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

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.

A Systematic Review and Recommendations Around Frameworks for Evaluating Scientific Validity in Nutritional Genomics.

Background: There is a significant lack of consistency used to determine the scientific validity of nutrigenetic research. The aims of this study were to examine existing frameworks used for determining scientific validity in nutrition and/or genetics and to determine which framework would be most appropriate to evaluate scientific validity in nutrigenetics in the future. Methods: A systematic review (PROSPERO registration: CRD42021261948) was conducted up until July 2021 using Medline, Embase, and Web of Science, with articles screened in duplicate. Gray literature searches were also conducted (June-July 2021), and reference lists of two relevant review articles were screened. Included articles provided the complete methods for a framework that has been used to evaluate scientific validity in nutrition and/or genetics. Articles were excluded if they provided a framework for evaluating health services/systems more broadly. Citing articles of the included articles were then screened in Google Scholar to determine if the framework had been used in nutrition or genetics, or both; frameworks that had not were excluded. Summary tables were piloted in duplicate and revised accordingly prior to synthesizing all included articles. Frameworks were critically appraised for their applicability to nutrigenetic scientific validity assessment using a predetermined categorization matrix, which included key factors deemed important by an expert panel for assessing scientific validity in nutrigenetics. Results: Upon screening 3,931 articles, a total of 49 articles representing 41 total frameworks, were included in the final analysis (19 used in genetics, 9 used in nutrition, and 13 used in both). Factors deemed important for evaluating nutrigenetic evidence related to study design and quality, generalizability, directness, consistency, precision, confounding, effect size, biological plausibility, publication/funding bias, allele and nutrient dose-response, and summary levels of evidence. Frameworks varied in the components of their scientific validity assessment, with most assessing study quality. Consideration of biological plausibility was more common in frameworks used in genetics. Dose-response effects were rarely considered. Two included frameworks incorporated all but one predetermined key factor important for nutrigenetic scientific validity assessment. Discussion/Conclusions: A single existing framework was highlighted as optimal for the rigorous evaluation of scientific validity in nutritional genomics, and minor modifications are proposed to strengthen it further. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=261948, PROSPERO [CRD42021261948].

An unsupervised learning approach to identify novel signatures of health and disease from multimodal data.

BACKGROUND: Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease signatures. METHODS: We collected 1385 data features from diverse modalities, including metabolome, microbiome, genetics, and advanced imaging, from 1253 individuals and from a longitudinal validation cohort of 1083 individuals. We utilized a combination of unsupervised machine learning methods to identify multimodal biomarker signatures of health and disease risk. RESULTS: Our method identified a set of cardiometabolic biomarkers that goes beyond standard clinical biomarkers. Stratification of individuals based on the signatures of these biomarkers identified distinct subsets of individuals with similar health statuses. Subset membership was a better predictor for diabetes than established clinical biomarkers such as glucose, insulin resistance, and body mass index. The novel biomarkers in the diabetes signature included 1-stearoyl-2-dihomo-linolenoyl-GPC and 1-(1-enyl-palmitoyl)-2-oleoyl-GPC. Another metabolite, cinnamoylglycine, was identified as a potential biomarker for both gut microbiome health and lean mass percentage. We identified potential early signatures for hypertension and a poor metabolic health outcome. Additionally, we found novel associations between a uremic toxin, p-cresol sulfate, and the abundance of the microbiome genera Intestinimonas and an unclassified genus in the Erysipelotrichaceae family. CONCLUSIONS: Our methodology and results demonstrate the potential of multimodal data integration, from the identification of novel biomarker signatures to a data-driven stratification of individuals into disease subtypes and stages-an essential step towards personalized, preventative health risk assessment.

Impact of helical computed tomography on the rate of negative appendicitis.

OBJECTIVE: To assess the impact of helical computed tomography (HCT) on the rate of negative appendicitis (NA). METHODS: A before-and-after comparison study comparing data from a prospective consecutive case series to data from a retrospective chart review. The prospective series included all patients presenting to the ED during a 19-month period, during which patients with suspected appendicitis were managed in accordance with a guideline that stipulated HCT in selected cases. The retrospective group included patients taken to the operating room (OR) with a preoperative diagnosis of appendicitis over a 4-year time frame before the use of HCT. The primary outcome variable was the rate of NA. RESULTS: During the HCT era, 104 of 310 patients, 71 (68%; 95% confidence interval [CI], 59-76) men and 33 (32%; 95% CI, 24-41) women, were taken to the OR with a diagnosis of appendicitis. Fourteen (13.5%; 95% CI, 8-21) were NA. During the pre-HCT period, 445 patients, 280 (62.9%; 95% CI, 58-67) men and 165 (37.1%; 95% CI, 33-42) women were taken to the OR with the preoperative diagnosis of appendicitis, and 66 (14.8%; 95% CI, 12-19) were NA. CONCLUSION: At the study institution, the selective use of HCT did not result in a significant decline in the rate of NA.

Ventilation patterns in patients with severe traumatic brain injury following paramedic rapid sequence intubation.

INTRODUCTION: Inadvertent hyperventilation has been documented during aeromedical transports but has not been studied following paramedic rapid sequence intubation (RSI). The San Diego Paramedic RSI Trial was designed to study the impact of paramedic RSI on outcome in patients with severe head injury. This analysis explores ventilation patterns in a cohort of trial patients undergoing end-tidal CO2 (ETCO2) monitoring. METHODS: Adult patients with severe head injury (Glasgow Coma Score: 3-8) unable to be intubated without RSI were prospectively enrolled in the trial. Midazolam and succinylcholine were used for RSI; rocuronium was administered following tube confirmation. Standardized ventilation protocols were used by most paramedics; however, one agency instituted ETCO2 monitoring during the second trial year, with paramedics instructed to target ETCO2 values of 30 to 35 mmHg. The incidence and duration of inadvertent hyperventilation (ETCO2: <30 mmHg) and severe hyperventilation (ETCO2: <25 mmHg) were explored for patients undergoing ETCO2 monitoring. The initial, final, minimum, and maximum values for ETCO2 and the maximum and minimum ventilatory rate values were also calculated using descriptive statistics (95% confidence interval). The pattern of ETCO2 values over time and distribution of recorded ventilatory rate values were explored graphically. RESULTS: A total of 76 trial patients had adequate ETCO2 data for this analysis. The mean values for initial, final, maximum, and minimum ETCO2 were 40.8 (range: 37.5-44.2), 28.4 (range: 25.4-31.4), 45.1 (range: 41.4-48.8), and 23.5 mmHg (range: 21.4-25.5), respectively. The mean maximum and minimum ventilatory rate values were 36.0/minute (range: 33.5-38.5) and 12.8/minute (range: 11.9-13.7), respectively. ETCO2 values less than 30 and 25 mmHg were documented in 79% and 59% of patients, respectively, with mean durations of 485 (range: 378-592) and 390 seconds (range: 285-494). CONCLUSION: Inadvertent hyperventilation is common following paramedic RSI, despite ETCO2 monitoring and target parameters.