Rare coding variants as risk modifiers of the 22q11.2 deletion implicate postnatal cortical development in syndromic schizophrenia.

22q11.2 deletion is one of the strongest known genetic risk factors for schizophrenia. Recent whole-genome sequencing of schizophrenia cases and controls with this deletion provided an unprecedented opportunity to identify risk modifying genetic variants and investigate their contribution to the pathogenesis of schizophrenia in 22q11.2 deletion syndrome. Here, we apply a novel analytic framework that integrates gene network and phenotype data to investigate the aggregate effects of rare coding variants and identified modifier genes in this etiologically homogenous cohort (223 schizophrenia cases and 233 controls of European descent). Our analyses revealed significant additive genetic components of rare nonsynonymous variants in 110 modifier genes (adjusted P = 9.4E-04) that overall accounted for 4.6% of the variance in schizophrenia status in this cohort, of which 4.0% was independent of the common polygenic risk for schizophrenia. The modifier genes affected by rare coding variants were enriched with genes involved in synaptic function and developmental disorders. Spatiotemporal transcriptomic analyses identified an enrichment of coexpression between modifier and 22q11.2 genes in cortical brain regions from late infancy to young adulthood. Corresponding gene coexpression modules are enriched with brain-specific protein-protein interactions of SLC25A1, COMT, and PI4KA in the 22q11.2 deletion region. Overall, our study highlights the contribution of rare coding variants to the SCZ risk. They not only complement common variants in disease genetics but also pinpoint brain regions and developmental stages critical to the etiology of syndromic schizophrenia.

Polygenic prediction of human longevity on the supposition of pervasive pleiotropy.

The highly polygenic nature of human longevity renders cross-trait pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between the aging-related traits (ARTs), we sought to model the additive variance in lifespan as a function of cumulative liability from pleiotropic segregating variants. We tracked allele frequency changes as a function of viability across different age bins and prioritized 34 variants with an immediate implication on lipid metabolism, body mass index (BMI), and cognitive performance, among other traits, revealed by PheWAS analysis in the UK Biobank. Given the highly complex and non-linear interactions between the genetic determinants of longevity, we reasoned that a composite polygenic score would approximate a substantial portion of the variance in lifespan and developed the integrated longevity genetic scores (iLGSs) for distinguishing exceptional survival. We showed that coefficients derived from our ensemble model could potentially reveal an interesting pattern of genomic pleiotropy specific to lifespan. We assessed the predictive performance of our model for distinguishing the enrichment of exceptional longevity among long-lived individuals in two replication cohorts and showed that the median lifespan in the highest decile of our composite prognostic index is up to 4.8 years longer. Finally, using the proteomic correlates of iLGS, we identified protein markers associated with exceptional longevity irrespective of chronological age and prioritized drugs with repurposing potentials for gerotherapeutics. Together, our approach demonstrates a promising framework for polygenic modeling of additive liability conferred by ARTs in defining exceptional longevity and assisting the identification of individuals at higher risk of mortality for targeted lifestyle modifications earlier in life. Furthermore, the proteomic signature associated with iLGS highlights the functional pathway upstream of the PI3K-Akt that can be effectively targeted to slow down aging and extend lifespan.

Substance abuse and the risk of severe COVID-19: Mendelian randomization confirms the causal role of opioids but hints a negative causal effect for cannabinoids.

Since the start of the COVID-19 global pandemic, our understanding of the underlying disease mechanism and factors associated with the disease severity has dramatically increased. A recent study investigated the relationship between substance use disorders (SUD) and the risk of severe COVID-19 in the United States and concluded that the risk of hospitalization and death due to COVID-19 is directly correlated with substance abuse, including opioid use disorder (OUD) and cannabis use disorder (CUD). While we found this analysis fascinating, we believe this observation may be biased due to comorbidities (such as hypertension, diabetes, and cardiovascular disease) confounding the direct effect of SUD on severe COVID-19 illness. To answer this question, we sought to investigate the causal relationship between substance abuse and medication-taking history (as a proxy trait for comorbidities) with the risk of COVID-19 adverse outcomes. Our Mendelian randomization analysis confirms the causal relationship between OUD and severe COVID-19 illness but suggests an inverse causal effect for cannabinoids. Considering that COVID-19 mortality is largely attributed to disturbed immune regulation, the possible modulatory impact of cannabinoids in alleviating cytokine storms merits further investigation.

Genomic expansion of Aldh1a1 protects beavers against high metabolic aldehydes from lipid oxidation.

The North American beaver is an exceptionally long-lived and cancer-resistant rodent species. Here, we report the evolutionary changes in its gene coding sequences, copy numbers, and expression. We identify changes that likely increase its ability to detoxify aldehydes, enhance tumor suppression and DNA repair, and alter lipid metabolism, potentially contributing to its longevity and cancer resistance. Hpgd, a tumor suppressor gene, is uniquely duplicated in beavers among rodents, and several genes associated with tumor suppression and longevity are under positive selection in beavers. Lipid metabolism genes show positive selection signals, changes in copy numbers, or altered gene expression in beavers. Aldh1a1, encoding an enzyme for aldehydes detoxification, is particularly notable due to its massive expansion in beavers, which enhances their cellular resistance to ethanol and capacity to metabolize diverse aldehyde substrates from lipid oxidation and their woody diet. We hypothesize that the amplification of Aldh1a1 may contribute to the longevity of beavers.

Deep post-GWAS analysis identifies potential risk genes and risk variants for Alzheimer's disease, providing new insights into its disease mechanisms.

Alzheimer's disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms-e.g., the complement and coagulation cascade and phosphorylation and activation of immune response-and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes-e.g., IL1RAP, PMAIP1, LAMTOR4-as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.

Exome sequencing identifies a disease variant of the mitochondrial ATP-Mg/Pi carrier SLC25A25 in two families with kidney stones.

BACKGROUND: Calcium kidney stones are common and recurrences are often not preventable by available empiric remedies. Their etiology is multifactorial and polygenic, and an increasing number of genes are implicated. Their identification will enable improved management. METHODS: DNA from three stone-formers in a Southampton family (UK) and two from an Italian family were analyzed independently by whole exome sequencing and selected variants were genotyped across all available members of both pedigrees. A disease variant of SLC25A25 (OMIM 608745), encoding the mitochondrial ATP-Mg/Pi carrier 3 (APC3) was identified, and analyzed structurally and functionally with respect to its calcium-regulated transport activity. RESULTS: All five patients had a heterozygous dominant SLC25A25 variant (rs140777921; GRCh37.p13: chr 9 130868670 G>C; p.Gln349His; Reference Sequence NM_001006641.3). Non-stone formers also carried the variant indicating incomplete penetrance. Modeling suggests that the variant lacks a conserved polar interaction, which may cause structural instability. Calcium-regulated ATP transport was reduced to ~20% of the wild type, showing a large reduction in function. CONCLUSION: The transporter is important in regulating mitochondrial ATP production. This rare variant may increase urine lithogenicity through impaired provision of ATP for solute transport processes in the kidney, and/or for purinergic signaling. Variants found in other genes may compound this abnormality.

Rare genetic coding variants associated with human longevity and protection against age-related diseases.

Extreme longevity in humans has a strong genetic component, but whether this involves genetic variation in the same longevity pathways as found in model organisms is unclear. Using whole-exome sequences of a large cohort of Ashkenazi Jewish centenarians to examine enrichment for rare coding variants, we found most longevity-associated rare coding variants converge upon conserved insulin/insulin-like growth factor 1 signaling and AMP-activating protein kinase signaling pathways. Centenarians have a number of pathogenic rare coding variants similar to control individuals, suggesting that rare variants detected in the conserved longevity pathways are protective against age-related pathology. Indeed, we detected a pro-longevity effect of rare coding variants in the Wnt signaling pathway on individuals harboring the known common risk allele APOE4. The genetic component of extreme human longevity constitutes, at least in part, rare coding variants in pathways that protect against aging, including those that control longevity in model organisms.

Molecular insights into the role of AMPA receptors in the synaptic plasticity, pathogenesis and treatment of epilepsy: therapeutic potentials of perampanel and antisense oligonucleotide (ASO) technology.

Glutamate is considered as the predominant excitatory neurotransmitter in the mammalian central nervous systems (CNS). Alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) are the main glutamate-gated ionotropic channels that mediate the majority of fast synaptic excitation in the brain. AMPARs are highly dynamic that constitutively move into and out of the postsynaptic membrane. Changes in the postsynaptic number of AMPARs play a key role in controlling synaptic plasticity and also brain functions such as memory formation and forgetting development. Impairments in the regulation of AMPAR function, trafficking, and signaling pathway may also contribute to neuronal hyperexcitability and epileptogenesis process, which offers AMPAR as a potential target for epilepsy therapy. Over the last decade, various types of AMPAR antagonists such as perampanel and talampanel have been developed to treat epilepsy, but they usually show limited efficacy at low doses and produce unwanted cognitive and motor side effects when administered at higher doses. In the present article, the latest findings in the field of molecular mechanisms controlling AMPAR biology, as well as the role of these mechanism dysfunctions in generating epilepsy will be reviewed. Also, a comprehensive summary of recent findings from clinical trials with perampanel, in treating epilepsy, glioma-associated epilepsy and Parkinson's disease is provided. Finally, antisense oligonucleotide therapy as an alternative strategy for the efficient treatment of epilepsy is discussed.

Gene-dense autosomal chromosomes show evidence for increased selection.

Purifying selection tends to reduce nucleotide and haplotype diversity leading to increased linkage disequilibrium. However, detection of evidence for selection is difficult as the signature is confounded by wide variation in the recombination rate which has a complex relationship with selection. The effective bottleneck time (the ratio of the linkage disequilibrium map to the genetic map in Morgans) controls for variability in the recombination rate. Reduced effective bottleneck times indicate stronger residual linkage disequilibrium, consistent with increased selection. Using whole genome sequence data from one European and three Sub-Saharan African human populations we find, in the African samples, strong correlations between high gene densities and reduced effective bottleneck time for autosomal chromosomes. This suggests that gene-dense autosomes have been subject to increased purifying selection reducing effective bottleneck times compared to gene-poor autosomes. Although previous studies have shown unusually strong linkage disequilibrium for the sex chromosomes variation within the autosomes has not been recognised. The strongest relationship is between effective bottleneck time and the density of essential genes, which are likely targets of greater selective pressure (p = 0.006, for the 22 autosomes). The magnitude of the reduction in chromosome-specific effective bottleneck times from the least to the most gene-dense autosomes is ~17-21% for Sub-Saharan African populations. The effect size is greater in Sub-Saharan African populations, compared to a European sample, consistent with increased efficiency of selection in populations with larger effective population sizes which have not been subject to intense population bottlenecks as experienced by populations of European ancestry. The findings highlight the value of deeper analyses of selection within Sub-Saharan African populations.

Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data.

Quantification of linkage disequilibrium (LD) patterns in the human genome is essential for genome-wide association studies, selection signature mapping and studies of recombination. Whole genome sequence (WGS) data provides optimal source data for this quantification as it is free from biases introduced by the design of array genotyping platforms. The Malécot-Morton model of LD allows the creation of a cumulative map for each choromosome, analogous to an LD form of a linkage map. Here we report LD maps generated from WGS data for a large population of European ancestry, as well as populations of Baganda, Ethiopian and Zulu ancestry. We achieve high average genetic marker densities of 2.3-4.6/kb. These maps show good agreement with prior, low resolution maps and are consistent between populations. Files are provided in BED format to allow researchers to readily utilise this resource.

Understanding the disease genome: gene essentiality and the interplay of selection, recombination and mutation.

Despite the identification of many genetic variants contributing to human disease (the 'disease genome'), establishing reliable molecular diagnoses remain challenging in many cases. The ability to sequence the genomes of patients has been transformative, but difficulty in interpretation of voluminous genetic variation often confounds recognition of underlying causal variants. There are numerous predictors of pathogenicity for individual DNA variants, but their utility is reduced because many plausibly pathogenic variants are probably neutral. The rapidly increasing quantity and quality of information on the properties of genes suggests that gene-specific information might be useful for prediction of causal variation when used alongside variant-specific predictors of pathogenicity. The key to understanding the role of genes in disease relates in part to gene essentiality, which has recently been approximated, for example, by quantifying the degree of intolerance of individual genes to loss-of-function variation. Increasing understanding of the interplay between genetic recombination, selection and mutation and their relationship to gene essentiality suggests that gene-specific information may be useful for the interpretation of sequenced genomes. Considered alongside additional distinctive properties of the disease genome, such as the timing of the evolutionary emergence of genes and the roles of their products in protein networks, the case for using gene-specific measures to guide filtering of sequenced genomes seems strong.

Mutations specific to the Rac-GEF domain of TRIO cause intellectual disability and microcephaly.

BACKGROUND: Neurodevelopmental disorders have challenged clinical genetics for decades, with over 700 genes implicated and many whose function remains unknown. The application of whole-exome sequencing is proving pivotal in closing the genotype/phenotype gap through the discovery of new genes and variants that help to unravel the pathogenic mechanisms driving neuropathogenesis. One such discovery includes TRIO, a gene recently implicated in neurodevelopmental delay. Trio is a Dbl family guanine nucleotide exchange factor (GEF) and a major regulator of neuronal development, controlling actin cytoskeleton dynamics by activating the GTPase Rac1. METHODS: Whole-exome sequencing was undertaken on a family presenting with global developmental delay, microcephaly and mild dysmorphism. Father/daughter exome analysis was performed, followed by confirmatory Sanger sequencing and segregation analysis on four individuals. Three further patients were recruited through the deciphering developmental disorders (DDD) study. Functional studies were undertaken using patient-specific Trio protein mutations. RESULTS: We identified a frameshift deletion in TRIO that segregated autosomal dominantly. By scrutinising data from DDD, we further identified three unrelated children with a similar phenotype who harboured de novo missense mutations in TRIO. Biochemical studies demonstrated that in three out of four families, the Trio mutations led to a markedly reduced Rac1 activation. CONCLUSIONS: We describe an inherited global developmental delay phenotype associated with a frameshift deletion in TRIO. Additionally, we identify pathogenic de novo missense mutations in TRIO associated with the same consistent phenotype, intellectual disability, microcephaly and dysmorphism with striking digital features. We further functionally validate the importance of the GEF domain in Trio protein function. Our study demonstrates how genomic technologies are yet again proving prolific in diagnosing and advancing the understanding of neurodevelopmental disorders.

The role of non-HLA single nucleotide polymorphisms in multiple sclerosis susceptibility.

Multiple sclerosis (MS) is the most common neurological disease of the central nervous system affecting young adults. While the etiology of the disease is still unknown, epidemiological and genetics studies have shown a significant inherited component involved in MS pathogenesis. Single nucleotide polymorphisms (SNPs) associated with MS have been recently evaluated by two main groups of high-throughput genotyping analyses: candidate gene approaches and genome-wide association studies (GWAS). Although both types of studies have identified polymorphisms in the human leukocyte antigen (HLA) region as the strongest susceptibility loci for MS, recent investigations have identified a broad spectrum of non-HLA genes prominently associated with MS. This review will focus on recent findings in non-HLA genes as well as their SNPs which have shown high linkage to MS as a genetic-based disorder. Understanding of non-HLA polymorphisms will help elucidate the signalling aberrations involved in MS development and may help to identify novel, personalized approaches to therapy.