Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease.

Age-related changes to the genome-wide DNA methylation (DNAm) pattern observed in blood are well-documented. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study (CHS) participants, with replication in 2655 Atherosclerosis Risk in Communities (ARIC) Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations associated with these two leading CHIP genes may promote the risk for CAD.

Long read sequencing and expression studies of AHDC1 deletions in Xia-Gibbs syndrome reveal a novel genetic regulatory mechanism.

Xia-Gibbs syndrome (XGS; MIM# 615829) is a rare mendelian disorder characterized by Development Delay (DD), intellectual disability (ID), and hypotonia. Individuals with XGS typically harbor de novo protein-truncating mutations in the AT-Hook DNA binding motif containing 1 (AHDC1) gene, although some missense mutations can also cause XGS. Large de novo heterozygous deletions that encompass the AHDC1 gene have also been ascribed as diagnostic for the disorder, without substantial evidence to support their pathogenicity. We analyzed 19 individuals with large contiguous deletions involving AHDC1, along with other genes. One individual bore the smallest known contiguous AHDC1 deletion (∼350 Kb), encompassing eight other genes within chr1p36.11 (Feline Gardner-Rasheed, IFI6, FAM76A, STX12, PPP1R8, THEMIS2, RPA2, SMPDL3B) and terminating within the first intron of AHDC1. The breakpoint junctions and phase of the deletion were identified using both short and long read sequencing (Oxford Nanopore). Quantification of RNA expression patterns in whole blood revealed that AHDC1 exhibited a mono-allelic expression pattern with no deficiency in overall AHDC1 expression levels, in contrast to the other deleted genes, which exhibited a 50% reduction in mRNA expression. These results suggest that AHDC1 expression in this individual is compensated by a novel regulatory mechanism and advances understanding of mutational and regulatory mechanisms in neurodevelopmental disorders.

AHDC1 missense mutations in Xia-Gibbs syndrome.

Xia-Gibbs syndrome (XGS; MIM: 615829) is a phenotypically heterogeneous neurodevelopmental disorder (NDD) caused by newly arising mutations in the AT-Hook DNA-Binding Motif-Containing 1 (AHDC1) gene that are predicted to lead to truncated AHDC1 protein synthesis. More than 270 individuals have been diagnosed with XGS worldwide. Despite the absence of an independent assay for AHDC1 protein function to corroborate potential functional consequences of rare variant genetic findings, there are also reports of individuals with XGS-like trait manifestations who have de novo missense AHDC1 mutations and who have been provided a molecular diagnosis of the disorder. To investigate a potential contribution of missense mutations to XGS, we mapped the missense mutations from 10 such individuals to the AHDC1 conserved protein domain structure and detailed the observed phenotypes. Five newly identified individuals were ascertained from a local XGS Registry, and an additional five were taken from external reports or databases, including one publication. Where clinical data were available, individuals with missense mutations all displayed phenotypes consistent with those observed in individuals with AHDC1 truncating mutations, including delayed motor milestones, intellectual disability (ID), hypotonia, and speech delay. A subset of the 10 reported missense mutations cluster in two regions of the AHDC1 protein with known conserved domains, likely representing functional motifs. Variants outside the clustered regions score lower for computational prediction of their likely damaging effects. Overall, de novo missense variants in AHDC1 are likely diagnostic of XGS when in silico analysis of their position relative to conserved regions is considered together with disease trait manifestations.

Genetic testing in ambulatory cardiology clinics reveals high rate of findings with clinical management implications.

PURPOSE: Cardiovascular disease (CVD) is the leading cause of death in adults in the United States, yet the benefits of genetic testing are not universally accepted. METHODS: We developed the "HeartCare" panel of genes associated with CVD, evaluating high-penetrance Mendelian conditions, coronary artery disease (CAD) polygenic risk, LPA gene polymorphisms, and specific pharmacogenetic (PGx) variants. We enrolled 709 individuals from cardiology clinics at Baylor College of Medicine, and samples were analyzed in a CAP/CLIA-certified laboratory. Results were returned to the ordering physician and uploaded to the electronic medical record. RESULTS: Notably, 32% of patients had a genetic finding with clinical management implications, even after excluding PGx results, including 9% who were molecularly diagnosed with a Mendelian condition. Among surveyed physicians, 84% reported medical management changes based on these results, including specialist referrals, cardiac tests, and medication changes. LPA polymorphisms and high polygenic risk of CAD were found in 20% and 9% of patients, respectively, leading to diet, lifestyle, and other changes. Warfarin and simvastatin pharmacogenetic variants were present in roughly half of the cohort. CONCLUSION: Our results support the use of genetic information in routine cardiovascular health management and provide a roadmap for accompanying research.

Phenotypic and protein localization heterogeneity associated with AHDC1 pathogenic protein-truncating alleles in Xia-Gibbs syndrome.

Xia-Gibbs syndrome (XGS) is a rare Mendelian disease typically caused by de novo stop-gain or frameshift mutations in the AT-hook DNA binding motif containing 1 (AHDC1) gene. Patients usually present in early infancy with hypotonia and developmental delay and later exhibit intellectual disability (ID). The overall presentation is variable, however, and the emerging clinical picture is still evolving. A detailed phenotypic analysis of 34 XGS individuals revealed five core phenotypes (delayed motor milestones, speech delay, low muscle tone, ID, and hypotonia) in more than 80% of individuals and an additional 12 features that occurred more variably. Seizures and scoliosis were more frequently associated with truncations that arise before the midpoint of the protein although the occurrence of most features could not be predicted by the mutation position. Transient expression of wild type and different patient truncated AHDC1 protein forms in human cell lines revealed abnormal patterns of nuclear localization including a diffuse distribution of a short truncated form and nucleolar aggregation in mid-protein truncated forms. Overall, both the occurrence of variable phenotypes and the different distribution of the expressed protein reflect the heterogeneity of this syndrome.

Phenotypic expansion in KIF1A-related dominant disorders: A description of novel variants and review of published cases.

KIF1A is a molecular motor for membrane-bound cargo important to the development and survival of sensory neurons. KIF1A dysfunction has been associated with several Mendelian disorders with a spectrum of overlapping phenotypes, ranging from spastic paraplegia to intellectual disability. We present a novel pathogenic in-frame deletion in the KIF1A molecular motor domain inherited by two affected siblings from an unaffected mother with apparent germline mosaicism. We identified eight additional cases with heterozygous, pathogenic KIF1A variants ascertained from a local data lake. Our data provide evidence for the expansion of KIF1A-associated phenotypes to include hip subluxation and dystonia as well as phenotypes observed in only a single case: gelastic cataplexy, coxa valga, and double collecting system. We review the literature and suggest that KIF1A dysfunction is better understood as a single neuromuscular disorder with variable involvement of other organ systems than a set of discrete disorders converging at a single locus.

Evaluation of computational genotyping of structural variation for clinical diagnoses.

BACKGROUND: Structural variation (SV) plays a pivotal role in genetic disease. The discovery of SVs based on short DNA sequence reads from next-generation DNA sequence methods is error-prone, with low sensitivity and high false discovery rates. These shortcomings can be partially overcome with extensive orthogonal validation methods or use of long reads, but the current cost precludes their application for routine clinical diagnostics. In contrast, SV genotyping of known sites of SV occurrence is relatively robust and therefore offers a cost-effective clinical diagnostic tool with potentially few false-positive and false-negative results, even when applied to short-read DNA sequence data. RESULTS: We assess 5 state-of-the-art SV genotyping software methods, applied to short-read sequence data. The methods are characterized on the basis of their ability to genotype different SV types, spanning different size ranges. Furthermore, we analyze their ability to parse different VCF file subformats and assess their reliance on specific metadata. We compare the SV genotyping methods across a range of simulated and real data including SVs that were not found with Illumina data alone. We assess sensitivity and the ability to filter initial false discovery calls. We determined the impact of SV type and size on the performance for each SV genotyper. Overall, STIX performed the best on both simulated and GiaB based SV calls, demonstrating a good balance between sensitivity and specificty. CONCLUSION: Our results indicate that, although SV genotyping software methods have superior performance to SV callers, there are limitations that suggest the need for further innovation.