protein models. We analyzed GOF, LOF, and neutral variants in terms of local protein structure and function, splicing disruption, and phenotypic associations, thereby revealing previously unreported relationships between various biological phenomena and variant functional outcomes. For example, GOF and LOF variants exhibit contrasting enrichments in protein structural and functional regions, whilst LOF variants are more likely to disrupt canonical splicing as indicated by splicing-related features employed by the model. Further, by performing phenome-wide association studies (PheWAS), we identified strong associations between relevant phenotypes and high-confidence predicted GOF and LOF variants. LoGoFunc outperforms other tools trained solely to predict pathogenicity or general variant impact for the identification of pathogenic GOF and LOF variants.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Classifier updated to include features derived from AlphaFold2. Additional precalculated predictions for missense variants added.

Epilepsy (EP) and congenital heart disease (CHD) are two apparently unrelated diseases that nevertheless display substantial mutual comorbidity. Thus, while congenital heart defects are associated with an elevated risk of developing epilepsy, the incidence of epilepsy in CHD patients correlates with CHD severity. Although genetic determinants have been postulated to underlie the comorbidity of EP and CHD, the precise genetic etiology is unknown. We performed variant and gene association analyses on EP and CHD patients separately, using whole exomes of genetically identified Europeans from the UK Biobank and Mount Sinai BioMe Biobank. We prioritized biologically plausible candidate genes and investigated the enriched pathways and other identified comorbidities by biological proximity calculation, pathway analyses, and gene-level phenome-wide association studies. Our variant- and gene-level results point to the Voltage-Gated Calcium Channels (VGCC) pathway as being a unifying framework for EP and CHD comorbidity. Additionally, pathway-level analyses indicated that the functions of disease-associated genes partially overlap between the two disease entities. Finally, phenome-wide association analyses of prioritized candidate genes revealed that cerebral blood flow and ulcerative colitis constitute the two main traits associated with both EP and CHD.

Inflammatory bowel disease (IBD) is a group of chronic digestive tract inflammatory conditions whose genetic etiology is still poorly understood. The incidence of IBD is particularly high among Ashkenazi Jews. Here, we identify 8 novel and plausible IBD-causing genes from the exomes of 4453 genetically identified Ashkenazi Jewish IBD cases (1734) and controls (2719). Various biological pathway analyses are performed, along with bulk and single-cell RNA sequencing, to demonstrate the likely physiological relatedness of the novel genes to IBD. Importantly, we demonstrate that the rare and high impact genetic architecture of Ashkenazi Jewish adult IBD displays significant overlap with very early onset-IBD genetics. Moreover, by performing biobank phenome-wide analyses, we find that IBD genes have pleiotropic effects that involve other immune responses. Finally, we show that polygenic risk score analyses based on genome-wide high impact variants have high power to predict IBD susceptibility. Inflammatory bowel disease (IBD) is highly prevalent among the Ashkenazi Jewish population. Here, the authors identify novel IBD-associated variants and genes, validated by transcriptomic and phenome-wide associations.

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Chronic stress induces changes in the periphery and the central nervous system (CNS) that contribute to neuropathology and behavioral abnormalities associated with psychiatric disorders. In this study, we examined the impact of peripheral and central inflammation during chronic social defeat stress (CSDS) in female mice. Compared to male mice, we found that female mice exhibited heightened peripheral inflammatory response and identified C-C motif chemokine ligand 5 (CCL5), as a stress-susceptibility marker in females. Blocking CCL5 signaling in the periphery promoted resilience to CSDS. In the brain, stress-susceptible mice displayed increased expression of C-C chemokine receptor 5 (CCR5), a receptor for CCL5, in microglia in the prefrontal cortex (PFC). This upregulation was associated with microglia morphological changes, their increased migration to the blood vessels, and enhanced phagocytosis of synaptic components and vascular material. These changes coincided with neurophysiological alterations and impaired blood-brain barrier (BBB) integrity. By blocking CCR5 signaling specifically in the PFC were able to prevent stress-induced physiological changes and rescue social avoidance behavior. Our findings are the first to demonstrate that stress-mediated dysregulation of the CCL5-CCR5 axis triggers excessive phagocytosis of synaptic materials and neurovascular components by microglia, resulting in disruptions in neurotransmission, reduced BBB integrity, and increased stress susceptibility. Our study provides new insights into the role of cortical microglia in female stress susceptibility and suggests that the CCL5-CCR5 axis may serve as a novel sex-specific therapeutic target for treating psychiatric disorders in females.Chronic stress induces changes in the periphery and the central nervous system (CNS) that contribute to neuropathology and behavioral abnormalities associated with psychiatric disorders. In this study, we examined the impact of peripheral and central inflammation during chronic social defeat stress (CSDS) in female mice. Compared to male mice, we found that female mice exhibited heightened peripheral inflammatory response and identified C-C motif chemokine ligand 5 (CCL5), as a stress-susceptibility marker in females. Blocking CCL5 signaling in the periphery promoted resilience to CSDS. In the brain, stress-susceptible mice displayed increased expression of C-C chemokine receptor 5 (CCR5), a receptor for CCL5, in microglia in the prefrontal cortex (PFC). This upregulation was associated with microglia morphological changes, their increased migration to the blood vessels, and enhanced phagocytosis of synaptic components and vascular material. These changes coincided with neurophysiological alterations and impaired blood-brain barrier (BBB) integrity. By blocking CCR5 signaling specifically in the PFC were able to prevent stress-induced physiological changes and rescue social avoidance behavior. Our findings are the first to demonstrate that stress-mediated dysregulation of the CCL5-CCR5 axis triggers excessive phagocytosis of synaptic materials and neurovascular components by microglia, resulting in disruptions in neurotransmission, reduced BBB integrity, and increased stress susceptibility. Our study provides new insights into the role of cortical microglia in female stress susceptibility and suggests that the CCL5-CCR5 axis may serve as a novel sex-specific therapeutic target for treating psychiatric disorders in females.