Combined Annotation-Dependent Depletion (CADD) is a widely used measure of variant deleteriousness that can effectively prioritize causal variants in genetic analyses, particularly highly penetrant contributors to severe Mendelian disorders. CADD is an integrative annotation built from more than 60 genomic features, and can score human single nucleotide variants and short insertion and deletions anywhere in the reference assembly. CADD uses a machine learning model trained on a binary distinction between simulated de novo variants and variants that have arisen and become fixed in human populations since the split between humans and chimpanzees; the former are free of selective pressure and may thus include both neutral and deleterious alleles, while the latter are overwhelmingly neutral (or, at most, weakly deleterious) by virtue of having survived millions of years of purifying selection. Here we review the latest updates to CADD, including the most recent version, 1.4, which supports the human genome build GRCh38. We also present updates to our website that include simplified variant lookup, extended documentation, an Application Program Interface and improved mechanisms for integrating CADD scores into other tools or applications. CADD scores, software and documentation are available at https://cadd.gs.washington.edu.

CADD: predicting the deleteriousness of variants throughout the human genome.

Births in the united states. interesting changes going on.

https://www.nature.com/articles/s41422-022-00653-7.pdf

Cuproptosis: a copper-triggered modality of mitochondrial cell death

Description Excess copper causes mitochondrial protein aggregation and triggers a distinct form of cell death Copper and other trace metals are essential for life. However, it is important that these metals are present at the right amount in cells. Too little metal can impair the function of important metal-binding enzymes, and too much metal can overwhelm a cell, leading to death. In humans, mutations that cause excess copper accumulation are life-threatening, and yet there may exist a window such that more focused increases of intracellular copper can be used to selectively kill cancer cells (1). A better understanding of how copper accumulation causes cellular toxicity is therefore of great interest. On page 1254 of this issue, Tsvetkov et al. (2) reveal that copper toxicity involves the disruption of specific mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death. This mechanism may explain the pathology associated with genetic copper overload disorders and suggest new ways to harness copper toxicity to treat cancer.

Copper-induced cell death

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, which is characterized by metabolic reprogramming. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical impacts of cuproptosis-related genes (CRGs) in ccRCC largely remain unclear. In the current study, we systematically evaluated the genetic alterations of cuproptosis-related genes in ccRCC. Our results revealed that CDKN2A, DLAT, DLD, FDX1, GLS, PDHA1 and PDHB exhibited differential expression between ccRCC and normal tissues (|log2(fold change)| > 2/3 and p < 0.05). Utilizing an iterative sure independence screening (SIS) method, we separately constructed the prognostic signature of CRGs for predicting the overall survival (OS) and progression-free survival (PFS) in ccRCC patients. The prognostic score of CRGs yielded an area under the curve (AUC) of 0.658 and 0.682 for the prediction of 5-year OS and PFS, respectively. In the Kaplan−Meier survival analysis of OS, a higher risk score of cuproptosis-related gene signature was significantly correlated with worse overall survival (HR = 2.72 (2.01–3.68), log-rank p = 1.76 × 10−7). Patients with a higher risk had a significantly shorter PFS (HR = 2.83 (2.08–3.85), log-rank p = 3.66 × 10−7). Two independent validation datasets (GSE40435 (N = 101), GSE53757 (N = 72)) were collected for meta-analysis, suggesting that CDKN2A (log2(fold change) = 1.46, 95%CI: 1.75–2.35) showed significantly higher expression in ccRCC tissues while DLAT (log2(fold change) = −0.54, 95%CI: −0.93–−0.15) and FDX1 (log2(fold change) = −1.01, 95%CI: −1.61–−0.42) were lowly expressed. The expression of CDKN2A and FDX1 in ccRCC was also significantly associated with immune infiltration levels and programmed cell death protein 1 (PD-1) expression (CDKN2A: r = 0.24, p = 2.14 × 10−8; FDX1: r = −0.17, p = 1.37 × 10−4). In conclusion, the cuproptosis-related gene signature could serve as a potential prognostic predictor for ccRCC patients and may offer novel insights into the cancer treatment.

/pdf/a-novel-cuproptosis-related-prognostic-gene-signature-and-ju6muuqa.pdf

A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma

Copper is an essential nutrient whose redox properties make it both beneficial and toxic to the cell. Recent progress in studying transition metal signalling has forged new links between researchers of different disciplines that can help translate basic research in the chemistry and biology of copper into clinical therapies and diagnostics to exploit copper-dependent disease vulnerabilities. This concept is particularly relevant in cancer, as tumour growth and metastasis have a heightened requirement for this metal nutrient. Indeed, the traditional view of copper as solely an active site metabolic cofactor has been challenged by emerging evidence that copper is also a dynamic signalling metal and metalloallosteric regulator, such as for copper-dependent phosphodiesterase 3B (PDE3B) in lipolysis, mitogen-activated protein kinase kinase 1 (MEK1) and MEK2 in cell growth and proliferation and the kinases ULK1 and ULK2 in autophagy. In this Perspective, we summarize our current understanding of the connection between copper and cancer and explore how challenges in the field could be addressed by using the framework of cuproplasia, which is defined as regulated copper-dependent cell proliferation and is a representative example of a broad range of metalloplasias. Cuproplasia is linked to a diverse array of cellular processes, including mitochondrial respiration, antioxidant defence, redox signalling, kinase signalling, autophagy and protein quality control. Identifying and characterizing new modes of copper-dependent signalling offers translational opportunities that leverage disease vulnerabilities to this metal nutrient.

Connecting copper and cancer: from transition metal signalling to metalloplasia.

Background Previous estimates of the prevalence of Menkes disease, a lethal X-linked recessive disorder of copper metabolism, were based on confirmed clinical cases ascertained from specific populations and varied from 1 in 40,000 to 1 in 354,507. With newly available population-based allelic frequencies of DNA sequence variants, the expected birth prevalence of Menkes disease and other ATP7A-related phenotypes can be reconsidered using Hardy-Weinberg theoretical principles. Methods We reviewed the canonical ATP7A transcript in the current version of gnomAD (v2.1.1) to evaluate frequency of complete loss-of-function alleles in a diverse normal control population. As a comparator, we used the DMD locus, associated with Duchenne and Becker Muscular Dystrophy, another X-linked recessive trait. We applied Hardy-Weinberg theory and PolyPhen-2 in silico plus REVEL and CADD ensemble analyses to calculate estimated frequencies of normal and predicted deleterious ATP7A alleles. Results We identified 1106 total ATP7A variants out of 205,523 alleles in gnomAD, with missense variants most common (43.4%). Complete loss-of-function variants were found in four ATP7A alleles (frequency = 0.0000194), including three frameshift/nonsense mutations and one canonical splice donor site defect. Assuming Hardy-Weinberg equilibrium, this frequency of pathogenic alleles predicts 1 in 34,810 live male births with Menkes disease or other ATP7A-related disorders each year in the US. The same analysis for DMD loss-of-function variants predicted 1 in 7246 newborn males with Duchenne (or Becker) muscular dystrophy. We also identified nine ATP7A missense variants in gnomAD predicted as deleterious by PolyPhen-2 and stringent REVEL/CADD criteria, comprising 12 more disease-causing alleles and raising the estimated birth prevalence to 1 in 8664 and predicting 225 newborns with Menkes disease or other ATP7A-related disorders per year in the US alone. Conclusions Assuming Hardy-Weinberg equilibrium, the allelic frequency of deleterious ATP7A variants in a genomic database from a large diverse population predicts a birth prevalence of Menkes disease or ATP7A-related disorders as high as 1 in 8664 live male births. This genome-driven ascertainment of deleterious ATP7A alleles in the population implies a higher birth prevalence of Menkes disease and ATP7A-related conditions than previously appreciated. A population-based newborn screening pilot study for Menkes disease will be instrumental in confirming the prediction.

Stephen G. Kaler

Papers

Connecting copper and cancer: from transition metal signalling to metalloplasia.

Estimated birth prevalence of Menkes disease and ATP7A-related disorders based on the Genome Aggregation Database (gnomAD).