A test of automated use of electronic health records to aid in diagnosis of genetic disease.

PURPOSE: Automated use of electronic health records may aid in decreasing the diagnostic delay for rare diseases. The phenotype risk score (PheRS) is a weighted aggregate of syndromically related phenotypes that measures the similarity between an individual's conditions and features of a disease. For some diseases, there are individuals without a diagnosis of that disease who have scores similar to diagnosed patients. These individuals may have that disease but not yet be diagnosed. METHODS: We calculated the PheRS for cystic fibrosis (CF) for 965,626 subjects in the Vanderbilt University Medical Center electronic health record. RESULTS: Of the 400 subjects with the highest PheRS for CF, 248 (62%) had been diagnosed with CF. Twenty-six of the remaining participants, those who were alive and had DNA available in the linked DNA biobank, underwent clinical review and sequencing analysis of CFTR and SERPINA1. This uncovered a potential diagnosis for 2 subjects, 1 with CF and 1 with alpha-1-antitrypsin deficiency. An additional 7 subjects had pathogenic or likely pathogenic variants, 2 in CFTR and 5 in SERPINA1. CONCLUSION: These findings may be clinically actionable for the providers caring for these patients. Importantly, this study highlights feasibility and challenges for future implications of this approach.

Exploring US internal medicine resident career preferences: a Q-methodology study.

Career selection in medicine is a complex and underexplored process. Most medical career studies performed in the U.S. focused on the effect of demographic variables and medical education debt on career choice. Considering ongoing U.S. physician workforce shortages and the trilateral adaptive model of career decision making, a robust assessment of professional attitudes and work-life preferences is necessary. The objective of this study was to explore and define the dominant viewpoints related to career choice selection in a cohort of U.S. IM residents. We administered an electronic Q-sort in which 218 IM residents sorted 50 statements reflecting the spectrum of opinions that influence postgraduate career choice decisions. Participants provided comments that explained the reasoning behind their individual responses. In the final year of residency training, we ascertained participating residents' chosen career. Factor analysis grouped similar sorts and revealed four distinct viewpoints. We characterized the viewpoints as "Fellowship-Bound-Academic," "Altruistic-Longitudinal-Generalist," "Inpatient-Burnout-Aware," and "Lifestyle-Focused-Consultant." There is concordance between residents who loaded significantly onto a viewpoint and their ultimate career choice. Four dominant career choice viewpoints were found among contemporary U.S. IM residents. These viewpoints reflect the intersection of competing priorities, personal interests, professional identity, socio-economic factors, and work/life satisfaction. Better appreciation of determinants of IM residents' career choices may help address workforce shortages and enhance professional satisfaction.

Diagnosis and discovery: Insights from the NIH Undiagnosed Diseases Program.

Living with an undiagnosed medical condition places a tremendous burden on patients, their families, and their healthcare providers. The Undiagnosed Diseases Program (UDP) was established at the National Institutes of Health (NIH) in 2008 with the primary goals of providing a diagnosis for patients with mysterious conditions and advancing medical knowledge about rare and common diseases. The program reviews applications from referring clinicians for cases that are considered undiagnosed despite a thorough evaluation. Those that are accepted receive clinical evaluations involving deep phenotyping and genetic testing that includes exome and genomic sequencing. Selected candidate gene variants are evaluated by collaborators using functional assays. Since its inception, the UDP has received more than 4500 applications and has completed evaluations on nearly 1300 individuals. Here we present six cases that exemplify the discovery of novel disease mechanisms, the importance of deep phenotyping for rare diseases, and how genetic diagnoses have led to appropriate treatment. The creation of the Undiagnosed Diseases Network (UDN) in 2014 has substantially increased the number of patients evaluated and allowed for greater opportunities for data sharing. Expansion to the Undiagnosed Diseases Network International (UDNI) has the possibility to extend this reach even farther. Together, networks of undiagnosed diseases programs are powerful tools to advance our knowledge of pathophysiology, accelerate accurate diagnoses, and improve patient care for patients with rare conditions.

Phenotypic heterogeneity of ZMPSTE24 deficiency.

A 4-year-old girl was referred to the Undiagnosed Diseases Network with a history of short stature, thin and translucent skin, macrocephaly, small hands, and camptodactyly. She had been diagnosed with possible Hallerman-Streiff syndrome. Her evaluation showed that she was mosaic for uniparental isodisomy of chromosome 1, which harbored a pathogenic c.1077dupT variant in ZMPSTE24 which predicts p.(Leu362fsX18). ZMPSTE24 is a zinc metalloproteinase that is involved in processing farnesylated proteins and pathogenic ZMPSTE24 variants cause accumulation of abnormal farnesylated forms of prelamin A. This, in turn, causes a spectrum of disease severity which is based on enzyme activity. The current patient has an intermediate form, which is a genocopy of severe Progeria.

Comparison of phenomic profiles in the All of Us Research Program against the US general population and the UK Biobank.

IMPORTANCE: Knowledge gained from cohort studies has dramatically advanced both public and precision health. The All of Us Research Program seeks to enroll 1 million diverse participants who share multiple sources of data, providing unique opportunities for research. It is important to understand the phenomic profiles of its participants to conduct research in this cohort. OBJECTIVES: More than 280 000 participants have shared their electronic health records (EHRs) in the All of Us Research Program. We aim to understand the phenomic profiles of this cohort through comparisons with those in the US general population and a well-established nation-wide cohort, UK Biobank, and to test whether association results of selected commonly studied diseases in the All of Us cohort were comparable to those in UK Biobank. MATERIALS AND METHODS: We included participants with EHRs in All of Us and participants with health records from UK Biobank. The estimates of prevalence of diseases in the US general population were obtained from the Global Burden of Diseases (GBD) study. We conducted phenome-wide association studies (PheWAS) of 9 commonly studied diseases in both cohorts. RESULTS: This study included 287 012 participants from the All of Us EHR cohort and 502 477 participants from the UK Biobank. A total of 314 diseases curated by the GBD were evaluated in All of Us, 80.9% (N = 254) of which were more common in All of Us than in the US general population [prevalence ratio (PR) >1.1, P < 2 × 10-5]. Among 2515 diseases and phenotypes evaluated in both All of Us and UK Biobank, 85.6% (N = 2152) were more common in All of Us (PR >1.1, P < 2 × 10-5). The Pearson correlation coefficients of effect sizes from PheWAS between All of Us and UK Biobank were 0.61, 0.50, 0.60, 0.57, 0.40, 0.53, 0.46, 0.47, and 0.24 for ischemic heart diseases, lung cancer, chronic obstructive pulmonary disease, dementia, colorectal cancer, lower back pain, multiple sclerosis, lupus, and cystic fibrosis, respectively. DISCUSSION: Despite the differences in prevalence of diseases in All of Us compared to the US general population or the UK Biobank, our study supports that All of Us can facilitate rapid investigation of a broad range of diseases. CONCLUSION: Most diseases were more common in All of Us than in the general US population or the UK Biobank. Results of disease-disease association tests from All of Us are comparable to those estimated in another well-studied national cohort.

Racial and Ethnic Disparities in Antihypertensive Medication Prescribing Patterns and Effectiveness.

Variability in drug effectiveness and provider prescribing patterns have been reported in different racial and ethnic populations. We sought to evaluate antihypertensive drug effectiveness and prescribing patterns among self-identified Hispanic/Latino (Hispanic), Non-Hispanic Black (Black), and Non-Hispanic White (White) populations that enrolled in the NIH All of Us Research Program, a US longitudinal cohort. We employed a self-controlled case study method using electronic health record and survey data from 17,718 White, Hispanic, and Black participants who were diagnosed with essential hypertension and prescribed at least one of 19 commonly used antihypertensive medications. Effectiveness was determined by calculating the reduction in systolic blood pressure measurements after 28 or more days of drug exposure. Starting systolic blood pressure and effectiveness for each medication were compared for self-reported Black, Hispanic, and White participants using adjusted linear regressions. Black and Hispanic participants were started on antihypertensive medications at significantly higher SBP than White participants in 13 and 7 out of 19 medications, respectively. More Black participants were prescribed multiple antihypertensive medications (58.46%) than White (52.35%) or Hispanic (49.9%) participants. First-line HTN medications differed by race and ethnicity. Following the 2017 American College of Cardiology and the American Heart Association High Blood Pressure Guideline release, around 64% of Black participants were prescribed a recommended first-line antihypertensive drug compared with 76% of White and 82% of Hispanic participants. Effect sizes suggested that most antihypertensive drugs were less effective in Hispanic and Black, compared with White, participants, and statistical significance was reached in 6 out of 19 drugs. These results indicate that Black and Hispanic populations may benefit from earlier intervention and screening and highlight the potential benefits of personalizing first-line medications.

Genomic Diagnoses for Ectopic Intracerebral Calcifications.

Background and Objectives: Ectopic intracerebral calcifications (EICs) in the basal ganglia, thalamus, cerebellum, or white matter are seen in a variety of disease states or may be found incidentally on brain imaging. The clinical significance and proportion of cases attributable to an underlying genetic cause is unknown. Methods: This retrospective cohort study details the clinical, imaging, and genomic findings of 44 patients with EICs who had no established diagnosis despite extensive medical workup. Results: In total, 15 of 44 patients received a diagnosis through genomic testing explaining their calcifications, and 2 more received a diagnosis that has not been previously associated with EICs. Six of the 15 were found to have one of the 4 genes (PDGFB, PDGFRB, SLC20A2, and XPR1) conventionally associated with the phenotypic term "idiopathic basal ganglia calcifications." Discussion: These findings support the use of genomic testing for symptomatic patients with EICs.

MYH2-associated myopathy caused by a novel splice-site variant.

MYH2 encodes MyHCIIa, a myosin heavy chain found in fast type 2A fibers. Pathogenic variants in this gene have previously been implicated in dominant and recessive forms of myopathy. Three individuals reported here are part of a family in which four generations of individuals are affected by a slowly progressive, predominantly proximal myopathy in an autosomal dominant inheritance pattern. Affected individuals in this family lacked classic features of an MYH2-associated myopathy such as congenital contractures and ophthalmoplegia. A novel variant, MYH2 c.5673+1G>C, was detected in the proband and subsequently found to segregate with disease in five additional family members. Further studies demonstrated that this variant affects splicing, resulting in novel transcripts. These data and muscle biopsy findings in the proband, indicate that this family's MYH2 variant is causative of their myopathy, adding to our understanding of the clinical and molecular characteristics of the disease.

Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants.

Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a "personalized structural biology" (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.

Whole genome sequencing reveals novel IGHMBP2 variant leading to unique cryptic splice-site and Charcot-Marie-Tooth phenotype with early onset symptoms.

BACKGROUND: Rare variants (RV) in immunoglobulin mu-binding protein 2 (IGHMBP2) [OMIM 600502] can cause an autosomal recessive type of Charcot-Marie-Tooth (CMT) disease [OMIM 616155], an inherited peripheral neuropathy. Over 40 different genes are associated with CMT, with different possible inheritance patterns. METHODS AND RESULTS: An 11-year-old female with motor delays was found to have distal atrophy, weakness, and areflexia without bulbar or sensory findings. Her clinical evaluation was unrevealing. Whole exome sequencing (WES) revealed a maternally inherited IGHMBP2 RV (c.1730T>C) predicted to be pathogenic, but no variant on the other allele was identified. Deletion and duplication analysis was negative. She was referred to the Undiagnosed Disease Network (UDN) for further evaluation. Whole genome sequencing (WGS) confirmed the previously identified IGHMBP2 RV and identified a paternally inherited non-coding IGHMBP2 RV. This was predicted to activate a cryptic splice site perturbing IGHMBP2 splicing. Reverse transcriptase polymerase chain reaction (RT-PCR) analysis was consistent with activation of the cryptic splice site. The abnormal transcript was shown to undergo nonsense-mediated decay (NMD), resulting in halpoinsufficiency. CONCLUSION: This case demonstrates the deficiencies of WES and traditional molecular analyses and highlights the advantages of utilization of WGS and functional studies.