Genetic test utilization and diagnostic yield in adult patients with neurological disorders

The yield of genetic workup for middle-aged and elderly patients with neurological disorders in a real-world setting

Genetic workup is becoming increasingly common in the clinical assessment of neurological disorders. We evaluated its yield among middle-aged and elderly neurological patients, in a real-world context. This retrospective study included 368 consecutive Israeli patients aged 50 years and older (202 [54.9%] males), who were referred to a single neurogenetics clinic between 2017 and mid-2023. All had neurological disorders, without a previous molecular diagnosis. Demographic, clinical and genetic data were collected from medical records. The mean age at first genetic counseling at the clinic was 62.3 ± 7.8 years (range 50-85 years), and the main indications for referral were neuromuscular, movement and cerebrovascular disorders, as well as cognitive impairment and dementia. Out of the 368 patients, 245 (66.6%) underwent genetic testing that included exome sequencing (ES), analysis of nucleotide repeat expansions, detection of specific mutations, targeted gene panel sequencing or chromosomal microarray analysis. Overall, 80 patients (21.7%) received a molecular diagnosis due to 36 conditions, accounting for 32.7% of the patients who performed genetic testing. The diagnostic rates were highest for neuromuscular (58/186 patients [31.2%] in this group, 39.2% of 148 tested individuals) and movement disorders (14/79 [17.7%] patients, 29.2% of 48 tested), but lower for other disorders. Testing of nucleotide repeat expansions and ES provided a diagnosis to 28/73 (38.4%) and 19/132 (14.4%) individuals, respectively. Based on our findings, genetic workup and testing are useful in the diagnostic process of neurological patients aged ≥50 years, in particular for those with neuromuscular and movement disorders.

Diagnostic yield of clinical exome sequencing in adulthood in medical genetics clinics

Clinical exome sequencing (ES) is the most comprehensive genomic test to identify underlying genetic diseases in Canada. We performed this retrospective cohort study to investigate the diagnostic yield of clinical ES in adulthood. Inclusion criteria were: (1) Adult patients ≥18 years old; (2) Patients underwent clinical ES between January 1 and December 31, 2021; (3) Patients were seen in the Department of Medical Genetics. We reviewed patient charts. We applied American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification guidelines for interpretation of variants. Non-parametric Fisher's exact statistical test was used. Seventy-seven patients underwent clinical ES. Fourteen different genetic diseases were confirmed in 15 patients: FBXO11, MYH7, MED13L, NSD2, ANKRD11 (n = 2), SHANK3, RHOBTB2, CDKL5, TRIO, TCF4, SCN1, SMAD3, POGZ, and EIF2B3 diseases. The diagnostic yield of clinical ES was 19.5%. Patients with a genetic diagnosis had a significantly higher frequency of neurodevelopmental disorders than those with no genetic diagnosis (p = 0.00339). The diagnostic yield of clinical ES was the highest in patients with seizures (35.7%), and with progressive neurodegenerative diseases (33.3%). Clinical ES is a helpful genomic test to provide genetic diagnoses to the patients who are referred to medical genetic clinics due to suspected genetic diseases in adulthood to end their diagnostic odyssey. Targeted next generation sequencing panels for specific phenotypes may decrease the cost of genomic test in adulthood.

Genetic diagnosis for adult patients at a genetic clinic

Clinical utility of genetic testing has rapidly increased in the past decade to identify the definitive diagnosis, etiology, and specific management. The majority of patients receiving testing are children. There are several barriers for genetic tests in adult patients; barriers may arise from either patients or clinicians. Our study aims to realize the detection rate and the benefits of genetic tests in adults. We conducted a prospective study of 10 adult patients who were referred to a genetic clinic. Exome sequencing (ES) was pursued in all cases, and chromosomal microarray (CMA) was performed for six cases. Our result is impressive; six cases (60%) received likely pathogenic and pathogenic variants. Four definitive diagnosis cases had known pathogenic variants in KCNJ2, TGFBR1, SCN1A, and FBN1, whereas another two cases revealed novel likely pathogenic and pathogenic variants in GNB1 and DNAH9. Our study demonstrates the success in genetic diagnosis in adult patients: four cases with definitive, two cases with possible, and one case with partial diagnosis. The advantage of diagnosis is beyond obtaining the diagnosis itself, but also relieving any doubt for the patient regarding any previous questionable diagnosis, guide for management, and recurrence risk in their children or family members. Therefore, this supports the value of genetic testing in adult patients.

Precision medicine for genetic epilepsy on the horizon: Recent advances, present challenges, and suggestions for continued progress

The genetic basis of many epilepsies is increasingly understood, giving rise to the possibility of precision treatments tailored to specific genetic etiologies. Despite this, current medical therapy for most epilepsies remains imprecise, aimed primarily at empirical seizure reduction rather than targeting specific disease processes. Intellectual and technological leaps in diagnosis over the past 10 years have not yet translated to routine changes in clinical practice. However, the epilepsy community is poised to make impressive gains in precision therapy, with continued innovation in gene discovery, diagnostic ability, and bioinformatics; increased access to genetic testing and counseling; fuller understanding of natural histories; agility and rigor in preclinical research, including strategic use of emerging model systems; and engagement of an evolving group of stakeholders (including patient advocates, governmental resources, and clinicians and scientists in academia and industry). In each of these areas, we highlight notable examples of recent progress, new or persistent challenges, and future directions. The future of precision medicine for genetic epilepsy looks bright if key opportunities on the horizon can be pursued with strategic and coordinated effort.

Analyzing Precision Medicine Utilization with Real-World Data: A Scoping Review

Precision medicine (PM), specifically genetic-based testing, is currently used in over 140,000 individual tests to inform the clinical management of disease. Though several databases (e.g., the NIH Genetic Testing Registry) demonstrate the availability of these sequencing-based tests, we do not currently understand the extent to which these tests are used. There exists a need to synthesize the body of real-world data (RWD) describing the use of sequencing-based tests to inform their appropriate use. To accomplish this, we performed a scoping review to examine what RWD sources have been used in studies of PM utilization between January 2015 and August 2021 to characterize the use of genome sequencing (GS), exome sequencing (ES), tumor sequencing (TS), next-generation sequencing-based panels (NGS), gene expression profiling (GEP), and pharmacogenomics (PGx) panels. We abstracted variables describing the use of these types of tests and performed a descriptive statistical analysis. We identified 440 articles in our search and included 72 articles in our study. Publications based on registry databases were the most common, followed by studies based on private insurer administrative claims. Slightly more than one-third (38%) used integrated datasets. Two thirds (67%) of the studies focused on the use of tests for oncological clinical applications. We summarize the RWD sources used in peer-reviewed literature on the use of PM. Our findings will help improve future study design by encouraging the use of centralized databases and registries to track the implementation and use of PM.

NeuroSCORE is a genome-wide omics-based model that identifies candidate disease genes of the central nervous system

To identify candidate disease genes of central nervous system (CNS) phenotypes, we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We identified five genome-wide metrics highly associated with CNS phenotypes to score 19,601 protein-coding genes. Genes scored one point per metric (range: 0-5), identifying 8298 scored genes (scores ≥ 1) and 1601 "high scoring" genes (scores ≥ 3). Using logistic regression, we determined the odds ratio that genes with a NeuroSCORE from 1 to 5 would be associated with known CNS-related phenotypes compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts and aggregate mouse model data. High scoring genes are associated with CNS phenotypes (OR = 5.5, p < 2E-16), enriched in case CNVs, and mouse ortholog genes that cause behavioral and nervous system abnormalities. We identified 1058 high scoring genes with no disease association in OMIM. Transforming the logistic regression results indicates high scoring genes have an 84-92% chance of being associated with a CNS phenotype. Top scoring genes include GRIA1, MAP4K4, SF1, TNPO2, and ZSWIM8. Finally, we interrogated CNVs in the Clinical Genome Resource, finding the majority of clinically significant CNVs contain high scoring genes. These findings can direct future research and improve molecular diagnostics.

No-boundary thinking: a viable solution to ethical data-driven AI in precision medicine

Today Artificial Intelligence (AI) supports difficult decisions about policy, health, and our personal lives. The AI algorithms we develop and deploy to make sense of information, are informed by data, and based on models that capture and use pertinent details of the population or phenomenon being analyzed. For any application area, more importantly in precision medicine which directly impacts human lives, the data upon which algorithms are run must be procured, cleaned, and organized well to assure reliable and interpretable results, and to assure that they do not perpetrate or amplify human prejudices. This must be done without violating basic assumptions of the algorithms in use. Algorithmic results need to be clearly communicated to stakeholders and domain experts to enable sound conclusions. Our position is that AI holds great promise for supporting precision medicine, but we need to move forward with great care, with consideration for possible ethical implications. We make the case that a no-boundary or convergent approach is essential to support sound and ethical decisions. No-boundary thinking supports problem definition and solving with teams of experts possessing diverse perspectives. When dealing with AI and the data needed to use AI, there is a spectrum of activities that needs the attention of a no-boundary team. This is necessary if we are to draw viable conclusions and develop actions and policies based on the AI, the data, and the scientific foundations of the domain in question.

Next-generation gene panel testing in adolescents and adults in a medical neuropsychiatric genetics clinic

Intellectual disability (ID) encompasses a clinically and genetically heterogeneous group of neurodevelopmental disorders that may present with psychiatric illness in up to 40% of cases. Despite the evidence for clinical utility of genetic panels in pediatrics, there are no published studies in adolescents/adults with ID or autism spectrum disorder (ASD). This study was approved by our institutional research ethics board. We retrospectively reviewed the medical charts of all patients evaluated between January 2017 and December 2019 in our adult neuropsychiatric genetics clinic at the McGill University Health Centre (MUHC), who had undergone a comprehensive ID/ASD gene panel. Thirty-four patients aged > 16 years, affected by ID/ASD and/or other neuropsychiatric/behavioral disorders, were identified. Pathogenic or likely pathogenic variants were identified in one-third of our cohort (32%): 8 single-nucleotide variants in 8 genes (CASK, SHANK3, IQSEC2, CHD2, ZBTB20, TREX1, SON, and TUBB2A) and 3 copy number variants (17p13.3, 16p13.12p13.11, and 9p24.3p24.1). The presence of psychiatric/behavioral disorders, regardless of the co-occurrence of ID, and, at a borderline level, the presence of ID alone were associated with positive genetic findings (p = 0.024 and p = 0.054, respectively). Moreover, seizures were associated with positive genetic results (p = 0.024). One-third of individuals presenting with psychiatric illness who met our red flags for Mendelian diseases have pathogenic or likely pathogenic variants which can be identified using a comprehensive ID/ASD gene panel (~ 2500 genes) performed on an exome backbone.

Temporal trends and yield of clinical diagnostic genetic testing in adult neurology

While genetics evaluation is increasingly utilized in adult neurology patients, its usage and efficacy are not well characterized. Here, we report our experience with 1461 consecutive patients evaluated in an adult neurogenetics clinic at a large academic medical center between January 2015 and March 2020. Of the 1461 patients evaluated, 1215 patients were referred for the purposes of identifying a genetic diagnosis for an undiagnosed condition, 90.5% of whom underwent genetic testing. The modalities of genetic testing utilized varied across referral diagnostic categories, including a range of utilization of whole exome sequencing (WES) as an initial test in 13.9% of neuromuscular patients to 52.9% in white matter disorder patients. The usage of WES increased over time, from 7.7% of initial testing in 2015 to a peak of 27.3% in 2019. Overall, genetic testing yielded a causal genetic diagnosis in 30.7% of patients. This yield was higher in certain referring diagnosis categories, such as neuromuscular (39.0%) and epilepsy (29.8%). Our study demonstrates that evaluation at an adult neurogenetics referral center can yield diagnoses in a substantial fraction of patients. Additional research will be needed to determine optimal genetic testing strategies and cost effectiveness of adult neurogenetics evaluation.

Utilization and uptake of clinical genetics services in high-income countries: A scoping review

Ongoing rapid growth in the need for genetic services has the potential to severely strain the capacity of the clinical genetics workforce to deliver this care. Unfortunately, assessments of the scale of this health policy challenge and potential solutions are hampered by the lack of a consolidated evidence base on the growth in genetic service utilization. To enable health policy research and strategic planning by health systems in this area, we conducted a scoping review of the literature on the utilization and uptake of clinical genetics services in high-income countries published between 2010 and 2018. One-hundred-and-ninety-five unique studies were included in the review. Most focused on cancer (85/195; 44%) and prenatal care (50/195; 26%), which are consistently the two areas with the greatest volume of genetic service utilization in both the United States and other high-income countries. Utilization and uptake rates varied considerably and were influenced by contextual factors including health system characteristics, provider knowledge, and patient preferences. Moreover, growth in genetic service utilization appears to be driven to a significant degree by technological advances and the integration of new tests into clinical care. Our review highlights both the policy challenge posed by the rapid growth in the utilization of genetic services and the variability in this trend across clinical indications and health systems.

Genetic skin disorders: The value of a multidisciplinary clinic

Genodermatoses are inherited disorders with skin manifestations and can present with multisystem involvement, resulting in challenges in diagnosis and treatment. To address this, the expertise of dermatology and clinical genetics through a multidisciplinary clinic (Genodermatoses Clinic) were combined. A retrospective cohort study of 45 children seen between March 2018 and February 2019 in the Genodermatoses Clinic at The Children's Hospital of Philadelphia was performed. Patient demographics, referral information, genetic testing modality, diagnoses, and patient satisfaction scores were evaluated to assess the clinic's impact. The majority of patients (42.2%) were referred from Dermatology and 86.7% were referred for diagnosis. Two-thirds of the patients were recommended genetic testing, and subsequently 73.3% completed testing. Nearly three-quarters, 26 out of 36 patients (72.2%), of our undiagnosed patients received a clinical and/or molecular diagnosis, which is imperative in managing their care. Twenty-two individuals pursued genetic testing. In eight individuals (36%), molecular testing was diagnostic. However, in two individuals the molecular diagnosis did not completely explain the phenotype. However, there are still obstacles to genetic testing, such as cost of testing and insurance barriers. Almost all (91.4%) rated the Genodermatoses Clinic as "Very Good," the top Press Ganey score. High patient satisfaction scores suggest a positive impact of the Genodermatoses clinic, emphasizing the importance to increase support for the clinical and administrative time needed for patients with genodermatoses.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice .

Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging

To understand the value and clinical impact of surveying genome-wide disease-causing genes and variants, we used a prospective cohort study design that enrolled volunteers who agreed to have their whole genome sequenced and to participate in deep phenotyping using clinical laboratory tests, metabolomics technologies, and advanced noninvasive imaging. The genomic results are integrated with the phenotype results. Approximately 1 in 6 adult individuals (17.3%) had genetic findings and, when integrated with deep phenotyping data, including family/medical histories with genetic findings, 1 in 9 (11.5%) had genotype and phenotype associations. Genomics and metabolomics association analysis revealed 5.1% of heterozygotes with phenotype manifestations affecting serum metabolite levels. We report observations from our study in which health outcomes and benefits were not measured.

Genome sequencing has established clinical utility for rare disease diagnosis. While increasing numbers of individuals have undergone elective genome sequencing, a comprehensive study surveying genome-wide disease-associated genes in adults with deep phenotyping has not been reported. Here we report the results of a 3-y precision medicine study with a goal to integrate whole-genome sequencing with deep phenotyping. A cohort of 1,190 adult participants (402 female [33.8%]; mean age, 54 y [range 20 to 89+]; 70.6% European) had whole-genome sequencing, and were deeply phenotyped using metabolomics, advanced imaging, and clinical laboratory tests in addition to family/medical history. Of 1,190 adults, 206 (17.3%) had at least 1 genetic variant with pathogenic (P) or likely pathogenic (LP) assessment that suggests a predisposition of genetic risk. A multidisciplinary clinical team reviewed all reportable findings for the assessment of genotype and phenotype associations, and 137 (11.5%) had genotype and phenotype associations. A high percentage of genotype and phenotype associations (>75%) was observed for dyslipidemia (n = 24), cardiomyopathy, arrhythmia, and other cardiac diseases (n = 42), and diabetes and endocrine diseases (n = 17). A lack of genotype and phenotype associations, a potential burden for patient care, was observed in 69 (5.8%) individuals with P/LP variants. Genomics and metabolomics associations identified 61 (5.1%) heterozygotes with phenotype manifestations affecting serum metabolite levels in amino acid, lipid and cofactor, and vitamin pathways. Our descriptive analysis provides results on the integration of whole-genome sequencing and deep phenotyping for clinical assessments in adults.