Population Allele Frequencies Research Articles

Geographical distribution of MTHFR C677T gene polymorphisms among the reproductive-age women in Chinese Han populations: based on migration

BackgroundMethylenetetrahydrofolate reductase (MTHFR) is essential for the metabolism of folic acid and homocysteine. The MTHFR C677T polymorphism is associated with several disorders. Our study aims to explore the geographical distributions of the MTHFR C677T polymorphism of women in China and how migration affected the polymorphism in Suzhou.MethodsA total of 7188 women of reproductive age were recruited in Suzhou of the study. Subjects were classified according to their native places after data extraction. MTHFR C677T gene polymorphisms were detected by quantitative PCR with genomic DNA isolated from blood samples.ResultsThe frequencies of the 677T allele and 677TT genotype were higher in northern China than that in southern China and decreased in geographical gradients from north to south. The frequencies were considerably higher in the migrant population than that in the indigenous population of Suzhou. The migrant population have gradually changed the prevalence in Suzhou.ConclusionsOur study suggested that the prevalence of MTHFR C677T polymorphisms among women varied across different geographical regions in Chinese Han populations. The 677T allele frequencies of the northern populations were significantly higher than those of the southern populations. The migrant population gradually changed the prevalence of the MTHFR C677T polymorphism in Suzhou.

Molecular genetic analysis of candidate genes for glutaric aciduria type II in a cohort of patients from Queensland, Australia

Glutaric aciduria type II (GAII) is a heterogeneous genetic disorder affecting mitochondrial fatty acid, amino acid and choline oxidation. Clinical manifestations vary across the lifespan and onset may occur at any time from the early neonatal period to advanced adulthood. Historically, some patients, in particular those with late onset disease, have experienced significant benefit from riboflavin supplementation. GAII has been considered an autosomal recessive condition caused by pathogenic variants in the gene encoding electron-transfer flavoprotein ubiquinone-oxidoreductase (ETFDH) or in the genes encoding electron-transfer flavoprotein subunits A and B (ETFA and ETFB respectively). Variants in genes involved in riboflavin metabolism have also been reported. However, in some patients, molecular analysis has failed to reveal diagnostic molecular results. In this study, we report the outcome of molecular analysis in 28 Australian patients across the lifespan, 10 paediatric and 18 adult, who had a diagnosis of glutaric aciduria type II based on both clinical and biochemical parameters. Whole genome sequencing was performed on 26 of the patients and two neonatal onset patients had targeted sequencing of candidate genes. The two patients who had targeted sequencing had biallelic pathogenic variants (in ETFA and ETFDH). None of the 26 patients whose whole genome was sequenced had biallelic variants in any of the primary candidate genes. Interestingly, nine of these patients (34.6%) had a monoallelic pathogenic or likely pathogenic variant in a single primary candidate gene and one patient (3.9%) had a monoallelic pathogenic or likely pathogenic variant in two separate genes within the same pathway. The frequencies of the damaging variants within ETFDH and FAD transporter gene SLC25A32 were significantly higher than expected when compared to the corresponding allele frequencies in the general population. The remaining 16 patients (61.5%) had no pathogenic or likely pathogenic variants in the candidate genes. Ten (56%) of the 18 adult patients were taking the selective serotonin reuptake inhibitor antidepressant sertraline, which has been shown to produce a GAII phenotype, and another two adults (11%) were taking a serotonin-norepinephrine reuptake inhibitor antidepressant, venlafaxine or duloxetine, which have a mechanism of action overlapping that of sertraline. Riboflavin deficiency can also mimic both the clinical and biochemical phenotype of GAII. Several patients on these antidepressants showed an initial response to riboflavin but then that response waned. These results suggest that the GAII phenotype can result from a complex interaction between monoallelic variants and the cellular environment. Whole genome or targeted gene panel analysis may not provide a clear molecular diagnosis.

Variant ranking pipeline for complex familial disorders

Identifying genetic susceptibility factors for complex disorders remains a challenging task. To analyze collections of small and large pedigrees where genetic heterogeneity is likely, but biological commonalities are plausible, we have developed a weights-based pipeline to prioritize variants and genes. The Weights-based vAriant Ranking in Pedigrees (WARP) pipeline prioritizes variants using 5 weights: disease incidence rate, number of cases in a family, genome fraction shared amongst cases in a family, allele frequency and variant deleteriousness. Weights, except for the population allele frequency weight, are normalized between 0 and 1. Weights are combined multiplicatively to produce family-specific-variant weights that are then averaged across all families in which the variant is observed to generate a multifamily weight. Sorting multifamily weights in descending order creates a ranked list of variants and genes for further investigation. WARP was validated using familial melanoma sequence data from the European Genome-phenome Archive. The pipeline identified variation in known germline melanoma genes POT1, MITF and BAP1 in 4 out of 13 families (31%). Analysis of the other 9 families identified several interesting genes, some of which might have a role in melanoma. WARP provides an approach to identify disease predisposing genes in studies with small and large pedigrees.

Further delineation of short-chain enoyl-CoA hydratase deficiency in the Pacific population

Short-chain enoyl-coA hydratase (SCEH) deficiency due to biallelic pathogenic ECHS1 variants was first reported in 2014 in association with Leigh syndrome (LS) and increased S-(2-carboxypropyl)cysteine excretion. It is potentially treatable with a valine-restricted, high-energy diet and emergency regimen. Recently, Simon et al. described four Samoan children harbouring a hypomorphic allele (c.489G>A, p.Pro163=) associated with reduced levels of normally-spliced mRNA. This synonymous variant, missed on standard genomic testing, is prevalent in the Samoan population (allele frequency 0.17). Patients with LS and one ECHS1 variant were identified in NZ and Australian genomic and clinical databases. ECHS1 sequence data were interrogated for the c.489G>A variant and clinical data were reviewed. Thirteen patients from 10 families were identified; all had Pacific ancestry including Samoan, Māori, Cook Island Māori, and Tokelauan. All developed bilateral globus pallidi lesions, excluding one pre-symptomatic infant. Symptom onset was in early childhood, and was triggered by illness or starvation in 9/13. Four of 13 had exercise-induced dyskinesia, 9/13 optic atrophy and 6/13 nystagmus. Urine S-(2-carboxypropyl)cysteine-carnitine and other SCEH-related metabolites were normal or mildly increased. Functional studies demonstrated skipping of exon four and markedly reduced ECHS1 protein. These data provide further support for the pathogenicity of this ECHS1 variant which is also prevalent in Māori, Cook Island Māori, and Tongan populations (allele frequency 0.14-0.24). It highlights the need to search for a second variant in apparent heterozygotes with an appropriate phenotype, and has implications for genetic counselling in family members who are heterozygous for the more severe ECHS1 alleles. SYNOPSIS: Short-chain enoyl-CoA hydratase deficiency is a frequent cause of Leigh-like disease in Māori and wider-Pacific populations, due to the high carrier frequency of a hypomorphic ECHS1 variant c.489G>A, p.[Pro163=, Phe139Valfs*65] that may be overlooked by standard genomic testing.

Assisting the analysis of insertions and deletions using regional allele frequencies.

Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides "regional AF" (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10-4 and rAF>10-4) as "rAF-hi" indels. Notably, a high percentage of rare indels were "rAF-hi", with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels' parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.

Individual and population-level variability in HLA-DR associated immunogenicity risk of biologics used for the treatment of rheumatoid arthritis.

While conventional in silico immunogenicity risk assessments focus on measuring immunogenicity based on the potential of therapeutic proteins to be processed and presented by a global population-wide set of human leukocyte antigen (HLA) alleles to T cells, future refinements might adjust for HLA allele frequencies in different geographic regions or populations, as well for as individuals in those populations. Adjustment by HLA allele distribution may reveal risk patterns that are specific to population groups or individuals, which current methods that rely on global-population HLA prevalence may obscure. This analysis uses HLA frequency-weighted binding predictions to define immunogenicity risk for global and sub-global populations. A comparison of assessments tuned for North American/European versus Japanese/Asian populations suggests that the potential for anti-therapeutic responses (anti-therapeutic antibodies or ATA) for several commonly prescribed Rheumatoid Arthritis (RA) therapeutic biologics may differ, significantly, between the Caucasian and Japanese populations. This appears to align with reports of differing product-related immunogenicity that is observed in different populations. Further definition of population-level (regional) and individual patient-specific immunogenic risk profiles may enable prescription of the RA therapeutic with the highest probability of success to each patient, depending on their population of origin and/or their individual HLA background. Furthermore, HLA-specific immunogenicity outcomes data are limited, thus there is a need to expand HLA-association studies that examine the relationship between HLA haplotype and ATA in the clinic.

PNPLA3 fatty liver allele was fixed in Neanderthals and segregates neutrally in humans

ObjectiveFat deposition is modulated by environmental factors and genetic predisposition. Genome-wide association studies identified PNPLA3 p.I148M (rs738409) as a common variant that increases risk of developing liver steatosis. When and...

Locally adaptive inversions in structured populations.

Inversions have been proposed to facilitate local adaptation, by linking together locally coadapted alleles at different loci. Prior work addressing this question theoretically has considered the spread of inversions in "continent-island" scenarios in which there is a unidirectional flow of maladapted migrants into the island population. In this setting, inversions capturing locally adaptive haplotypes are most likely to invade when selection is weak, because stronger local selection (i) more effectively purges maladaptive alleles and (ii) generates linkage disequilibrium between adaptive alleles, thus lessening the advantage of inversions. We show this finding only holds under limited conditions by studying the establishment of inversions in a more general two-deme model, which explicitly considers the dynamics of allele frequencies in both populations linked by bidirectional migration. In this model, the level of symmetry between demes can be varied from complete asymmetry (continent-island) to complete symmetry. For symmetric selection and migration, strong selection increases the allele frequency divergence between demes thereby increasing the frequency of maladaptive alleles in migrants, favoring inversions-the opposite of the pattern seen in the asymmetric continent-island scenario. We also account for the likelihood that a new inversion captures an adaptive haplotype in the first instance. When considering the combined process of capture and invasion in "continent island" and symmetric scenarios, relatively strong selection increases inversion establishment probability. Migration must also be low enough that the inversion is likely to capture an adaptive allele combination, but not so low as to eliminate the inversion's advantage. Overall, our analysis suggests that inversions are likely to harbor larger effect alleles that experience relatively strong selection.

Impact of Circulating Lymphoma Cells on HLA Typing Outcomes in Patients with Diffuse Large B-Cell Lymphoma: A Case Report

Recipient's high resolution HLA typing is required in allogeneic hematopoietic cell transplantation from unrelated donors, as well as for haploidentical family donors. For these purposes, Next-Generation Sequencing (NGS) methods are the gold standard. We present a case of a patient with an incorrect HLA typing result caused by the population of circulating lymphoma cells. The first HLA examination was performed from peripheral blood (PB) using NGS in the active phase of diffuse large B-cell lymphoma with bone marrow involvement. Because of rare and inconclusive results, confirmed twice for the A* locus (A*02:32N), real-time polymerase chain reaction (RT-PCR)was performed. With RT-PCR method, we obtained more expected results according to the population allele frequency: in HLA-A locus (A*02:01) but also in DQB1 (DQB1*03:01, not as in NGS - DQB1*03:10). For the final verification, we used swab material and we obtained unambiguous NGS result with expected, frequent HLA-A*02:01 and DQB1*03:01 alleles corresponding to the RT-PCR result from PB. To conclude, we suspect that the discrepancies between NGS and RT-PCR results were caused by the presence of a significant amount of circulating lymphoma cells in the peripheral blood sample. Lymphomagenic mutations may involve the histocompatibility antigen coding region and affect HLA expressed on malignant cells. This finding may be relevant for the selection of test material in primary and confirmatory HLA testing in patients with active hematological malignancies because of the strong impact of incorrect HLA typing on the procedure of a donor selection.

Cardiac arrhythmia and epilepsy genetic variants in sudden unexpected death in epilepsy.

Sudden Unexpected Death in Epilepsy (SUDEP) is the leading epilepsy-related cause of death, affecting approximately 1 per 1,000 individuals with epilepsy per year. Genetic variants that affect autonomic function, such as genes associated with cardiac arrhythmias, may predispose people with epilepsy to greater risk of both sudden cardiac death and SUDEP. Advances in next generation sequencing allow for the exploration of gene variants as potential biomarkers. Genetic testing for the presence of cardiac arrhythmia and epilepsy gene variants was performed via genetic panels in 39 cases of SUDEP identified via autopsy by the Ontario Forensic Pathology Service. Variants were summarized by in-silico evidence for pathogenicity from 4 algorithms (SIFT, PolyPhen-2, PROVEAN, Mutation Taster) and allele frequencies in the general population (GnomAD). A maximum credible population allele frequency of 0.00004 was calculated based on epilepsy prevalence and SUDEP incidence to assess whether a variant was compatible with a pathogenic interpretation. Median age at the time of death was 33.3 years (range: 2, 60). Fifty-nine percent (n=23) were male. Gene panels detected 62 unique variants in 45 genes: 19 on the arrhythmia panel and 26 on the epilepsy panel. At least one variant was identified in 28 (72%) of decedents. Missense mutations comprised 57 (92%) of the observed variants. At least three in silico models predicted 12 (46%) cardiac arrhythmia panel missense variants and 20 (65%) epilepsy panel missense variants were pathogenic. Population allele frequencies were <0.00004 for 11 (42%) of the cardiac variants and 10 (32%) of the epilepsy variants. Together, these metrics identified 13 SUDEP variants of interest. Nearly three-quarters of decedents in this SUDEP cohort carried variants in comprehensive epilepsy or cardiac arrhythmia gene panels, with more than a third having variants in both panels. The proportion of decedents with cardiac variants aligns with recent studies of the disproportionate cardiac burden the epilepsy community faces compared to the general population and suggests a possible cardiac contribution to epilepsy mortality. These results identified 13 priority targets for future functional studies of these genes potential role in sudden death and demonstrates the necessity for further exploration of potential genetic contributions to SUDEP.

Abstract PO3-16-01: Personalized circulating tumor DNA assay precisely predicts the response of neoadjuvant chemotherapy in breast cancer patients

Abstract Introduction Circulating tumor DNA (ctDNA), which is detected in the blood as cell free DNA fragment from tumor cells, could indicates genomic landscape, tumor burden and treatment response during chemotherapy as a non-invasive method. Especially, personized ctDNA assay by next-generation sequencing(NGS) is able to detect a trace amount of ctDNA and precisely figure out the change of the amount of ctDNA during NAC and follow up period after curative surgery. Here, we performed serial ctDNA evaluations in EBC patients who diagnosed as TNBC or HER2-positive BC and received NAC followed by curative surgery. We aimed to predict NAC response and detect minimal residual disease (MRD) using personalized ctDNA assay. Methods CtDNA was detected by AlphaLiquid®Detect, a tumor-informed personalized MRD detection assay exploring most of the mutations in tumor. Whole exome sequencing (WES) of tumor tissue and peripheral blood mononuclear cells (PBMCs) was performed. Patient-specific somatic mutations were selected using a proprietary algorithm. In brief, clonal variants were prioritized using integrated information including variant allele frequency, population allele frequency databases, somatic variant databases, variant pathogenicity, and genomic context. Up to 100 variants were selected for patient monitoring. A hybridization capture panel consisting of a pool of 4 patients’ selected variants was synthesized. These bespoke panels (BSPs) were used for ctDNA detection. Patients with more than 2 tumor-derived mutations detected in plasma were considered as ctDNA positive. Inclusion criteria included patient who diagnosed as stage IIA-IIIC BC planned to NAC followed by curative surgery. Among BC subtypes, TNBC and HER2-positive BC were allowed. Collection of specimens and associated clinical data used in this study was approved by the Institutional Review Board of Samsung Medical Center (IRB File No.2021-02-033), and we received informed consents for this study. Results From May 2021 to Sep 2022, 158 patients has been enrolled. Archival tissues were not available in 47 patients and tissue WES had failed in six patients. Therefore, 105 patients were enrolled and analyzed their ctDNA at diagnosis based on tissue WES data. Of 105 patients, Median age of BC patients was 49.3 years of age (range: 26.1, 67.8). Thirty-six patients (34.3%) were post-menopausal status and others (65.7%) were pre-menopausal status. In BC pathology at diagnosis, 56 (53.3%) were TNBC and other 49 (46.7%) were HER2-positive BC. Among HER2-positive BC, hormone receptor (HR)-positive were in 21 (20.0%). In clinical stage at diagnosis, stage II were 46 (43.8%) and stage III in 59 (56.2%). In 105 patients, median number of somatic mutations was 60 (interquartile range [IQR]: 38.5, 91). CtDNA detection rate at BC diagnosis was 90.5% and all of BC which not be detected ctDNA was HER2-positive BC with clinical stage II. Median amount of ctDNA at diagnosis was 20 (IQR: 6, 44). In the number of somatic mutations, there was no difference according to BC subtypes (P=0.121) and clinical stage (P=0.700) but the amounts of ctDNA at diagnosis was different. CtDNA was much more detected in TNBC compared to HER2-positive BC (Median: 34.5 vs. 15.9; P&amp;lt; 0.001) and clinical stage III compared to clinical stage II (Median 33.2 vs. 19.5; P=0.002). After NAC, ctDNA at curative surgery was tested in 70 patients. In 70 patients, pathologic complete response(pCR) was observed in 44 patients. CtDNA was detected in ten patients (14.3%) and eight did not achieve pCR and two with pCR (Specificity of assay: 95.5%, positive predictive value: 0.80, P=0.032). Conclusions Personalized ctDNA assay can precisely detected ctDNA at diagnosis and their detection rate was associated with BC subtypes and clinical stage. In addition, ctDNA at curative surgery also can predict NAC response in EBC patients. Long term ctDNA follow up of MRD would be warranted. Citation Format: Ji-Yeon Kim, Hae Hyun Jung, Jeong Eon Lee, Seok Won Kim, Hwang-Phill Kim, Sunghoon Heo, Jongseong Ahn, Tae-You Kim, Young-Hyuck Im. Personalized circulating tumor DNA assay precisely predicts the response of neoadjuvant chemotherapy in breast cancer patients [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-16-01.

Multiomic analysis of uterine leiomyomas in self-described Black and White women: molecular insights into health disparities

Black women are at an increased risk to develop uterine leiomyomas (ULMs) and to experience worse disease prognosis compared to White women. Epidemiological and molecular factors have been identified as underlying these disparities, but there remains a paucity of deep, multi-omic analysis investigating molecular differences in ULMs from Black and White patients. To identify molecular alterations within ULM tissues correlating with patient race by multi-omic analyses of ULMs collected from cohorts of Black and White women. We performed multi-omic analysis of ULMs from Black (42) and White (47) women undergoing hysterectomy for symptomatic uterine leiomyomata. Our analysis also included application of orthogonal methods to evaluate fibroid biomechanical properties, such as second harmonic generation microscopy, uniaxial compression testing, as well as sheer wave ultrasonography analyses. We found a greater proportion of mediator complex subunit 12 (MED12) mutant ULMs from Black women (>35% increase, Mann Whitney U p = 7E-4). MED12 mutant tumors exhibited elevated abundance of extracellular matrix proteins, including several collagen isoforms, involved in regulation of the core matrisome. Histological analysis of tissue fibrosis using trichrome staining and secondary harmonic generation microscopy confirmed that MED12 mutant tumors are more fibrotic than MED12 wildtype tumors. Using Sheer Wave ultrasonography in a prospectively collected cohort, Black patients had fibroids that were firmer when compared to White patients, even when similar in size. These analyses also uncovered expression quantitative trait loci (eQTL) associated with altered allele frequencies in African and European populations that correlated with differential abundance of several proteins in ULM that are independent of MED12 mutational status, including multiple eQTL mapping to tetratricopeptide repeat protein 38. Our study shows that Black women have a higher prevalence of ULMs harboring mutations in MED12 and that this mutational status correlates with increased tissue fibrosis in comparison with wildtype ULMs. Our study provides insights into molecular alterations underlying racial disparities in ULMs and improves our understanding of the molecular etiology underlying ULM development within these populations.

Benchmarking kinship estimation tools for ancient genomes using pedigree simulations.

There is growing interest in uncovering genetic kinship patterns in past societies using low-coverage palaeogenomes. Here, we benchmark four tools for kinship estimation with such data: lcMLkin, NgsRelate, KIN, and READ, which differ in their input, IBD estimation methods, and statistical approaches. We used pedigree and ancient genome sequence simulations to evaluate these tools when only a limited number (1 to 50 K, with minor allele frequency ≥0.01) of shared SNPs are available. The performance of all four tools was comparable using ≥20 K SNPs. We found that first-degree related pairs can be accurately classified even with 1 K SNPs, with 85% F1 scores using READ and 96% using NgsRelate or lcMLkin. Distinguishing third-degree relatives from unrelated pairs or second-degree relatives was also possible with high accuracy (F1 > 90%) with 5 K SNPs using NgsRelate and lcMLkin, while READ and KIN showed lower success (69 and 79% respectively). Meanwhile, noise in population allele frequencies and inbreeding (first-cousin mating) led to deviations in kinship coefficients, with different sensitivities across tools. We conclude that using multiple tools in parallel might be an effective approach to achieve robust estimates on ultra-low-coverage genomes.

Abstract 792: Continuous, probabilistic variant interpretation with Bayesian graphical models

Abstract Introduction: Current variant classification (VC) frameworks rely on rules-based approaches that use heuristic weighting of various types of evidence, resulting in &amp;gt; 50% of variants being classified as variants of uncertain significance (VUS), and leaving many patients with uncertainty about their disease risk or diagnosis. We propose a probabilistic and scalable Bayesian approach to model the causal relationships between various types of evidence. A fully quantitative system maximizes the utility and integration of various evidence types, empowering clinicians to make more nuanced management decisions. Methods: Probabilistic graphical models (PGMs) are uniquely suited to the needs of clinical VC. Two different component PGMs were developed to model two of the evidence categories that will ultimately be used in a comprehensive VC system: population allele frequency (Population PGM) and reported phenotype observations (Reported Phenotype PGM). Results: The Population PGM treats population allele frequency observations as a binomial process. By conditioning the model on partial observations, the probabilistic relationships between pathogenicity and allele frequencies can be estimated while stochastic variational inference allows uncertainty to be efficiently propagated. The resulting model performs well across a large number of genes at inferring pathogenicity of a variant from its allele frequency, with an average precision of &amp;gt;99% for benign variants. In the Reported Phenotype PGM, phenotypic features characteristic of a disorder are learned from patients expected to be affected based on genotype. Patient-level predictions are in turn combined at the variant level to derive variant pathogenicity likelihoods. To date, models representing at least 102 inherited conditions and 259 genes have demonstrated high predictive performance (&amp;gt;0.8 AUROC) for both patient-level and variant-level predictions. Finally, as a proof-of-concept, we demonstrate how each component PGM can be combined into a probabilistic Bayesian VC framework that also includes protein structure and stability, evolutionary conservation, and sequence context. This framework has high concordance with known, well-accepted pathogenic and benign variants classified with rules-based systems, and could make high-confidence predictions for many variants currently classified as VUS. Conclusion: We present a Bayesian approach that can integrate diverse types of evidence to achieve high VC accuracy while quantifying uncertainty. Future expansion of this Bayesian framework to all evidence types relevant to VC may allow for more accurate risk management guidelines and further inform medical and genetic counseling recommendations. Citation Format: Wolfgang Michael Korn, Yuya Kobayashi, Flavia M. Facio, Arun Nampally, Keith Nykamp, Robert Nussbaum, Alexandre Colavin, Britt Johnson, Toby Manders. Continuous, probabilistic variant interpretation with Bayesian graphical models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 792.

Abstract 4884: Evaluating the utility of in silico variant annotation tools for cancer driver detection

Abstract In cancer genomics, precise variant annotation is crucial for clinical decisions, drug development, and research. The burgeoning genomic data offers an opportunity to use data-driven approaches to generate knowledge that supports clinical decisions. Particularly machine learning (ML) and Deep learning (DL), are becoming essential, as their application is fast, scalable, simple to implement, and generates reproducible results. The methods ranging from simple sequence-based alignment scoring to advanced algorithms like Logistic regression, Support vector machine, and Recurrent neural networks, have been employed by multiple variant annotation tools. This study compares in-silico methods available in Ensembl's Variant Effect Predictor (VEP) using a test dataset with COSMIC annotations. ML/DL success relies on robust training sets with comprehensive genomic variants features, including effects on transcription/translation, genomic context, annotation resources, in silico pathogenicity predictions, and population allele frequency. The training set, composed of known benign or pathogenic variants, serves as a reference for these algorithms to classify new and unseen variants. Our analysis reveals a limited concordance between the prediction algorithms. Despite comparable true/false positives/negatives, discrepancies persist in variant classification. Certain algorithms exhibit a propensity to over or under-call deleterious mutations. Some demonstrate a tendency to classify random variants in non-cancer genes as deleterious. Challenges include the absence of consensus on informative features, diverse training datasets, and restriction to well annotated proteins/transcripts. Balancing the sensitivity and false positives in detecting cancer drivers is crucial. Integrating individual prediction scores with ML algorithms enhances tool performance but comes with risk of error propagation, and limited accuracy. The study emphasises the need for context-specific variant classification tools, as many variants' impacts are cancer-type specific, and some may drive disease synergistically. Existing tools, designed for a "one variant - one score approach," struggle to capture complex associations, especially those dependent on changes in the tumour microenvironment. Highlighting areas for improvement, the study addresses the "black box" problem in decision processes. While limited interpretability might not hinder practical applications, tools should evolve to assess more complex associations guided by biology. Formal consensus, reference training datasets, and standards are deemed essential for developing next-generation tools. The envisioned context-dependent tools aim to streamline feature complexity, thereby mitigating the black box problem and advancing the accuracy and interpretability of cancer variant annotation. Citation Format: Madhumita, Zbyslaw Sondka, Jon Teague. Evaluating the utility of in silico variant annotation tools for cancer driver detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4884.

Abstract P01: Impact of Germline and Somatic ATM Variants in Chronic Lymphocytic Leukemia (CLL): Clinical Implications and Response to PARP Inhibition

Abstract Background: Next-generation sequencing has revealed numerous Variants of Unknown Significance (VUS) in the ATM gene, important in DNA repair and chronic lymphocytic leukemia (CLL) pathogenesis. This study evaluates the effect of rare ATM germline variants, including VUS, on features of CLL, ATM kinase activity, and response to PARP inhibition. Methods:ATM variants were detected in 885 CLL patients (327 DFCI; 276 German CLL Study Group; 282 ICGC) using DeepVariant, and compared to 5310 ancestry-matched controls. Concurrently, 278 CLL patients with ATM aberrations from clinical sequencing were retrospectively analyzed, annotated by population allele frequency (JCO 2023, Lampson et al.). ATM kinase activity was measured by ATM and KAP1 phosphorylation following gamma-irradiation in primary CLL samples. The impact of talazoparib, a PARP inhibitor, on ATM aberrant and wild-type CLL cell proliferation was also assessed. Results: Among the 885 CLL cases, 130 ATM germline variants were identified by DeepVariant, including 87 missense variants. The top 5 most frequent rare germline missense variants with high odds ratio for association with CLL were ATM p.L2332P (AF cases vs controls, 0.328% vs 0.0188%, OR 17.46), p.L2307F (OR 16.88), p.F763L (OR 18.89), p.Y1442H (OR 35.39) and p.S99G (OR 16.28). In our retrospective clinical cohort, we identified 294 ATM variants with 146 unique variants. Our previously proposed algorithm for classifying germline vs somatic identified 74 germline, with 70 missense, and 72 somatic. Phosphorylation of ATM and KAP1 (pATM, pKAP1) in response to IR was reduced in 13 patients assessed with germline ATM variants (9 rare and 4 non-rare; ATM variant alone group) compared to those without any somatic or germline ATM aberrancy (WT group) (P&amp;lt;0.01). Phosphorylation levels were also significantly lower in 17 patients with rare germline ATM variants with concurrent del(11q) (del11q + ATM germline variant group) compared to 15 with del(11q) alone (del 11q group) (P&amp;lt;0.01). We obtained similar results from Western blot analysis. To assess the sensitivity of ATM deficient cells to talazoparib, we compared proliferation inhibition across groups cocultured with talazoparib for 14 days. The del11q with ATM-somatic group exhibited significantly greater sensitivity to talazoparib at lower dosages compared to ATM WT (talazoparib 0.1 μM, P&amp;lt;0.05; 0.5μM, P=0.098). The monoallelic ATM deficient groups (del11q alone or ATM-germline alone) tended to have lower proliferation, but not significantly. Higher concentrations of talazoparib (2.5μM) strongly inhibited proliferation of all CLLs including WT. Conclusion: This study highlights the prevalence of rare ATM germline variants in CLL and their impact on ATM function in CLL. Our findings also suggest that these variants affect the DNA damage response in primary CLL cells and that ATM biallelic deficiency influences sensitivity to PARP inhibitors. Our evidence could lead to more personalized therapeutic strategies for CLL patients with distinct ATM aberrancies. Citation Format: Kiyomi Mashima, Nicholas Moore, Mariia Mikhaleva, Anna Petráčková, Samantha Shupe, Stacey M Fernandes, Amaro Taylor-Weiner, Riaz Gillani, Hoyin Chu, Seunghun Han, Sabrina Camp, Eric Kofman, Gad Getz, Catherine J. Wu, Svitlana Tyekucheva, Matthew S Davids, Eliezer Mendel Van Allen, Saud AlDubayan, Jennifer R Brown. Impact of Germline and Somatic ATM Variants in Chronic Lymphocytic Leukemia (CLL): Clinical Implications and Response to PARP Inhibition [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P01.

Comparing Classifications from Multiple Variant Annotation Software Solutions Using Real-World Next Generation Sequencing Data from Oncology Testing

Variant annotation is an important step in deciphering the functional impact of genomic variants and their association with diseases. In this study, we analyzed 80 pan-cancer cases that underwent comprehensive genomic testing and compared the auto-classified variant tiers among four globally-available software solutions for variant interpretation from Roche, SOPHiA GENETICS, QIAGEN, and Genoox. The results revealed striking differences in tier classifications, which are believed to be a result of several factors, including subjectivity in the AMP/ASCO/CAP guidelines, threshold settings for variant allele frequencies and population allele frequencies, as well as variation in disease ontologies. Although the software tools described here provide a time-saving and repeatable process for interpretation of genomic data, it is crucial to understand the nuances and various settings for these solutions, as they can strongly influence variant tier classifications and downstream management.

Frequencies of HLA-B alleles in Indonesian Malay Ethnic

BackgroundThe HLA-B alleles have been used as a marker to predict drug-induced adverse reactions and as a major contributor to hypersensitivity reactions. We examined the feasibility of HLA-B alleles as pharmacogenomic markers of drug-induced hypersensitivity in an Indonesian Malay Ethnic. MethodsFifty-eight Indonesian individuals of Malay ethnicity were enrolled in this study. HLA-B alleles were determined using reverse sequence-specific oligonucleotide probe coupled with xMAP technology. ResultsHLA-B*15:02 (15.52%), HLA-B*35:05 (9.48%), and HLA-B*07:05 (7.76%) were frequent alleles in the Indonesian Malay ethnic populations. We discovered at least eight pharmacogenomics markers of drug-induced hypersensitivity: HLA-B*15:02, HLA-B*15:21, HLA-B*13:01, HLA-B*35:05, HLA-B*38:02, HLA-B*51:01, HLA-B*57:01, and HLA-B*58:01. HLA-B*15:02 was in the same serotype group with HLA-B*15:21, which is a B-75 serotype associated with genetic predisposition for carbamazepine-induced Stevens–Johnson syndrome and toxic epidermal necrolysis. The Indonesian population, represented by Malay, Javanese, and Sundanese ethnicities, was similar to South East Asian, Han Chinese, and Taiwanese populations based on HLA-B*15:02 frequency as the most common allele found in Malay ethnics. ConclusionWe provided valuable information on the frequency of drug hypersensitivity-associated HLA-B alleles in Indonesian Malay ethnic population, which can improve treatment safety.

The present and future of forensic genetics

In this article, we discuss the current state and future directions in the field of forensic genetics. The DNA analysis of biological traces found at a crime scene, which was first used in a criminal investigation in 1987, did revolutionize forensic science. Over the past three decades, significant advances have been made in the recognition capacity, speed, and sensitivity of DNA profiling methods, as well as in their capability of typing increasingly complex patterns. Creation of DNA databases of criminals and crime scenes, as well as population allele frequencies, allows suspects to be identified from crime scene samples and DNA evidence to be statistically processed to verify its reliability. At present, it has become possible to identify even single cells left at a crime scene and to successfully analyze ancient human remains. Forensic DNA profiling can be used to identify not only individuals known to the investigating authorities. Experts are increasingly applying new genetic markers that can expand the scope of DNA profiling methods. Modern developments enable extraction of new types of forensically significant information from biological traces, e.g., using molecular approaches to searching for individuals previously unknown to investigators. New methods have been proposed to identify the relationship between the donors of forensic samples and the crimes committed. Modern advances in the decoding of the human genome, as well as the availability of genome-wide analysis and sequencing techniques, pave the way for new forensic DNA tools capable of enhancing the quality of forensic science in the near future.

Evaluation of the genetic basis of familial-associated early-onset hematologic cancers in an ancestral/ethnically diverse population.

Genetic predisposition to hematologic malignancies has historically been addressed utilizing patients recruited from clinical trials and pedigrees constructed at major treatment centers. Such efforts leave unexplored the genetic basis of variations in risk by race/ethnic group shown in population-based surveillance data where cancer registration, compulsory by law, delivers universal enrollment. To address this, we performed exome sequencing on DNA isolated from newborn bloodspots derived from sibling pairs with early-onset cancers across California in which at least one of the siblings developed a hematologic cancer, using unbiased recruitment from the full state population. We identified pathogenic/likely pathogenic (P/ LP) variants among 1,172 selected cancer genes that were private or present at low allele frequencies in reference populations. Within 64 subjects from 32 families, we found 9 LP variants shared between siblings, and an additional 7 such variants in singleton children (not shared with their sibling). In 8 of the shared cases, the ancestral origin of the local haplotype that carries P/LP variants matched the dominant global ancestry of study participant families. This was the case for Latino sibling pairs on FLG and CBLB, non-Latino White sibling pairs in TP53 and NOD2, and a shared GATA2 variant for a non-Latino Black sibling pair. A new inherited mutation in HABP2 was identified in a sibling pair, one with diffuse large B-cell lymphoma and the other with neuroblastoma. Overall, the profile of P/LP germline variants across ancestral/ethnic groups suggests that rare alleles contributing to hematologic diseases originate within their race/ethnic origin parental populations, demonstrating the value of this discovery process in diverse, population-based registries.