Influence of autozygosity on common disease risk across the phenotypic spectrum.

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (FROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity.

Inherited mutations affecting the SRCAP complex are central in moderate-penetrance predisposition to uterine leiomyomas.

Uterine leiomyomas (ULs) are benign smooth muscle tumors that are common in premenopausal women. Somatic alterations in MED12, HMGA2, FH, genes encoding subunits of the SRCAP complex, and genes involved in Cullin 3-RING E3 ligase neddylation are mutually exclusive UL drivers. Established predisposition genes explain only partially the estimated heritability of leiomyomas. Here, we examined loss-of-function variants across 18,899 genes in a cohort of 233,614 White European women, revealing variants in four genes encoding SRCAP complex subunits (YEATS4, ZNHIT1, DMAP1, and ACTL6A) with a significant association to ULs, and YEATS4 and ZNHIT1 strikingly rank first and second, respectively. Positive mutation status was also associated with younger age at diagnosis and hysterectomy. Moderate-penetrance UL risk was largely attributed to rare non-synonymous mutations affecting the SRCAP complex. To examine this disease phenotype more closely, we set out to identify inherited mutations affecting the SRCAP complex in our in-house sample collection of Finnish individuals with ULs (n = 860). We detected one individual with an ACTL6A splice-site mutation, two individuals with a YEATS4 missense mutation, and four individuals with DMAP1 mutations: one splice-site, one nonsense, and two missense variants. These individuals had large and/or multiple ULs, were often diagnosed at an early age, and many had family history of ULs. When a somatic second hit was found, ACTL6A and DMAP1 were silenced in tumors by somatic mutation and YEATS4 by promoter hypermethylation. Decreased H2A.Z staining was observed in the tumors, providing further evidence for the pathogenic nature of the germline mutations. Our results establish inactivation of genes encoding SRCAP complex subunits as a central contributor to moderate-penetrance UL predisposition.

Analysis of missense variants in the human genome reveals widespread gene-specific clustering and improves prediction of pathogenicity.

We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (46%) and 172 (20%) genes, respectively, revealing that variant clustering is widespread across the human exome. This clustering likely occurs as a consequence of mechanisms shaping pathogenicity at the protein level, as illustrated by the overlap of some clusters with known functional domains. We then took advantage of these findings to develop a pathogenicity predictor, MutScore, that integrates qualitative features of DNA substitutions with the new additional information derived from this positional clustering. Using a random forest approach, MutScore was able to identify pathogenic missense mutations with very high accuracy, outperforming existing predictive tools, especially for variants associated with autosomal-dominant disease and cancer. Thus, the within-gene clustering of pathogenic and benign DNA changes is an important and previously underappreciated feature of the human exome, which can be harnessed to improve the prediction of pathogenicity and disambiguation of DNA variants of uncertain significance.

Uncertainty in Genomics Impacts Precision Medicine.

As exacting as genetic and genomic testing have become, health professionals continue to encounter uncertainty in their applications to medical practice. As examining the human genome at more refined levels increases, so is the likelihood of encountering uncertainty about the meaning of the information. The history of this concept informs how we might confront and deal with uncertainty, and what the future might hold. Precision medicine holds great promise for establishing more accurate diagnoses, directing specific therapy to patients who will most benefit from it, and avoiding treatments in patients who are most likely to suffer adverse consequences, or at best not benefit. But its application depends importantly on the proper interpretation of a person's genotype.

CoverageMaster: comprehensive CNV detection and visualization from NGS short reads for genetic medicine applications.

CoverageMaster (CoM) is a copy number variation (CNV) calling algorithm based on depth-of-coverage maps designed to detect CNVs of any size in exome [whole exome sequencing (WES)] and genome [whole genome sequencing (WGS)] data. The core of the algorithm is the compression of sequencing coverage data in a multiscale Wavelet space and the analysis through an iterative Hidden Markov Model. CoM processes WES and WGS data at nucleotide scale resolution and accurately detects and visualizes full size range CNVs, including single or partial exon deletions and duplications. The results obtained with this approach support the possibility for coverage-based CNV callers to replace probe-based methods such as array comparative genomic hybridization and multiplex ligation-dependent probe amplification in the near future.

Enhancing prediction accuracy of coronary artery disease through machine learning-driven genomic variant selection.

Machine learning (ML) methods are increasingly becoming crucial in genome-wide association studies for identifying key genetic variants or SNPs that statistical methods might overlook. Statistical methods predominantly identify SNPs with notable effect sizes by conducting association tests on individual genetic variants, one at a time, to determine their relationship with the target phenotype. These genetic variants are then used to create polygenic risk scores (PRSs), estimating an individual's genetic risk for complex diseases like cancer or cardiovascular disorders. Unlike traditional methods, ML algorithms can identify groups of low-risk genetic variants that improve prediction accuracy when combined in a mathematical model. However, the application of ML strategies requires addressing the feature selection challenge to prevent overfitting. Moreover, ensuring the ML model depends on a concise set of genomic variants enhances its clinical applicability, where testing is feasible for only a limited number of SNPs. In this study, we introduce a robust pipeline that applies ML algorithms in combination with feature selection (ML-FS algorithms), aimed at identifying the most significant genomic variants associated with the coronary artery disease (CAD) phenotype. The proposed computational approach was tested on individuals from the UK Biobank, differentiating between CAD and non-CAD individuals within this extensive cohort, and benchmarked against standard PRS-based methodologies like LDpred2 and Lassosum. Our strategy incorporates cross-validation to ensure a more robust evaluation of genomic variant-based prediction models. This method is commonly applied in machine learning strategies but has often been neglected in previous studies assessing the predictive performance of polygenic risk scores. Our results demonstrate that the ML-FS algorithm can identify panels with as few as 50 genetic markers that can achieve approximately 80% accuracy when used in combination with known risk factors. The modest increase in accuracy over PRS performances is noteworthy, especially considering that PRS models incorporate a substantially larger number of genetic variants. This extensive variant selection can pose practical challenges in clinical settings. Additionally, the proposed approach revealed novel CAD-genetic variant associations.

Two New Families and a Literature Review of ELOVL4-Associated Spinocerebellar Ataxia Type 34.

Autosomal dominant variants in ELOVL4 cause spinocerebellar ataxia type 34 (SCA34; ATX-ELOVL4), classically associated with a skin condition known as erythrokeratoderma. Here, we report a large Italian-Maltese-Australian family with spinocerebellar ataxia. Notably, while there were dermatological manifestations (eczema), erythrokeratoderma was not present. Using a next-generation sequencing panel, we identified a previously reported ELOVL4 variant, NM_022726.4: c.698C > T p.(Thr233Met). The variant was initially classified as a variant of uncertain significance; however, through segregation studies, we reclassified the variant as likely pathogenic. We next identified an individual from another family (Algerian-Maltese-Australian) with the same ELOVL4 variant with spinocerebellar ataxia but without dermatological manifestations. We subsequently performed the first dedicated literature review of ELOVL4-associated ataxia to gain further insights into genotype-phenotype relationships. We identified a total of 60 reported cases of SCA34 to date. The majority had gait ataxia (88.3%), limb ataxia (76.7%), dysarthria (63.3%), and nystagmus (58.3%). Of note, skin lesions related to erythrokeratoderma were seen in a minority of cases (33.3%). Other extracerebellar manifestations included pyramidal tract signs, autonomic disturbances, retinitis pigmentosa, and cognitive impairment. For brain MRI data, cerebellar atrophy was seen in all cases (100%), whereas the hot cross bun sign (typically associated with multiple system atrophy type C) was seen in 32.4% of cases. Our family study and literature review highlight the variable phenotypic spectrum of SCA34. Importantly, it shows that erythrokeratoderma is not found in most cases and that, while a dermatological assessment may be helpful in these patients, SCA34 diagnosis should be considered irrespective of dermatological manifestations.

"Why did I choose genetics?": A survey of current and recent medical genetics and genomics residents provides insight into recruitment efforts.

There is a shortage of clinical geneticists, even with concerted recruitment efforts. Previously, no data had been collected about why young career geneticists chose this specialty. To investigate this question, we carried out a survey of current and recent medical genetics and genomics residents. The goal of this survey was to understand their reasons for pursuing medical genetics and genomics as a specialty. Results demonstrate that, for most, interest in genetics begins in medical school and was largely influenced by mentorship. This suggests that placing greater focus on introducing medical genetics as a clinical specialty and fostering robust mentorship of students in preclinical years may increase recruitment into medical genetics residencies.

Personal journeys to and in human genetics and dysmorphology.

Genetics has become a critical component of medicine over the past five to six decades. Alongside genetics, a relatively new discipline, dysmorphology, has also begun to play an important role in providing critically important diagnoses to individuals and families. Both have become indispensable to unraveling rare diseases. Almost every medical specialty relies on individuals experienced in these specialties to provide diagnoses for patients who present themselves to other doctors. Additionally, both specialties have become reliant on molecular geneticists to identify genes associated with human disorders. Many of the medical geneticists, dysmorphologists, and molecular geneticists traveled a circuitous route before arriving at the position they occupied. The purpose of collecting the memoirs contained in this article was to convey to the reader that many of the individuals who contributed to the advancement of genetics and dysmorphology since the late 1960s/early 1970s traveled along a journey based on many chances taken, replying to the necessities they faced along the way before finding full enjoyment in the practice of medical and human genetics or dysmorphology. Additionally, and of equal importance, all exhibited an ability to evolve with their field of expertise as human genetics became human genomics with the development of novel technologies.

Ocular manifestations in a cohort of 43 patients with KBG syndrome.

Ophthalmological conditions are underreported in patients with KBG syndrome, which is classically described as presenting with dental, developmental, intellectual, skeletal, and craniofacial abnormalities. This study analyzed the prevalence of four ophthalmological conditions (strabismus, astigmatism, myopia, hyperopia) in 43 patients with KBG syndrome carrying variants in ANKRD11 or deletions in 16q24.3 and compared it to the literature. Forty-three patients were recruited via self-referral or a private Facebook group hosted by the KBG Foundation, with 40 of them having pathogenic or likely pathogenic variants. Virtual interviews were conducted to collect a comprehensive medical history verified by medical records. From these records, data analysis was performed to calculate the prevalence of ophthalmological conditions. Out of the 40 participants with pathogenic or likely pathogenic variants, strabismus was reported in 9 (22.5%) participants, while astigmatism, myopia, and hyperopia were reported in 11 (27.5%), 6 (15.0%), and 8 (20.0%) participants, respectively. Other reported conditions include anisometropia, amblyopia, and nystagmus. When compared to the literature, the prevalence of strabismus and refractive errors is higher than other studies. However, more research is needed to determine if variants in ANKRD11 play a role in abnormal development of the visual system. In patients with established KBG syndrome, screening for misalignment or refractive errors should be done, as interventions in patients with these conditions can improve functioning and quality of life.

Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study.

BACKGROUND: While characteristic facial features provide important clues for finding the correct diagnosis in genetic syndromes, valid assessment can be challenging. The next-generation phenotyping algorithm DeepGestalt analyzes patient images and provides syndrome suggestions. GestaltMatcher matches patient images with similar facial features. The new D-Score provides a score for the degree of facial dysmorphism. OBJECTIVE: We aimed to test state-of-the-art facial phenotyping tools by benchmarking GestaltMatcher and D-Score and comparing them to DeepGestalt. METHODS: Using a retrospective sample of 4796 images of patients with 486 different genetic syndromes (London Medical Database, GestaltMatcher Database, and literature images) and 323 inconspicuous control images, we determined the clinical use of D-Score, GestaltMatcher, and DeepGestalt, evaluating sensitivity; specificity; accuracy; the number of supported diagnoses; and potential biases such as age, sex, and ethnicity. RESULTS: DeepGestalt suggested 340 distinct syndromes and GestaltMatcher suggested 1128 syndromes. The top-30 sensitivity was higher for DeepGestalt (88%, SD 18%) than for GestaltMatcher (76%, SD 26%). DeepGestalt generally assigned lower scores but provided higher scores for patient images than for inconspicuous control images, thus allowing the 2 cohorts to be separated with an area under the receiver operating characteristic curve (AUROC) of 0.73. GestaltMatcher could not separate the 2 classes (AUROC 0.55). Trained for this purpose, D-Score achieved the highest discriminatory power (AUROC 0.86). D-Score's levels increased with the age of the depicted individuals. Male individuals yielded higher D-scores than female individuals. Ethnicity did not appear to influence D-scores. CONCLUSIONS: If used with caution, algorithms such as D-score could help clinicians with constrained resources or limited experience in syndromology to decide whether a patient needs further genetic evaluation. Algorithms such as DeepGestalt could support diagnosing rather common genetic syndromes with facial abnormalities, whereas algorithms such as GestaltMatcher could suggest rare diagnoses that are unknown to the clinician in patients with a characteristic, dysmorphic face.

Identifying knowledge deficiencies in genetics education among medical students and interns in Saudi Arabia- A cross-sectional study.

BACKGROUND: Understanding genetics is crucial for medical students, particularly in Saudi Arabia, where genetic disorders are prevalent owing to high rates of consanguineous marriages. This knowledge is essential for the early detection, prevention, and management of genetic disorders, and for incorporating medical genetics and genomics into patient care. This study aimed to assess the current state of genetics knowledge among medical students and interns across Saudi Arabia and to identify knowledge gaps in genetics. METHOD: A cross-sectional study was conducted between August and September 2023 involving 732 medical students from all regions of Saudi Arabia. The participants completed a validated questionnaire assessing their knowledge of basic genetics, genetic inheritance, genetic testing, and clinical genetics. RESULT: Over 60% of medical students and interns reported that they considered themselves to have only slight knowledge in all areas of genetics. The results revealed a general lack of medical genetic understanding among students and interns, particularly regarding genetic inheritance and testing. For genetic inheritance, slight knowledge was found in 65.2% of pre-clinical, 60.1% of clinical, and 53.2% of interns, with significant differences between groups (p < 0.001). In genetic testing, 75.4% of pre-clinical, 83.9% of clinical, and 90.6% of interns showed slight knowledge, with significant differences across stages (p = 0.021). This study also found that lectures, genetics laboratories, and problem-solving sessions were the preferred resources for learning genetics. CONCLUSION: The current study revealed a notable deficiency in the understanding of medical genetics among medical students and interns in Saudi Arabia, particularly regarding genetic inheritance and testing. This is consistent with previous research highlighting the widespread lack of genetics knowledge among medical students. Integrating more comprehensive genetics education, especially during the clinical years, could improve students' preparedness and confidence in managing genetic disorders. These findings highlight the critical need for curriculum development to equip future physicians with the essential skills for managing genetic disorders.

Investigation on the construction of teaching case base in medical genetics.

Medical genetics is a basic medical course that discusses the diagnosis, prevention and treatment of diseases in relation with genetic factors. This course requires students who have abilities of strong logical thinking, independent thinking, problem analyzing and solving. Single "cramming" teaching is difficult to mobilize students' autonomous learning, and hardly achieves teaching effect of medical genetics. Teaching of case-based discussion breaks passive teaching mode in traditional class. The teacher throws out typically clinical cases. The students prepare materials around relevant problems of cases, and carry out class discussion. Then, key and difficult points of the course are integrated in teaching and learning interaction, which reaches a remarkable effect of teaching. Since 2013, the teaching and research group has carried out teaching of case-based discussion in undergraduates majoring in clinical medicine. In this paper, we screen and sort clinical cases on the basis of course teaching plan and case-based discussion in the teaching of medical genetics. The cases are summarized into 8 chapters in teaching case base, which basically cover the teaching of disease genetics and clinical genetics.The construction of teaching case base in medical genetics has realized the deep integration of clinical cases and teaching. Students can understand and master important and difficult points of teaching in a more intuitive way, which is helpful to stimulate students' innovative thinking, improve students' learning interest and class participation.

Age-related survey of clinical genetics literature and related resources.

Genetic conditions affect people throughout their entire lifespan; however, many clinical geneticists focus on the care of pediatric individuals. We analyzed the medical literature and related resources to help assess to what extent adults with genetic diseases were represented. This included general literature searches of PubMed (from 2001 through 2022), specific databases (the FDA orphan drug list and the Clinical Genomic Database) related to management and direct treatment of genetic conditions, and textbooks and morphology guides relevant to the diagnosis of genetic conditions. In the field of genetics/genomics in general, we overall detected a statistically significant emphasis on pediatric populations in the medical literature compared to select other disciplines and compared with the global population distribution. Clinical genetics articles about adults tended to focus on younger adult ages. In clinical genetics, management and treatments, as well as illustrations in several educational/diagnostic resources tended to focus on pediatric populations.

Clinical genome sequencing: Three years' experience at a tertiary children's hospital.

PURPOSE: Genome sequencing (GS) may shorten the diagnostic odyssey for patients, but clinical experience with this assay in nonresearch settings remains limited. Texas Children's Hospital began offering GS as a clinical test to admitted patients in 2020, providing an opportunity to study GS utilization, possibilities for test optimization, and testing outcomes. METHODS: We retrospectively reviewed GS orders for admitted patients for a nearly 3-year period from March 2020 through December 2022. We gathered anonymized clinical data from the electronic health record to answer the study questions. RESULTS: The diagnostic yield over 97 admitted patients was 35%. The majority of GS clinical indications were neurologic or metabolic (61%) and most patients were in intensive care (58%). Tests were often characterized as candidates for intervention/improvement (56%), frequently because of redundancy with prior testing. Patients receiving GS without prior exome sequencing (ES) had higher diagnostic rates (45%) than the cohort as a whole. In 2 cases, GS revealed a molecular diagnosis that is unlikely to be detected by ES. CONCLUSION: The performance of GS in clinical settings likely justifies its use as a first-line diagnostic test, but the incremental benefit for patients with prior ES may be limited.

Optimization of the biochemical genetics laboratory rotation using a multidesign approach to curriculum.

PURPOSE: A biochemical genetics laboratory rotation is required for multiple genetics training programs. Traditionally, this rotation has been observational with experience being dependent upon cases released and availability of laboratory director(s), resulting in inconsistent learning opportunities. This curriculum was created to standardize the learning experience. METHODS: The revised rotation provides multiple teaching modalities including small group didactic sessions (flipped classroom model), case-based sessions, and hands-on laboratory experience. Trainees prepare a presentation (learning by teaching) and discuss the differential diagnosis, metabolic pathway, newborn screening, treatment, and molecular characteristics of the gene(s) implicated. Learner assessment is performed using pre- and post-tests, learner evaluations, and instructor feedback. RESULTS: Pre- and post-test scores were significantly different (P < .001) for learners from all programs. Participants found the course to be effective, increased their learning, and allowed them to interact with metabolic testing results in helpful ways. Faculty appreciated the use of prerecorded lectures and additional time for in-depth teaching on interesting cases. CONCLUSION: The revised rotation has been well received by trainees and faculty. Interaction of learners with the laboratory staff was optimized by ensuring all parties were prepared to teach and learn. Future directions include expanding the program to include remote learners from other centers.

The prevalence and phenotypic range associated with biallelic PKDCC variants.

PKDCC encodes a component of Hedgehog signalling required for normal chondrogenesis and skeletal development. Although biallelic PKDCC variants have been implicated in rhizomelic shortening of limbs with variable dysmorphic features, this association was based on just two patients. In this study, data from the 100 000 Genomes Project was used in conjunction with exome sequencing and panel-testing results accessed via international collaboration to assemble a cohort of eight individuals from seven independent families with biallelic PKDCC variants. The allelic series included six frameshifts, a previously described splice-donor site variant and a likely pathogenic missense variant observed in two families that was supported by in silico structural modelling. Database queries suggested that the prevalence of this condition is between 1 of 127 and 1 of 721 in clinical cohorts with skeletal dysplasia of unknown aetiology. Clinical assessments, combined with data from previously published cases, indicate a predominantly upper limb involvement. Micrognathia, hypertelorism and hearing loss appear to be commonly co-occurring features. In conclusion, this study strengthens the link between biallelic inactivation of PKDCC and rhizomelic limb-shortening and will enable clinical testing laboratories to better interpret variants in this gene.

Digenic genotypes: The interface of inbreeding, linkage, and linkage disequilibrium.

Many traits in populations are well understood as being Mendelian effects at single loci or additive polygenic effects across numerous loci. However, there are important phenomena and traits that are intermediate between these two extremes and are known as oligogenic traits. Here we investigate digenic, or two-locus, traits and how their frequencies in populations are affected by non-random mating, specifically inbreeding, linkage disequilibrium, and selection. These effects are examined both separately and in combination to demonstrate how many digenic traits, especially double homozygous ones, can show significant, sometimes unexpected, changes in population frequency with inbreeding, linkage, and linkage disequilibrium. The effects of selection on deleterious digenic traits are also detailed. These results are applied to both digenic traits of medical significance as well as measuring inbreeding in natural populations.

Whither social media and clinical genetics?

Social media has become ubiquitous in daily life, and increasingly impacts medical and scientific fields, including related to clinical genetics. Recent events have led to questions about the use of certain social media platforms, as well as social media more generally. We discuss these considerations, including alternative and emerging platforms that can offer forums for the clinical genetics and related communities.

Perspectives on the future of dysmorphology.

The field of clinical genetics and genomics continues to evolve. In the past few decades, milestones like the initial sequencing of the human genome, dramatic changes in sequencing technologies, and the introduction of artificial intelligence, have upended the field and offered fascinating new insights. Though difficult to predict the precise paths the field will follow, rapid change may continue to be inevitable. Within genetics, the practice of dysmorphology, as defined by pioneering geneticist David W. Smith in the 1960s as "the study of, or general subject of abnormal development of tissue form" has also been affected by technological advances as well as more general trends in biomedicine. To address possibilities, potential, and perils regarding the future of dysmorphology, a group of clinical geneticists, representing different career stages, areas of focus, and geographic regions, have contributed to this piece by providing insights about how the practice of dysmorphology will develop over the next several decades.