A cross-disorder dosage sensitivity map of the human genome.

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

NASP gene contributes to autism by epigenetic dysregulation of neural and immune pathways.

BACKGROUND: Epigenetics makes substantial contribution to the aetiology of autism spectrum disorder (ASD) and may harbour a unique opportunity to prevent the development of ASD. We aimed to identify novel epigenetic genes involved in ASD aetiology. METHODS: Trio-based whole exome sequencing was conducted on ASD families. Genome editing technique was used to knock out the candidate causal gene in a relevant cell line. ATAC-seq, ChIP-seq and RNA-seq were performed to investigate the functional impact of knockout (KO) or mutation in the candidate gene. RESULTS: We identified a novel candidate gene NASP (nuclear autoantigenic sperm protein) for epigenetic dysregulation in ASD in a Chinese nuclear family including one proband with autism and comorbid atopic disease. The de novo likely gene disruptive variant tNASP(Q289X) subjects the expression of tNASP to nonsense-mediated decay. tNASP KO increases chromatin accessibility, promotes the active promoter state of genes enriched in synaptic signalling and leads to upregulated expression of genes in the neural signalling and immune signalling pathways. Compared with wild-type tNASP, tNASP(Q289X) enhances chromatin accessibility of the genes with enriched expression in the brain. RNA-seq revealed that genes involved in neural and immune signalling are affected by the tNASP mutation, consistent with the phenotypic impact and molecular effects of nasp-1 mutations in Caenorhabditis elegans. Two additional patients with ASD were found carrying deletion or deleterious mutation in the NASP gene. CONCLUSION: We identified novel epigenetic mechanisms mediated by tNASP which may contribute to the pathogenesis of ASD and its immune comorbidity.

Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency.

BACKGROUND: CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID). OBJECTIVES: This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID. METHODS: The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array. RESULTS: This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4+ T cells to immune stimulation. CONCLUSIONS: Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics.

Genome-wide association study between copy number variation and feeding behavior, feed efficiency, and growth traits in Nellore cattle.

BACKGROUND: Feeding costs represent the largest expenditures in beef production. Therefore, the animal efficiency in converting feed in high-quality protein for human consumption plays a major role in the environmental impact of the beef industry and in the beef producers' profitability. In this context, breeding animals for improved feed efficiency through genomic selection has been considered as a strategic practice in modern breeding programs around the world. Copy number variation (CNV) is a less-studied source of genetic variation that can contribute to phenotypic variability in complex traits. In this context, this study aimed to: (1) identify CNV and CNV regions (CNVRs) in the genome of Nellore cattle (Bos taurus indicus); (2) assess potential associations between the identified CNVR and weaning weight (W210), body weight measured at the time of selection (WSel), average daily gain (ADG), dry matter intake (DMI), residual feed intake (RFI), time spent at the feed bunk (TF), and frequency of visits to the feed bunk (FF); and, (3) perform functional enrichment analyses of the significant CNVR identified for each of the traits evaluated. RESULTS: A total of 3,161 CNVs and 561 CNVRs ranging from 4,973 bp to 3,215,394 bp were identified. The CNVRs covered up to 99,221,894 bp (3.99%) of the Nellore autosomal genome. Seventeen CNVR were significantly associated with dry matter intake and feeding frequency (number of daily visits to the feed bunk). The functional annotation of the associated CNVRs revealed important candidate genes related to metabolism that may be associated with the phenotypic expression of the evaluated traits. Furthermore, Gene Ontology (GO) analyses revealed 19 enrichment processes associated with FF. CONCLUSIONS: A total of 3,161 CNVs and 561 CNVRs were identified and characterized in a Nellore cattle population. Various CNVRs were significantly associated with DMI and FF, indicating that CNVs play an important role in key biological pathways and in the phenotypic expression of feeding behavior and growth traits in Nellore cattle.

Mutation burden analysis of six common mental disorders in African Americans by whole genome sequencing.

Mental disorders present a global health concern and have limited treatment options. In today's medical practice, medications such as antidepressants are prescribed not only for depression but also for conditions such as anxiety and attention deficit hyperactivity disorder (ADHD). Therefore, identifying gene targets for specific disorders is important and offers improved precision. In this study, we performed a genetic analysis of six common mental disorders-ADHD, anxiety, depression, delays in mental development, intellectual disabilities (IDs) and speech/language disorder-in the ethnic minority of African Americans (AAs) using whole genome sequencing (WGS). WGS data were generated from blood-derived DNA from 4178 AA individuals, including 1384 patients with the diagnosis of at least one mental disorder. Mutation burden analysis was applied based on rare and deleterious mutations in the AA population between cases and controls, and further analyzed in the context of patients with single mental disorder diagnosis. Certain genes uncovered demonstrated significant P-values in mutation burden analysis. In addition, exclusive recurrences in specific type of disorder were scanned through gene-drug interaction databases to assess for availability of potential medications. We uncovered 15 genes harboring deleterious mutations, including 3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGCR) and Uronyl 2-Sulfotransferase (UST) for ADHD; Farnesyltransferase, CAAX Box, Beta (FNTB) for anxiety; Xin Actin Binding Repeat Containing 2 (XIRP2), Natriuretic Peptide C (NPPC), Serine/Threonine Kinase 33 (STK33), Pannexin 1 (PANX1) and Neurotensin (NTS) for depression; RUNX Family Transcription Factor 3 (RUNX3), Tachykinin Receptor 1 (TACR1) and NADH:Ubiquinone Oxidoreductase Core Subunit S7 (NDUFS7) for delays in mental development; Hepsin (HPN) for ID and Collagen Type VI Alpha 3 Chain (COL6A3), Damage Specific DNA Binding Protein 1 (DDB1) and NADH:Ubiquinone Oxidoreductase Subunit A11 (NDUFA11) for speech/language disorder. Taken together, we have established critical insights into the development of new precision medicine approaches for mental disorders in AAs.

Secondary ACMG and non-ACMG genetic findings in a multiethnic cohort of 16,713 pediatric participants.

PURPOSE: Clinical next-generation sequencing is an effective approach for identifying pathogenic sequence variants that are medically actionable for participants and families but are not associated with the participant's primary diagnosis. These variants are called secondary findings (SFs). According to the literature, there is no report of the types and frequencies of SFs in a large pediatric cohort that includes substantial African-American participants. We sought to investigate the types (including American College of Medical Genetics and Genomics [ACMG] and non-ACMG-recommended gene lists), frequencies, and rates of SFs, as well as the effects of SF disclosure on the participants and families of a large pediatric cohort at the Center for Applied Genomics at The Children's Hospital of Philadelphia. METHODS: We systematically identified pathogenic (P) and likely pathogenic (LP) variants in established disease-causing genes, adhering to ACMG v3.2 secondary finding guidelines and beyond. For non-ACMG SFs, akin to incidental findings in clinical settings, we utilized a set of criteria focusing on pediatric onset, high penetrance, moderate to severe phenotypes, and the clinical actionability of the variants. This criteria-based approach was applied rather than using a fixed gene list to ensure that the variants identified are likely to affect participant health significantly. To identify and categorize these variants, we used a clinical-grade variant classification standard per ACMG/AMP recommendations; additionally, we conducted a detailed literature search to ensure a comprehensive exploration of potential SFs relevant to pediatric participants. RESULTS: We report a distinctive distribution of 1464 P/LP SF variants in 16,713 participants. There were 427 unique variants in ACMG genes and 265 in non-ACMG genes. The most frequently mutated genes among the ACMG and non-ACMG gene lists were TTR(41.6%) and CHEK2 (7.16%), respectively. Overall, variants of possible medical importance were found in 8.76% of participants in both ACMG (5.81%) and non-ACMG (2.95%) genes. CONCLUSION: Our study revealed that 8.76% of a large, multiethnic pediatric cohort carried actionable secondary genetic findings, with 5.81% in ACMG genes and 2.95% in non-ACMG genes. These findings emphasize the importance of including diverse populations in genetic research to ensure that all groups benefit from early identification of disease risks. Our results provide a foundation for expanding the ACMG gene list and improving clinical care through early interventions.

Revealing novel genomic insights and therapeutic targets for juvenile idiopathic arthritis through omics.

BACKGROUND: The genetic architecture of JIA remains only partially comprehended. There is a clear imperative for continued endeavours to uncover insights into the underlying causes of JIA. METHODS: This study encompassed a comprehensive spectrum of endeavours, including conducting a JIA genome-wide association study (GWAS) meta-analysis that incorporated data from 4550 JIA cases and 18 446 controls. We employed in silico and genome-editing approaches to prioritizing target genes. To investigate pleiotropic effects, we conducted phenome-wide association studies. Cell-type enrichment analyses were performed by integrating bulk and single-cell sequencing data. Finally, we delved into potential druggable targets for JIA. RESULTS: Fourteen genome-wide significant non-HLA loci were identified, including four novel loci, each exhibiting pleiotropic associations with other autoimmune diseases or musculoskeletal traits. We uncovered strong genetic correlation between JIA and BMD traits at 52 genomic regions, including three GWAS loci for JIA. Candidate genes with immune functions were captured by in silico analyses at each novel locus, with additional findings identified through our experimental approach. Cell-type enrichment analysis revealed 21 specific immune cell types crucial for the affected organs in JIA, indicating their potential contribution to the disease. Finally, 24 known or candidate druggable target genes were prioritized. CONCLUSIONS: Our identification of four novel JIA-associated genes, CD247, RHOH, COLEC10 and IRF8, broadens the novel potential drug repositioning opportunities. We established a new genetic link between COLEC10, TNFRSF11B and JIA/BMD. Additionally, the identification of RHOH underscores its role in positive thymocyte selection, thereby illuminating a critical facet of JIA's underlying biological mechanisms.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders.

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Genomic Disorders in CKD across the Lifespan.

SIGNIFICANCE STATEMENT: Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis. BACKGROUND: Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility. METHODS: We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort. RESULTS: We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk. CONCLUSION: Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Genetic architecture of asthma in African American patients.

BACKGROUND: Asthma is a chronic inflammatory disorder with a strong genetic inheritance. Although more than 100 loci were reported through the genome-wide association study of European populations, the genetic underpinning of asthma in African American individuals remains largely elusive. OBJECTIVE: We aimed to identify genetic loci associated with asthma in African American individuals. METHODS: Three cohorts were genotyped at the Children's Hospital of Philadelphia by using the Illumina single-nucleotide polymorphism array platform. Genotype imputation was performed by using the Trans-Omics for Precision Medicine (TOPMed) reference panel, which includes whole genome sequencing data from more than 100,000 individuals. A meta-analysis of 3 Children's Hospital of Philadelphia cohorts and 10 Consortium on Asthma among African Ancestry Populations in the Americas cohorts, totaling 19,628 subjects, was conducted to identify genetic loci associated with asthma in African American individuals. RESULTS: Our study identified 12 loci surpassing the classical genome-wide significance threshold (5 × 10-8). Of those loci, 8 reached the stricter significance threshold (3 × 10-8). The 9p24.1 locus (rs10975467 [P = 1.63 × 10-8]) has previously been associated with asthma in European individuals. Six loci are associated with enhancer activities, 2 loci are in DNase I-hypersensitive regions, and all of them are associated with regulatory motifs. Moreover, the locus 11q13.4 (rs7480008) is an expression quantitative trait locus of XRRA1 in lung (P = 9.4 × 10-10), and the locus 13q14.3 (rs1543525) is a splicing quantitative trait locus of DHRS12 in lung (P = 1.1 × 10-13). CONCLUSIONS: Our findings provide candidate genetic loci for therapeutic target identification and prioritization for African populations.

Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study.

BACKGROUND: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. METHODS: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record-derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. RESULTS: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. CONCLUSIONS: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier; NCT03394859.

Genomic variants exclusively identified in children with birth defects and concurrent malignant tumors predispose to cancer development.

Children with birth defects (BD) express distinct clinical features that often have various medical consequences, one of which is predisposition to the development of cancers. Identification of the underlying genetic mechanisms related to the development of cancer in BD patients would allow for preventive measures. We performed a whole genome sequencing (WGS) study on blood-derived DNA samples from 1566 individuals without chromosomal anomalies, including 454 BD probands with at least one type of malignant tumors, 767 cancer-free BD probands, and 345 healthy individuals. Exclusive recurrent variants were identified in BD-cancer and BD-only patients and mapped to their corresponding genomic regions. We observed statistically significant overlaps for protein-coding/ncRNA with exclusive variants in exons, introns, ncRNAs, and 3'UTR regions. Exclusive exonic variants, especially synonymous variants, tend to occur in prior exons locus in BD-cancer children. Intronic variants close to splicing site (< 500 bp from exon) have little overlaps in BD-cancer and BD-only patients. Exonic variants in non-coding RNA (ncRNA) tend to occur in different ncRNAs exons regardless of the overlaps. Notably, genes with 5' UTR variants are almost mutually exclusive between the two phenotypes. In conclusion, we conducted the first genomic study to explore the impact of recurrent variants exclusive to the two distinguished clinical phenotypes under study, BD with or without cancer, demonstrating enrichment of selective protein-coding/ncRNAs differentially expressed between these two phenotypes, suggesting that selective genetic factors may underlie the molecular processes of pediatric cancer development in BD children.

Biliary atresia is associated with polygenic susceptibility in ciliogenesis and planar polarity effector genes.

BACKGROUND & AIMS: Biliary atresia (BA) is poorly understood and leads to liver transplantation (LT), with the requirement for and associated risks of lifelong immunosuppression, in most children. We performed a genome-wide association study (GWAS) to determine the genetic basis of BA. METHODS: We performed a GWAS in 811 European BA cases treated with LT in US, Canadian and UK centers, and 4,654 genetically matched controls. Whole-genome sequencing of 100 cases evaluated synthetic association with rare variants. Functional studies included whole liver transcriptome analysis of 64 BA cases and perturbations in experimental models. RESULTS: A GWAS of common single nucleotide polymorphisms (SNPs), i.e. allele frequencies >1%, identified intronic SNPs rs6446628 in AFAP1 with genome-wide significance (p = 3.93E-8) and rs34599046 in TUSC3 at sub-threshold genome-wide significance (p = 1.34E-7), both supported by credible peaks of neighboring SNPs. Like other previously reported BA-associated genes, AFAP1 and TUSC3 are ciliogenesis and planar polarity effectors (CPLANE). In gene-set-based GWAS, BA was associated with 6,005 SNPs in 102 CPLANE genes (p = 5.84E-15). Compared with non-CPLANE genes, more CPLANE genes harbored rare variants (allele frequency <1%) that were assigned Human Phenotype Ontology terms related to hepatobiliary anomalies by predictive algorithms, 87% vs. 40%, p <0.0001. Rare variants were present in multiple genes distinct from those with BA-associated common variants in most BA cases. AFAP1 and TUSC3 knockdown blocked ciliogenesis in mouse tracheal cells. Inhibition of ciliogenesis caused biliary dysgenesis in zebrafish. AFAP1 and TUSC3 were expressed in fetal liver organoids, as well as fetal and BA livers, but not in normal or disease-control livers. Integrative analysis of BA-associated variants and liver transcripts revealed abnormal vasculogenesis and epithelial tube formation, explaining portal vein anomalies that co-exist with BA. CONCLUSIONS: BA is associated with polygenic susceptibility in CPLANE genes. Rare variants contribute to polygenic risk in vulnerable pathways via unique genes. IMPACT AND IMPLICATIONS: Liver transplantation is needed to cure most children born with biliary atresia, a poorly understood rare disease. Transplant immunosuppression increases the likelihood of life-threatening infections and cancers. To improve care by preventing this disease and its progression to transplantation, we examined its genetic basis. We find that this disease is associated with both common and rare mutations in highly specialized genes which maintain normal communication and movement of cells, and their organization into bile ducts and blood vessels during early development of the human embryo. Because defects in these genes also cause other birth defects, our findings could lead to preventive strategies to lower the incidence of biliary atresia and potentially other birth defects.

DeepCNV: a deep learning approach for authenticating copy number variations.

Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably high false positive rate. A common practice is to have human experts manually review original CNV calls for filtering false positives before further downstream analysis or experimental validation. Here, we propose DeepCNV, a deep learning-based tool, intended to replace human experts when validating CNV calls, focusing on the calls made by one of the most accurate CNV callers, PennCNV. The sophistication of the deep neural network algorithm is enriched with over 10 000 expert-scored samples that are split into training and testing sets. Variant confidence, especially for CNVs, is a main roadblock impeding the progress of linking CNVs with the disease. We show that DeepCNV adds to the confidence of the CNV calls with an optimal area under the receiver operating characteristic curve of 0.909, exceeding other machine learning methods. The superiority of DeepCNV was also benchmarked and confirmed using an experimental wet-lab validation dataset. We conclude that the improvement obtained by DeepCNV results in significantly fewer false positive results and failures to replicate the CNV association results.

Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients.

Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to complete questionnaires or standardized rating scales for diagnosis. In the past decade, multiple genomic association signals have been reported for mental disorders, some of which present attractive drug targets. Concurrently, machine learning algorithms, especially deep learning algorithms, have been successful in the diagnosis and/or labeling of complex diseases, such as attention deficit hyperactivity disorder (ADHD) or cancer. In this study, we focused on eight common mental disorders, including ADHD, depression, anxiety, autism, intellectual disabilities, speech/language disorder, delays in developments, and oppositional defiant disorder in the ethnic minority of African Americans. Blood-derived whole genome sequencing data from 4179 individuals were generated, including 1384 patients with the diagnosis of at least one mental disorder. The burden of genomic variants in coding/non-coding regions was applied as feature vectors in the deep learning algorithm. Our model showed ~65% accuracy in differentiating patients from controls. Ability to label patients with multiple disorders was similarly successful, with a hamming loss score less than 0.3, while exact diagnostic matches are around 10%. Genes in genomic regions with the highest weights showed enrichment of biological pathways involved in immune responses, antigen/nucleic acid binding, chemokine signaling pathway, and G-protein receptor activities. A noticeable fact is that variants in non-coding regions (e.g., ncRNA, intronic, and intergenic) performed equally well as variants in coding regions; however, unlike coding region variants, variants in non-coding regions do not express genomic hotspots whereas they carry much more narrow standard deviations, indicating they probably serve as alternative markers.

TOPORS as a novel causal gene for Joubert syndrome.

Joubert syndrome (JBTS) is a Mendelian disorder of the primary cilium defined by the clinical triad of hypotonia, developmental delay, and a distinct cerebellar malformation called the molar tooth sign. JBTS is inherited in an autosomal recessive, autosomal dominant, or X-linked recessive manner. Though over 40 genes have been identified as causal for JBTS, molecular diagnosis is not made in 30%-40% of individuals who meet clinical criteria. TOPORS encodes topoisomerase I-binding arginine/serine-rich protein, and homozygosity for a TOPORS missense variant (c.29C > A; p.(Pro10Gln)) was identified in individuals with the ciliopathy oral-facial-digital syndrome in two families of Dominican descent. Here, we report an additional proband of Dominican ancestry with JBTS found by exome sequencing to be homozygous for the identical p.(Pro10Gln) TOPORS missense variant. Query of the Mount Sinai BioMe biobank, which includes 1880 individuals of Dominican ancestry, supports a high carrier frequency of the TOPORS p.(Pro10Gln) variant in individuals of Dominican descent. Our data nominates TOPORS as a novel causal gene for JBTS and suggests that TOPORS variants should be considered in the differential of ciliopathy-spectrum disease in individuals of Dominican ancestry.

A genome-wide association meta-analysis identifies new eosinophilic esophagitis loci.

BACKGROUND: Eosinophilic esophagitis (EoE) is a chronic inflammatory disorder of the esophagus marked by eosinophilic infiltration. Cumulative evidence indicates that the risk of EoE involves the complex interplay of both genetic and environmental factors. Because only a few genetic loci have been identified in EoE, the genetic underpinning of EoE remains largely elusive. OBJECTIVE: We sought to identify genetic loci associated with EoE. METHODS: Four EoE cohorts were genotyped using the Illumina single nucleotide polymorphism array platform, totaling 1,930 cases and 13,634 controls of European ancestry. Genotype imputation was performed with the Michigan Imputation Server using the Trans-Omics for Precision Medicine reference panel including whole-genome sequencing data from more than 100,000 individuals. Meta-analysis was conducted to identify potential novel genetic loci associated with EoE. RESULTS: Our study identified 11 new genome-wide significant loci, of which 6 are common variant loci, including 5q31.1 (rs2106984, P = 4.16 × 10-8; odds ratio [OR], 1.26, RAD50), 15q22.2 (rs2279293, P = 1.23 × 10-10; OR, 0.69, RORA), and 15q23 (rs56062135, P = 2.91 × 10-11; OR, 1.29, SMAD3), which have been previously associated with allergic conditions. Interestingly, a low-frequency synonymous mutation within the MATN2 gene was identified as the most significant single nucleotide polymorphism at the 8q22.1 locus. We also identified 5 sex-specific loci in the EoE cases, including an inflammatory bowel disease-associated locus at 9p24.1 (rs62541556, P = 4.4 × 10-8; OR, 1.11, JAK2). CONCLUSIONS: Our findings demonstrate shared genetic underpinnings between EoE and other immune-mediated diseases and provide novel candidate genes for therapeutic target identification and prioritization.

Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.

BACKGROUND: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.

Genetic analysis for type 1 diabetes genes in juvenile dermatomyositis unveils genetic disease overlap.

OBJECTIVES: JDM is a serious autoimmune and complex genetic disease. Another autoimmune genetic disease, type 1 diabetes (T1D), has been observed for significantly increased prevalence in families with JDM, while increased JDM risk has also been observed in T1D cases. This study aimed to study whether these two autoimmune diseases, JDM and T1D, share common genetic susceptibility. METHODS: From 169 JDM families, 121 unrelated cases with European ancestry (EA) were identified by genome-wide genotyping, principal component analysis and identical-by-descent (IBD) analysis. T1D genetic risk score (GRS) were calculated in these cases and were compared with 361 EA T1D cases and 1943 non-diabetes EA controls. A total of 113 cases of the 121 unrelated European cases were sequenced by whole exome sequencing. RESULTS: We observed increased T1D GRS in JDM cases (P = 9.42E-05). Using whole exome sequencing, we uncovered the T1D genes, phospholipase B1, cystic fibrosis transmembrane conductance regulator, tyrosine hydroxylase, CD6 molecule, perforin 1 and dynein axonemal heavy chain 2, potentially associated with JDM by the burden test of rare functional coding variants. CONCLUSION: Novel mechanisms of JDM related to these T1D genes are suggested by this study, which may imply novel therapeutic targets for JDM and warrant further study.

Metabolomic profiling for dyslipidemia in pediatric patients with sickle cell disease, on behalf of the IHCC consortium.

BACKGROUND: Previous study has shown that dyslipidemia is common in patients with Sickle cell disease (SCD) and is associated with more serious SCD complications. METHODS: This study investigated systematically dyslipidemia in SCD using a state-of-art nuclear magnetic resonance (NMR) metabolomics platform, including 147 pediatric cases with SCD and 1234 controls without SCD. We examined 249 metabolomic biomarkers, including 98 biomarkers for lipoprotein subclasses, 70 biomarkers for relative lipoprotein lipid concentrations, plus biomarkers for fatty acids and phospholipids. RESULTS: Specific patterns of hypolipoproteinemia and hypocholesterolemia in pediatric SCD were observed in lipoprotein subclasses other than larger VLDL subclasses. Triglycerides are not significantly changed in SCD, except increased relative concentrations in lipoprotein subclasses. Decreased plasma FFAs (including total-FA, SFA, PUFA, Omega-6, and linoleic acid) and decreased plasma phospholipids were observed in SCD. CONCLUSION: This study scrutinized, for the first time, lipoprotein subclasses in pediatric patients with SCD, and identified SCD-specific dyslipidemia from altered lipoprotein metabolism. The findings of this study depict a broad panorama of lipid metabolism and nutrition in SCD, suggesting the potential of specific dietary supplementation of the deficient nutrients for the management of SCD.