A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale

Unpaired text and audio injection have emerged as dominant methods for improving ASR performance in the absence of a large labeled corpus. However, little guidance exists on deploying these methods to improve production ASR systems that are trained on very large supervised corpora and with realistic requirements like a constrained model size and CPU budget, streaming capability, and a rich lattice for rescoring and for downstream NLU tasks. In this work, we compare three state-of-the-art semi-supervised methods encompassing both unpaired text and audio as well as several of their combinations in a controlled setting using joint training. We find that in our setting these methods offer many improvements beyond raw WER, including substantial gains in tail-word WER, decoder computation during inference, and lattice density

The development, usability, and reliability of the Electronic Patient Visit Assessment (ePVA) for head and neck cancer

Background: Annually, over 65,000 persons are diagnosed with head and neck cancer in the United States. During treatment, up to 50% of patients become severely symptomatic with pain, fatigue, mouth sores, and inability to eat. Long term complications are lymphedema, fibrosis, dysphagia, and musculoskeletal impairment. Patients’ ability to perform daily activities and to interact socially may be impaired, resulting in poor quality of life. A pragmatic, clinically useful assessment is needed to ensure early detection and intervention for patients to report symptoms and functional limitations over time. We developed the Electronic Patient Visit Assessment (ePVA) that enables patients to report 42 symptoms related to head and neck cancer and 17 limitations of functional status. This manuscript reports (I) the development of the ePVA, (II) the content validity of the ePVA, and (III) the usability and reliability of the ePVA. Methods: Usability was evaluated using the “Think Aloud” technique to guide the iterative process to refine the ePVA based on participants’ evaluations. After signing the informed consent, 30 participants with head and neck cancer completed the ePVA using digital tablet devices while thinking aloud about ease of use. All patient conversations were recorded and professionally transcribed. Reliability of the ePVA symptom and functional limitation measures was estimated using the Kuder-Richardson test. Convergent validity of the ePVA was evaluated using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 global QoL/health scale. Transcribed qualitative data were analyzed using directed content analysis approach. Quantitative analyses consisted of descriptive statistics and correlation analyses. Results: Among participants, 90% strongly agreed or agreed that the ePVA system was easy to use and 80% were very satisfied. Only minor usability problems were reported due to formatting and software “bugs”. Reporting of usability problems decreased in frequency over the study period and no usability problems were reported by the last 3 participants who completed the ePVA. Based on participants’ suggestions during the iterative process, refinement of the ePVA included increased touch sensitivity of the touch screen technology and customized error messages to improve ease of use. The ePVA also recorded patient reported symptoms (mouth symptoms: 93%, fibrosis: 60%, fatigue: 60%). The ePVA demonstrated acceptable reliability (alpha =0.82–0.85) and convergent validity (ePVA total number of reported symptoms and function limitations was negatively correlated with EORTC QLQ-C30 global QOL/health scale: r=−0.55038, P<0.01). Conclusions: The ePVA was rigorously developed, accepted by patients with satisfaction, and demonstrated acceptable reliability and convergent validity. Future research will use data generated by the ePVA to determine the impact of symptom trajectories on functional status, treatment interruptions and terminations, and health resource use in head and neck cancer

Testing cross‐phenotype effects of rare variants in longitudinal studies of complex traits

Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next‐generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross‐phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare‐variant approaches exist for testing cross‐phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross‐phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome‐wide scale due to the use of a closed‐form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/1/gepi22121_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/2/gepi22121.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/3/gepi22121-sup-0001-SuppMat.pd

Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and Its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization

OBJECTIVE: In this study, we aimed to establish the causal effects of lowering sclerostin, target of the antiosteoporosis drug romosozumab, on atherosclerosis and its risk factors. METHODS: A genome-wide association study meta-analysis was performed of circulating sclerostin levels in 33,961 European individuals. Mendelian randomization (MR) was used to predict the causal effects of sclerostin lowering on 15 atherosclerosis-related diseases and risk factors. RESULTS: We found that 18 conditionally independent variants were associated with circulating sclerostin. Of these, 1 cis signal in SOST and 3 trans signals in B4GALNT3, RIN3, and SERPINA1 regions showed directionally opposite signals for sclerostin levels and estimated bone mineral density. Variants with these 4 regions were selected as genetic instruments. MR using 5 correlated cis-SNPs suggested that lower sclerostin increased the risk of type 2 diabetes mellitus (DM) (odds ratio [OR] 1.32 [95% confidence interval (95% CI) 1.03-1.69]) and myocardial infarction (MI) (OR 1.35 [95% CI 1.01-1.79]); sclerostin lowering was also suggested to increase the extent of coronary artery calcification (CAC) (β = 0.24 [95% CI 0.02-0.45]). MR using both cis and trans instruments suggested that lower sclerostin increased hypertension risk (OR 1.09 [95% CI 1.04-1.15]), but otherwise had attenuated effects. CONCLUSION: This study provides genetic evidence to suggest that lower levels of sclerostin may increase the risk of hypertension, type 2 DM, MI, and the extent of CAC. Taken together, these findings underscore the requirement for strategies to mitigate potential adverse effects of romosozumab treatment on atherosclerosis and its related risk factors

Insulin Resistance Exacerbates Genetic Predisposition to Nonalcoholic Fatty Liver Disease in Individuals Without Diabetes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/1/hep41353.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/2/hep41353_am.pd

Mosaic Chromosomal alterations in Blood across ancestries Using Whole-Genome Sequencing

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D

Type 2 Diabetes Modifies the association of Cad Genomic Risk Variants With Subclinical atherosclerosis

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loc

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin