Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data.

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Variant Classification for Pompe disease; ACMG/AMP specifications from the ClinGen Lysosomal Diseases Variant Curation Expert Panel.

Accurate determination of the clinical significance of genetic variants is critical to the integration of genomics in medicine. To facilitate this process, the NIH-funded Clinical Genome Resource (ClinGen) has assembled Variant Curation Expert Panels (VCEPs), groups of experts and biocurators which provide gene- and disease- specifications to the American College of Medical Genetics & Genomics and Association for Molecular Pathology's (ACMG/AMP) variation classification guidelines. With the goal of classifying the clinical significance of GAA variants in Pompe disease (Glycogen storage disease, type II), the ClinGen Lysosomal Diseases (LD) VCEP has specified the ACMG/AMP criteria for GAA. Variant classification can play an important role in confirming the diagnosis of Pompe disease as well as in the identification of carriers. Furthermore, since the inclusion of Pompe disease on the Recommended Uniform Screening Panel (RUSP) for newborns in the USA in 2015, the addition of molecular genetic testing has become an important component in the interpretation of newborn screening results, particularly for asymptomatic individuals. To date, the LD VCEP has submitted classifications and supporting data on 243 GAA variants to public databases, specifically ClinVar and the ClinGen Evidence Repository. Here, we describe the ACMG/AMP criteria specification process for GAA, an update of the GAA-specific variant classification guidelines, and comparison of the ClinGen LD VCEP's GAA variant classifications with variant classifications submitted to ClinVar. The LD VCEP has added to the publicly available knowledge on the pathogenicity of variants in GAA by increasing the number of expert-curated GAA variants present in ClinVar, and aids in resolving conflicting classifications and variants of uncertain clinical significance.

Frequency of use of the religious exemption in New Jersey cases of determination of brain death.

BACKGROUND: The 1981 Uniform Determination of Death Act (UDDA) established the validity of both cardio-respiratory and neurological criteria of death. However, many religious traditions including most forms of Haredi Judaism (ultra-orthodox) and many varieties of Buddhism strongly disagree with death by neurological criteria (DNC). Only one state in the U.S., New Jersey, allows for both religious exemptions to DNC and provides continuation of health insurance coverage when an exception is invoked in its 1991 Declaration of Death Act (NJDDA). There is yet no quantitative or qualitative data on the frequencies of religious exemptions in New Jersey. This study gathered information about the frequency of religious exemptions and policy in New Jersey that was created out of respect for religious beliefs. METHODS: Literature and internet searches on topics related to religious objections to DNC were conducted. Fifty-three chaplains and heads of bioethics committees in New Jersey hospitals were contacted by phone or email requesting a research interview. Respondents answered a set of questions about religious exemptions to DNC at the hospital where they worked that explored the frequency of such religious exemptions in the past five years, the religious tradition indicated, and whether any request for a religious exemption had been denied. This study was approved by the Northeastern University Institutional Review Board (IRB #: 16-03-15). RESULTS: Eighteen chaplains and bioethics committee members participated in a full research interview. Of these, five reported instances of religious exemptions to DNC occurring at the hospital at which they worked for a total of approximately 30-36 known exemptions in the past five years. Families sought religious exemptions because of faith in an Orthodox Judaism tradition and nonreligious reasons. No failed attempts to obtain an exemption were reported. CONCLUSIONS: Religious exemptions to DNC in New Jersey do occur, although very infrequently. Prior to this study, there was no information on their frequency. Considering religious exemptions do occur, there is a need for national or state policies that addresses both religious objections to DNC and hospital resources. More information is needed to better understand the impact of granting religious exemptions before new policy can be established.

Understanding the Design of Fear Appeals by Applying the Extended Parallel Process Model: A Qualitative Analysis of COVID-19 Public Service Announcements.

PURPOSE: Identify how early COVID-19 public health messages incorporated in the tenets of the extended parallel process model (EPPM). SETTING: YouTube videos developed by governmental departments, medical institutions, news organizations, and non-profit organizations in the United States were aggregated. METHOD: This qualitative study conducted a keyword search to identify public service announcements (PSAs). The sample was further refined after searching PSAs that contained fear appeals. A thematic analysis was performed by using the constant comparative method. SAMPLE: A total of forty-three videos was included in the final analysis. RESULT: Two themes emerged regarding messages aimed at arousing the perceived severity of threat. These themes include emphasizing the consequences of being infected and utilizing personal narratives. Perceived susceptibility of threat was aroused by emphasizing that some groups have higher risks than others. Two themes emerged around arousing perceived response efficacy: (1) the authority of professionals; and (2) altruism and personal responsibility. One way was identified to arouse perceived self-efficacy, which is informing the protective measures. CONCLUSION: Multiple strategies were used in PSAs about COVID-19 to arouse fear during the early stages of the pandemic. The utilization of self-efficacy was oversimplified, by not providing details about the rationale for the recommended behavior.

Acute Recurrent Pancreatitis in a Child With INS-Related Monogenic Diabetes and a Heterozygous Pathogenic CFTR Mutation.

Given the close anatomical and physiological links between the exocrine and endocrine pancreas, diseases of 1 compartment often affect the other through mechanisms that remain poorly understood. Pancreatitis has been associated with both type 1 and type 2 diabetes, but its association with monogenic diabetes is unknown. Patients heterozygous for pathogenic CFTR variants are cystic fibrosis carriers and have been reported to have an increased risk of acute pancreatitis. We describe a 12-year-old patient with monogenic neonatal diabetes due to a pathogenic heterozygous paternally inherited mutation of the insulin gene (INS), c.94 G > A (p.Gly32Ser), who experienced 3 recurrent episodes of acute pancreatitis over 7 months in conjunction with poor glycemic control, despite extensive efforts to improve glycemic control in the past 4 years. Intriguingly, the maternal side of the family has an extensive history of adult-onset pancreatitis consistent with autosomal dominant inheritance and the proband is heterozygous for a maternally inherited, CFTR variant c.3909C > G (p.Asn1303Lys). Paternally inherited monogenic neonatal diabetes may have promoted earlier age-of-onset of pancreatitis in this pediatric patient compared to maternal relatives with adult-onset acute pancreatitis. Further study is needed to clarify how separate pathophysiologies associated with INS and CFTR mutations influence interactions between the endocrine and exocrine pancreas.

Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data.

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines's PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.