Depletion of loss-of-function germline mutations in centenarians reveals longevity genes.

While previous studies identified common genetic variants associated with longevity in centenarians, the role of the rare loss-of-function (LOF) mutation burden remains largely unexplored. Here, we investigated the burden of rare LOF mutations in Ashkenazi Jewish individuals from the Longevity Genes Project and LonGenity study cohorts using whole-exome sequencing data. We found that centenarians had a significantly lower burden (11-22%) of LOF mutations compared to controls. Similar effects were also observed in their offspring. Gene-level burden analysis identified 35 genes with depleted LOF mutations in centenarians, with 14 of these validated in the UK Biobank. Mendelian randomization and multi-omic analyses on these genes identified RGP1, PCNX2, and ANO9 as longevity genes with consistent causal effects on multiple aging-related traits and altered expression during aging. Our findings suggest that a protective genetic background, characterized by a reduced burden of damaging variants, contributes to exceptional longevity, likely acting in concert with specific protective variants to promote healthy aging.

Ultrarare Variants in DNA Damage Repair Genes in Pediatric Acute-Onset Neuropsychiatric Syndrome or Acute Behavioral Regression in Neurodevelopmental Disorders.

Acute onset of severe psychiatric symptoms or regression may occur in children with premorbid neurodevelopmental disorders, although typically developing children can also be affected. Infections or other stressors are likely triggers. The underlying causes are unclear, but a current hypothesis suggests the convergence of genes that influence neuronal and immunological function. We previously identified 11 genes in Pediatric Acute-Onset Neuropsychiatry Syndrome (PANS), in which two classes of genes related to either synaptic function or the immune system were found. Among the latter, three affect the DNA damage response (DDR): PPM1D, CHK2, and RAG1. We now report an additional 17 cases with mutations in PPM1D and other DDR genes in patients with acute onset of psychiatric symptoms and/or regression that their clinicians classified as PANS or another inflammatory brain condition. The genes include clusters affecting p53 DNA repair (PPM1D, ATM, ATR, 53BP1, and RMRP), and the Fanconi Anemia Complex (FANCE, SLX4/FANCP, FANCA, FANCI, and FANCC). We hypothesize that defects in DNA repair genes, in the context of infection or other stressors, could contribute to decompensated states through an increase in genomic instability with a concomitant accumulation of cytosolic DNA in immune cells triggering DNA sensors, such as cGAS-STING and AIM2 inflammasomes, as well as central deficits on neuroplasticity. In addition, increased senescence and defective apoptosis affecting immunological responses could be playing a role. These compelling preliminary findings motivate further genetic and functional characterization as the downstream impact of DDR deficits may point to novel treatment strategies.

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

The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the 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 (the Scripps Wellderly cohort and the Medical Genome Reference Bank (MRGB)) 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 a 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.

Rare genetic coding variants associated with age-related episodic memory decline implicate distinct memory pathologies in the hippocampus.

Background: Approximately 40% of people aged 65 or older experience memory loss, particularly in episodic memory. Identifying the genetic basis of episodic memory decline is crucial for uncovering its underlying causes. Methods: We investigated common and rare genetic variants associated with episodic memory decline in 742 (632 for rare variants) Ashkenazi Jewish individuals (mean age 75) from the LonGenity study. All-atom MD simulations were performed to uncover mechanistic insights underlying rare variants associated with episodic memory decline. Results: In addition to the common polygenic risk of Alzheimer's Disease (AD), we identified and replicated rare variant association in ITSN1 and CRHR2 . Structural analyses revealed distinct memory pathologies mediated by interfacial rare coding variants such as impaired receptor activation of corticotropin releasing hormone and dysregulated L-serine synthesis. Discussion: Our study uncovers novel risk loci for episodic memory decline. The identified underlying mechanisms point toward heterogeneous memory pathologies mediated by rare coding variants.

Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS.

Congenital heart disease (CHD) affecting the conotruncal region of the heart, occurs in 40-50% of patients with 22q11.2 deletion syndrome (22q11.2DS). This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, encoding a T-box transcription factor, is one of the main genes responsible for the etiology of the syndrome. We suggest that genetic modifiers of conotruncal defects in patients with 22q11.2DS may be in the TBX1 gene network. To identify genetic modifiers, we analyzed rare, predicted damaging variants in whole genome sequence of 456 cases with conotruncal defects and 537 controls, with 22q11.2DS. We then performed gene set approaches and identified chromatin regulatory genes as modifiers. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2DS cases. Many of these genes were identified as risk factors for sporadic CHD in the general population. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. The genes KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models. Our findings indicate that disturbance of chromatin regulatory genes impact the TBX1 gene network serving as genetic modifiers of 22q11.2DS and sporadic CHD, suggesting that there are some shared mechanisms involving the TBX1 gene network in the etiology of CHD.

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.

Protocol for gene annotation, prediction, and validation of genomic gene expansion.

Although gene expansion plays an important role in evolution, its identification remains a challenge due to potential errors in genome assembly and annotation. Here, we describe a detailed step-by-step protocol for gene annotation, prediction of genomic gene expansion, and its computational and experimental validation. Finally, we also detail steps to discover functionality of each copy of replicated genes. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2021).

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.

Enhancer release and retargeting activates disease-susceptibility genes.

The functional engagement between an enhancer and its target promoter ensures precise gene transcription1. Understanding the basis of promoter choice by enhancers has important implications for health and disease. Here we report that functional loss of a preferred promoter can release its partner enhancer to loop to and activate an alternative promoter (or alternative promoters) in the neighbourhood. We refer to this target-switching process as 'enhancer release and retargeting'. Genetic deletion, motif perturbation or mutation, and dCas9-mediated CTCF tethering reveal that promoter choice by an enhancer can be determined by the binding of CTCF at promoters, in a cohesin-dependent manner-consistent with a model of 'enhancer scanning' inside the contact domain. Promoter-associated CTCF shows a lower affinity than that at chromatin domain boundaries and often lacks a preferred motif orientation or a partnering CTCF at the cognate enhancer, suggesting properties distinct from boundary CTCF. Analyses of cancer mutations, data from the GTEx project and risk loci from genome-wide association studies, together with a focused CRISPR interference screen, reveal that enhancer release and retargeting represents an overlooked mechanism that underlies the activation of disease-susceptibility genes, as exemplified by a risk locus for Parkinson's disease (NUCKS1-RAB7L1) and three loci associated with cancer (CLPTM1L-TERT, ZCCHC7-PAX5 and PVT1-MYC).

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.

Beaver and Naked Mole Rat Genomes Reveal Common Paths to Longevity.

Long-lived rodents have become an attractive model for the studies on aging. To understand evolutionary paths to long life, we prepare chromosome-level genome assemblies of the two longest-lived rodents, Canadian beaver (Castor canadensis) and naked mole rat (NMR, Heterocephalus glaber), which were scaffolded with in vitro proximity ligation and chromosome conformation capture data and complemented with long-read sequencing. Our comparative genomic analyses reveal that amino acid substitutions at "disease-causing" sites are widespread in the rodent genomes and that identical substitutions in long-lived rodents are associated with common adaptive phenotypes, e.g., enhanced resistance to DNA damage and cellular stress. By employing a newly developed substitution model and likelihood ratio test, we find that energy and fatty acid metabolism pathways are enriched for signals of positive selection in both long-lived rodents. Thus, the high-quality genome resource of long-lived rodents can assist in the discovery of genetic factors that control longevity and adaptive evolution.

Genetics of extreme human longevity to guide drug discovery for healthy ageing.

Ageing is the greatest risk factor for most common chronic human diseases, and it therefore is a logical target for developing interventions to prevent, mitigate or reverse multiple age-related morbidities. Over the past two decades, genetic and pharmacologic interventions targeting conserved pathways of growth and metabolism have consistently led to substantial extension of the lifespan and healthspan in model organisms as diverse as nematodes, flies and mice. Recent genetic analysis of long-lived individuals is revealing common and rare variants enriched in these same conserved pathways that significantly correlate with longevity. In this Perspective, we summarize recent insights into the genetics of extreme human longevity and propose the use of this rare phenotype to identify genetic variants as molecular targets for gaining insight into the physiology of healthy ageing and the development of new therapies to extend the human healthspan.

Epigenetic alterations to Polycomb targets precede malignant transition in a mouse model of breast cancer.

Malignant breast cancer remains a major health threat to women of all ages worldwide and epigenetic variations on DNA methylation have been widely reported in cancers of different types. We profiled DNA methylation with ERRBS (Enhanced Reduced Representation Bisulfite Sequencing) across four main stages of tumor progression in the MMTV-PyMT mouse model (hyperplasia, adenoma/mammary intraepithelial neoplasia, early carcinoma and late carcinoma), during which malignant transition occurs. We identified a large number of differentially methylated cytosines (DMCs) in tumors relative to age-matched normal mammary glands from FVB mice. Despite similarities, the methylation differences of the premalignant stages were distinct from the malignant ones. Many differentially methylated loci were preserved from the first to the last stage throughout tumor progression. Genes affected by methylation gains were enriched in Polycomb repressive complex 2 (PRC2) targets, which may present biomarkers for early diagnosis and targets for treatment.

PGA: post-GWAS analysis for disease gene identification.

Summary: Although the genome-wide association study (GWAS) is a powerful method to identify disease-associated variants, it does not directly address the biological mechanisms underlying such genetic association signals. Here, we present PGA, a Perl- and Java-based program for post-GWAS analysis that predicts likely disease genes given a list of GWAS-reported variants. Designed with a command line interface, PGA incorporates genomic and eQTL data in identifying disease gene candidates and uses gene network and ontology data to score them based upon the strength of their relationship to the disease in question. Availability and implementation: http://zdzlab.einstein.yu.edu/1/pga.html. Contact: zhengdong.zhang@einstein.yu.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

HEDD: Human Enhancer Disease Database.

Enhancers, as specialized genomic cis-regulatory elements, activate transcription of their target genes and play an important role in pathogenesis of many human complex diseases. Despite recent systematic identification of them in the human genome, currently there is an urgent need for comprehensive annotation databases of human enhancers with a focus on their disease connections. In response, we built the Human Enhancer Disease Database (HEDD) to facilitate studies of enhancers and their potential roles in human complex diseases. HEDD currently provides comprehensive genomic information for ∼2.8 million human enhancers identified by ENCODE, FANTOM5 and RoadMap with disease association scores based on enhancer-gene and gene-disease connections. It also provides Web-based analytical tools to visualize enhancer networks and score enhancers given a set of selected genes in a specific gene network. HEDD is freely accessible at http://zdzlab.einstein.yu.edu/1/hedd.php.