Placental somatic mutation in human stillbirth and live birth: A pilot case-control study of paired placental, fetal, and maternal whole genomes.

INTRODUCTION: A high frequency of single nucleotide somatic mutations in the placenta has been recently described, but its relationship to placental dysfunction is unknown. METHODS: We performed a pilot case-control study using paired fetal, maternal, and placental samples collected from healthy live birth controls (n = 10), live births with fetal growth restriction (FGR) due to placental insufficiency (n = 7), and stillbirths with FGR and placental insufficiency (n = 11). We quantified single nucleotide and structural somatic variants using bulk whole genome sequencing (30-60X coverage) in four biopsies from each placenta. We also assessed their association with clinical and histological evidence of placental dysfunction. RESULTS: Seventeen pregnancies had sufficiently high-quality placental, fetal, and maternal DNA for analysis. Each placenta had a median of 473 variants (range 111-870), with 95 % arising in just one biopsy within each placenta. In controls, live births with FGR, and stillbirths, the median variant counts per placenta were 514 (IQR 381-779), 582 (450-735), and 338 (245-441), respectively. After adjusting for depth of sequencing coverage and gestational age at birth, the somatic mutation burden was similar between groups (FGR live births vs. controls, adjusted diff. 59, 95 % CI -218 to +336; stillbirths vs controls, adjusted diff. -34, -351 to +419), and with no association with placental dysfunction (p = 0.7). DISCUSSION: We confirmed the high prevalence of somatic mutation in the human placenta and conclude that the placenta is highly clonal. We were not able to identify any relationship between somatic mutation burden and clinical or histologic placental insufficiency.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Precision subclassification of type 2 diabetes: a systematic review.

BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

In people with type 2 diabetes there may be differences in the way people present, including for example, their symptoms, body weight or how much insulin they make. We looked at recent publications describing research in this area to see whether it is possible to separate people with type 2 diabetes into different subgroups and, if so, whether these groupings were useful for patients. We found that it is possible to group people with type 2 diabetes into different subgroups and being in one subgroup can be more strongly linked to the likelihood of developing complications over others. This might mean that in the future we can treat people in different subgroups differently in ways that improves their treatment and their health but it requires further study.

Associations between diet quality and NT-proBNP in U.S. adults, NHANES 1999-2004.

Objective: N-terminal pro-brain-type natriuretic peptide (NT-proBNP) is a marker of cardiac wall stress and is a predictor of cardiovascular disease. Higher diet quality is associated with lower risk of cardiovascular disease. The association between diet quality and subclinical cardiovascular disease assessed by NT-proBNP is uncharacterized. We investigated the associations between diet quality, using Healthy Eating Index-2015 (HEI-2015), and NT-proBNP from the National Health and Nutrition Examination Survey (NHANES) 1999-2004. Methods: We included 9,782 adults from NHANES 1999-2004 without self-reported cardiovascular disease. The HEI-2015 ranges from 0 to 100, with higher scores indicating better diet quality. The HEI-2015 was categorized into sex-specific quintiles. Regression models were used to quantify associations between the overall HEI-2015 score and its 13 components with log-transformed NT-proBNP. The beta coefficients were converted to percent differences. Results: Among 9,782 participants, mean age was 45 years, 48% were men, and 72% were non-Hispanic White adults. After adjusting for sociodemographic characteristics, lifestyle factors, and medical history, those in the highest vs. lowest HEI-2015 quintile had an 8.5% (95% CI: -14.6% to -2.0%) lower NT-proBNP level. There was a dose-response association between HEI-2015 and NT-proBNP (P value for trend = 0.01). Each 1-unit higher in sodium and added sugars score indicating lower intake was associated with lower NT-proBNP by 7.7% (95% CI: -12.8% to -2.2%) and 6.5% (95% CI: -12.0% to -0.7%), respectively. Conclusion: Higher diet quality, especially lower intakes of sodium and added sugars, was associated with lower serum levels of NT-proBNP.

Systematic review of precision subclassification of type 2 diabetes.

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Inverse Associations between Measures of Adiposity and Glycated Albumin in US Adults, NHANES 1999-2004.

BACKGROUND: Glycated albumin (GA) is a short-term measure of glycemic control. Several studies have demonstrated an inverse association between body mass index (BMI) and GA, which may affect its performance as a biomarker of hyperglycemia. We investigated cross-sectional associations between GA and multiple measures of adiposity, and compared its performance as a glycemic biomarker by obesity status, in a nationally representative sample of US adults. METHODS: We measured GA in adults from the 1999-2004 National Health and Nutrition Examination Survey. Separately in adults with and without diabetes, we assessed associations of GA with adiposity measures (BMI, waist circumference, trunk fat, total body fat, and fat mass index) in sex-stratified multivariable regression models. We compared sensitivity and specificity of GA to identify elevated hemoglobin A1c (HbA1c), by obesity status. RESULTS: In covariate-adjusted regression models, all adiposity measures were inversely associated with GA in adults without diabetes (ß=-0.48 to -0.22%-point GA per 1 SD adiposity measure; n = 9750) and with diabetes (ß=-1.73 to -0.92%-point GA per SD). Comparing adults with vs without obesity, GA exhibited lower sensitivity (43% vs 54%) with equivalent specificity (99%) to detect undiagnosed diabetes (HbA1c ≥ 6.5%). Among adults with diagnosed diabetes (n = 1085), GA performed well to identify above-target glycemia (HbA1c ≥ 7.0%), with high specificity (>80%) overall but lower sensitivity in those with vs without obesity (81% vs 93%). CONCLUSIONS: Inverse associations between GA and adiposity were present in people with and without diabetes. GA is highly specific but may not be sufficiently sensitive for diabetes screening in adults with obesity.

Rare and low-frequency coding genetic variants contribute to pediatric-onset multiple sclerosis.

BACKGROUND: Rare genetic variants are emerging as important contributors to the heritability of multiple sclerosis (MS). Whether rare variants also contribute to pediatric-onset multiple sclerosis (POMS) is unknown. OBJECTIVE: To test whether genes harboring rare variants associated with adult-onset MS risk (PRF1, PRKRA, NLRP8, and HDAC7) and 52 major histocompatibility complex (MHC) genes are associated with POMS. METHODS: We analyzed DNA samples from 330 POMS cases and 306 controls from the US Network of Pediatric MS Centers and Kaiser Permanente Northern California for which Illumina ExomeChip genotypes were available. Using the gene-based method "SKAT-O," we tested the association between candidate genes and POMS risk. RESULTS: After correction for multiple comparisons, one adult-onset MS gene (PRF1, p = 2.70 × 10-3) and two MHC genes (BRD2, p = 5.89 × 10-5 and AGER, p = 7.96 × 10-5) were significantly associated with POMS. Results suggest these are independent of HLA-DRB1*1501. CONCLUSION: Findings support a role for rare coding variants in POMS susceptibility. In particular, rare minor alleles within PRF1 were more common among individuals with POMS compared to controls while the opposite was true for rare variants within significant MHC genes, BRD2 and AGER. These genes would not have been identified by common variant studies, emphasizing the merits of investigating rare genetic variation in complex diseases.

Whole-genome sequencing analysis in families with recurrent pregnancy loss: A pilot study.

One to two percent of couples suffer recurrent pregnancy loss and over 50% of the cases are unexplained. Whole genome sequencing (WGS) analysis has the potential to identify previously unrecognized causes of pregnancy loss, but few studies have been performed, and none have included DNA from families including parents, losses, and live births. We conducted a pilot WGS study in three families with unexplained recurrent pregnancy loss, including parents, healthy live births, and losses, which included an embryonic loss (<10 weeks' gestation), fetal deaths (10-20 weeks' gestation) and stillbirths (≥ 20 weeks' gestation). We used the Illumina platform for WGS and state-of-the-art protocols to identify single nucleotide variants (SNVs) following various modes of inheritance. We identified 87 SNVs involving 75 genes in embryonic loss (n = 1), 370 SNVs involving 228 genes in fetal death (n = 3), and 122 SNVs involving 122 genes in stillbirth (n = 2). Of these, 22 de novo, 6 inherited autosomal dominant and an X-linked recessive SNVs were pathogenic (probability of being loss-of-function intolerant >0.9), impacting known genes (e.g., DICER1, FBN2, FLT4, HERC1, and TAOK1) involved in embryonic/fetal development and congenital abnormalities. Further, we identified inherited missense compound heterozygous SNVs impacting genes (e.g., VWA5B2) in two fetal death samples. The variants were not identified as compound heterozygous SNVs in live births and population controls, providing evidence for haplosufficient genes relevant to pregnancy loss. In this pilot study, we provide evidence for de novo and inherited SNVs relevant to pregnancy loss. Our findings provide justification for conducting WGS using larger numbers of families and warrant validation by targeted sequencing to ascertain causal variants. Elucidating genes causing pregnancy loss may facilitate the development of risk stratification strategies and novel therapeutics.

Performance of glycated albumin as a biomarker of hyperglycemia in pregnancy: Results from the National Health and Nutrition Examination Survey 1999-2004.

AIM: We sought to evaluate the performance of glycated albumin (GA) as a measure of hyperglycemia in pregnant women. METHODS: We used data from 555 pregnant women aged 20-40 years who participated in NHANES 1999-2004 and did not report a pre-pregnancy diagnosis of diabetes. We used Pearson's correlations and evaluated the area under the curve (AUC) for GA to detect elevated concentrations of random glucose, HbA1c, or fasting glucose (subset). We compared results to 1607 nonpregnant women aged 20-40 without diabetes. RESULTS: In pregnant women, 1.9 % had HbA1c ≥ 39 mmol/mol (≥5.7 %), 9.1 % had random glucose ≥ 5.3 mmol/L (≥95 mg/dL), and 10.7 % had fasting glucose ≥ 5.3 mmol/L. In pregnancy, GA was poorly correlated with HbA1c (r = 0.08) and random glucose (r = 0.17). BMI was positively associated with HbA1c (r = 0.33) and random glucose (r = 0.25) but was inversely associated with GA (r = -0.27). GA had poor discrimination for detecting hyperglycemia in pregnant women, defined as HbA1c ≥ 39 mmol/mol (AUC = 0.634) or random glucose ≥ 5.3 mmol/L (AUC = 0.628). Similar patterns were observed among nonpregnant women. CONCLUSIONS: GA is not a sensitive test to screen for hyperglycemia in pregnancy. GA was inversely associated with adiposity in pregnant women without diabetes. Pregnancy-related weight gain may complicate interpretation of repeated GA measurements.

Obesity and Chronic Kidney Disease in US Adults With Type 1 and Type 2 Diabetes Mellitus.

OBJECTIVE: Obesity is a global public health challenge and strongly associated with type 2 diabetes (T2D), but its burden and effects are not well understood in people with type 1 diabetes (T1D). Particularly, the link between obesity and chronic kidney disease (CKD) in T1D is poorly characterized. RESEARCH DESIGN AND METHODS: We included all T1D and, for comparison, T2D in the Geisinger Health System from 2004 to 2018. We evaluated trends in obesity (body mass index ≥ 30 kg/m2), low estimated glomerular filtration rate (eGFR) (≤60 mL/min/1.73m2), and albuminuria (urine albumin-to-creatinine ratio ≥ 30 mg/g). We used multivariable logistic regression to evaluate the independent association of obesity with CKD in 2018. RESULTS: People with T1D were younger than T2D (median age 39 vs 62 years). Obesity increased in T1D over time (32.6% in 2004 to 36.8% in 2018), while obesity in T2D was stable at ~60%. The crude prevalence of low eGFR was higher in T2D than in T1D in all years (eg, 30.6% vs 16.1% in 2018), but after adjusting for age differences, prevalence was higher in T1D than T2D in all years (eg, 16.2% vs 9.3% in 2018). Obesity was associated with increased odds of low eGFR in T1D [adjusted odds ratio (AOR) = 1.52, 95% CI 1.12-2.08] and T2D (AOR = 1.29, 95% CI 1.23-1.35). CONCLUSIONS: Obesity is increasing in people with T1D and is associated with increased risk of CKD. After accounting for age, the burden of CKD in T1D exceeded the burden in T2D, suggesting the need for increased vigilance and assessment of kidney-protective medications in T1D.

The performance of glycated albumin as a biomarker of hyperglycemia and cardiometabolic risk in children and adolescents in the United States.

OBJECTIVE: Diabetes and prediabetes are growing concerns among US youth. Fasting glucose (FG) and HbA1c are standard diabetes screening tests, but HbA1c may be unreliable in some settings and fasting is burdensome in children. Glycated albumin (GA) is a non-fasting test that was recently cleared for clinical use in the United States, but studies in youth without diabetes are limited. RESEARCH DESIGN AND METHODS: We conducted a cross-sectional analysis in 6826 youth without diabetes aged 8-19 years in the 1999-2004 National Health and Nutrition Examination Survey. We evaluated the associations of GA with HbA1c, FG, and cardiometabolic risk factors. RESULTS: GA was poorly correlated with HbA1c (ρ = 0.074) and FG (ρ = -0.047) and was negatively associated with body mass index (BMI) and cardiometabolic risk factors. Compared to youth in the highest tertile of GA (≥13.5%), those in the lowest GA tertile (<12.4%) had a higher prevalence of obesity (29.9% vs. 7.6%), low high-density lipoprotein cholesterol (29.7% vs. 16.5%), and hypertensive blood pressure (4.0% vs. 2.7%). These inverse associations persisted after adjustment for age, sex, race/ethnicity, serum albumin, and C-reactive protein. CONCLUSIONS: GA was poorly correlated with traditional markers of hyperglycemia in youth without diabetes. Counterintuitively, there was a negative association between GA and BMI. Among youth without diabetes, GA does not identify youth at high cardiometabolic risk, and it does not appear to be an appropriate biomarker for screening of hyperglycemia.

National Outcomes of Elective Hybrid Arch Debranching with Endograft Exclusion versus Total Arch Replacement Procedures: Analysis of the Society of Thoracic Surgeons Adult Cardiac Surgery Database.

OBJECTIVE: Hybrid arch procedures (arch vessel debranching with thoracic endovascular aneurysm repair [TEVAR] coverage of arch pathology) have been presented as an alternative to total arch replacement (TAR). But multicenter-based analyses of these two procedures are needed to benchmark the field and establish areas of improvement. METHODS: The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database from July 2014 to December 2015 was queried for elective TAR and hybrid arch procedures. Demographics and operative characteristics were compared and stepwise variable selection was used to create a risk-set used for adjustment of all multivariable models. RESULTS: A total of 1,011 patients met inclusion criteria, 884 underwent TAR, and 127 had hybrid arch procedures. TAR patients were younger (mean age: 62.7 ± 13.3 vs. 66.7 ± 11.9 years; p = 0.001) and had less peripheral vascular disease (34.0 vs. 49.6%; p < 0.001) and preoperative dialysis (1.7 vs. 4.7%; p = 0.026), but similar history of stroke (p = 0.91)/cerebrovascular disease (p = 0.52). TAR patients had more concomitant procedures (60 vs. 34.6%; p < 0.0001). TAR patients had lower mortality (6.7 vs. 12.6%; p = 0.02), stroke (6.9 vs. 15%; p = 0.002), paralysis (1.8 vs. 7.1%; p = 0.002), renal failure (4.6 vs. 8.7%; p = 0.045), and STS morbidity (34.2 vs. 42.5%; p = 0.067). Composite mortality, stroke, and paralysis were significantly lower with TAR (11.5 vs. 25.2%; p = 0.0001). After risk adjustment, analysis showed hybrid arch procedures imparted an increased odds of mortality (odds ratio [OR] = 1.91, p = 0.046), stroke (OR = 2.3, p = 0.005), and composite endpoint of stroke or mortality (OR = 2.31, p = 0.0002). CONCLUSION: TAR remains the gold standard for elective aortic arch pathologies. Despite risk adjustment, hybrid arch procedures were associated with increased risk of mortality and stroke, advocating for careful adoption of these strategies.

Effective variant filtering and expected candidate variant yield in studies of rare human disease.

In studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

CaBagE: A Cas9-based Background Elimination strategy for targeted, long-read DNA sequencing.

A substantial fraction of the human genome is difficult to interrogate with short-read DNA sequencing technologies due to paralogy, complex haplotype structures, or tandem repeats. Long-read sequencing technologies, such as Oxford Nanopore's MinION, enable direct measurement of complex loci without introducing many of the biases inherent to short-read methods, though they suffer from relatively lower throughput. This limitation has motivated recent efforts to develop amplification-free strategies to target and enrich loci of interest for subsequent sequencing with long reads. Here, we present CaBagE, a method for target enrichment that is efficient and useful for sequencing large, structurally complex targets. The CaBagE method leverages the stable binding of Cas9 to its DNA target to protect desired fragments from digestion with exonuclease. Enriched DNA fragments are then sequenced with Oxford Nanopore's MinION long-read sequencing technology. Enrichment with CaBagE resulted in a median of 116X coverage (range 39-416) of target loci when tested on five genomic targets ranging from 4-20kb in length using healthy donor DNA. Four cancer gene targets were enriched in a single reaction and multiplexed on a single MinION flow cell. We further demonstrate the utility of CaBagE in two ALS patients with C9orf72 short tandem repeat expansions to produce genotype estimates commensurate with genotypes derived from repeat-primed PCR for each individual. With CaBagE there is a physical enrichment of on-target DNA in a given sample prior to sequencing. This feature allows adaptability across sequencing platforms and potential use as an enrichment strategy for applications beyond sequencing. CaBagE is a rapid enrichment method that can illuminate regions of the 'hidden genome' underlying human disease.

Screening and Diagnosis of Prediabetes and Diabetes in US Children and Adolescents.

BACKGROUND: The optimal approach to screening and diagnosis of prediabetes and diabetes in youth is uncertain. METHODS: We conducted a cross-sectional analysis of 14 119 youth aged 10 to 19 years in the 1999-2016 NHANES. First, we examined the performance of American Diabetes Association risk-based screening criteria. Second, we evaluated the performance of current clinical definitions of prediabetes and diabetes based on hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), either HbA1c or FPG, or both HbA1c and FPG (confirmatory definition) to identify youth at high cardiometabolic risk. RESULTS: Overall, 25.5% of US youth (10.6 million in 2016) were eligible for screening. Sensitivity and specificity of the screening criteria for detecting any hyperglycemia were low for both HbA1c ≥5.7% (sensitivity = 55.5%, specificity = 76.3%) and FPG ≥100 mg/dL (sensitivity = 35.8%, specificity = 77.1%). Confirmed undiagnosed diabetes (HbA1c ≥6.5% and FPG ≥126 mg/dL) was rare, <0.5% of youth. Most (>85%) cases of diabetes were diagnosed. Associations with cardiometabolic risk were consistently stronger and more specific for HbA1c-defined hyperglycemia (specificity = 98.6%; sensitivity = 4.0%) than FPG-defined hyperglycemia (specificity = 90.1%; sensitivity = 19.4%). CONCLUSIONS: One-quarter of US youth are eligible for screening for diabetes and prediabetes; however, few will test positive, especially for diabetes. Most cases of diabetes in US youth are diagnosed. Regardless of screening eligibility, we found that HbA1c is a specific and useful nonfasting test to identify high-risk youth who could benefit from lifestyle interventions to prevent diabetes and cardiovascular risk in adulthood.