Background Noninvasive prenatal screening for common autosomal trisomies, sex chromosome aneuploidies and microdeletions vary by methodology and laboratory practice. The fetal portion of all cell-free DNA in the maternal circulation defines the fetal fraction (FF). The minimum specimen FF levels for reporting results vary between laboratories as well as the screening target (e.g., common trisomies vs select microdeletions). This variability can lead to confusion for both healthcare providers and patients. Methods Participants in the College of American Pathologists Non-Invasive Prenatal Testing 2021-B Exercise provided FF estimates for 3 manufactured samples. Responses to supplemental questions were also collected and analyzed. Results Overall, 72 of 77 participants responded. FF was measured by 66 participants using sequence counts (40), single nucleotide polymorphisms (15), fragment length (24), and Y chromosome sequences (24). Nearly half (48%) used multiple methods. For common trisomies, minimum FFs were none or <1% (n = 7), 1.0% to 3.9% (n = 35), 4.0% to 6.9% (n = 23), and ≥7.0% (n = 1); 4 participants did not measure FF. Challenge-specific FFs were variable with CVs of 13%, 15%, and 36%; the latter rate appears due to that sample’s fetal karyotype of 47,XYY. Comparing adjusted FF results for the 3 samples shows that 85% of participant results were within 20% of the consensus. Conclusions Using multiple methods to estimate FF was common, and cutoff levels for sample suitability varied widely. Within-laboratory FFs were less variable than between laboratories. Current FF estimates from clinical laboratories are not standardized and should be considered laboratory-specific.

ObjectiveDetermine current analytical methods and number of cell-free (cf) DNA prenatal screening tests performed for common trisomies.MethodsThe College of American Pathologists 2022-B Noninvasive Prenatal Testing exercise was distributed in December 2022 to 93 participants in 22 countries. Supplemental questions included the number of tests performed in a recent month and the proportion of samples originating outside the United States (US).ResultsEighty-three participants from three continents returned results; 74 (89%) were suitable for the analyses. Nine manufacturer/platform combinations were identified, most commonly Illumina/Nextseq (55%). The most common methodology was whole genome sequencing (76%). Annualized cfDNA tests were 2.80 million, with Asian, European and North American participants representing 10.6%, 6.5% and 82.9% of tests, respectively. When restricted to US in-country tests, the annualized rate was 2.18 million, with four of 20 participants testing 79.2%. Among 73 respondents, 63 (86%) were for-profit, eight (11%) were non-profit academic or government supported and the remaining two included hospital-based and private non-profit. Eighteen (25%) supported relevant academic training.ConclusionIn 2011, screening for common trisomies was based on serum/ultrasound markers with an estimated 2.96 million US pregnancies screened in 131 laboratories. In 2022, cfDNA-based screening was offered by 20 laboratories testing 2.18 million US pregnancies. What's already known about this topic?Serum/ultrasound based prenatal screening for common trisomies is being replaced by cell-free (cf) DNA-based screening for common trisomies.What does this study add?In 2022, an estimated 59% of all United States (US) pregnancies received cfDNA screening for common trisomies, with four of 20 reporting laboratories performing 79% of these tests.

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case–control study of 499 autistic and 209 typically developing (TYP) children, ages 18–48 months, enrolled in the Children’s Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5–11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants’ biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

Inadequate glycogen branching enzyme 1 (GBE1) activity results in different forms of glycogen storage disease type IV, including adult polyglucosan body disorder (APBD). APBD is clinically characterized by adult-onset development of progressive spasticity, neuropathy, and neurogenic bladder and is histologically characterized by the accumulation of structurally abnormal glycogen (polyglucosan bodies) in multiple cell types. How insufficient GBE1 activity causes the disease phenotype of APBD is poorly understood. We hypothesized that proteomic analysis of tissue from GBE1-deficient individuals would provide insights into GBE1-mediated pathobiology. In this discovery study, we utilized label-free LC-MS/MS to quantify the proteomes of lymphoblasts from 3 persons with APBD and 15 age- and gender-matched controls, with validation of the findings by targeted MS. There were 531 differentially expressed proteins out of 3,427 detected between APBD subjects vs. controls, including pronounced deficiency of GBE1. Bioinformatic analyses indicated multiple canonical pathways and protein-protein interaction networks to be statistically markedly enriched in APBD subjects, including: RNA processing/transport/translation, cell cycle control/replication, mTOR signaling, protein ubiquitination, unfolded protein and endoplasmic reticulum stress responses, glycolysis and cell death/apoptosis. Dysregulation of these processes, therefore, are primary or secondary factors in APBD pathobiology in this model system. Our findings further suggest that proteomic analysis of GBE1 mutant lymphoblasts can be leveraged as part of the screening for pharmaceutical agents for the treatment of APBD.

ABSTRACT Neurodevelopmental disorders (NDDs) often result from highly penetrant variation in one of many genes, including genes not yet characterized. Using the MatchMaker Exchange, we assembled a cohort of 22 individuals with rare, protein-altering variation in the X-linked transcriptional coregulator gene ZMYM3 . Most (n=19) individuals were males; 15 males had maternally-inherited alleles, three of the variants in males arose de novo , and one had unknown inheritance. Overlapping features included developmental delay, intellectual disability, behavioral abnormalities, and a specific facial gestalt in a subset of males. Variants in almost all individuals (n=21) are missense, two of which are recurrent. Three unrelated males were identified with inherited variation at R441, a site at which variation has been previously reported in NDD-affected males, and two individuals have de novo variation at R1294. All variants affect evolutionarily conserved sites, and most are predicted to damage protein structure or function. ZMYM3 is relatively intolerant to variation in the general population, is highly expressed in the brain, and encodes a component of the KDM1A-RCOR1 chromatin-modifying complex. ChIP-seq experiments on one mutant, ZMYM3 R1274W , indicate dramatically reduced genomic occupancy, supporting a hypomorphic effect. While we are unable to perform statistical evaluations to support a conclusive causative role for variation in ZMYM3 in disease, the totality of the evidence, including the presence of recurrent variation, overlapping phenotypic features, protein-modeling data, evolutionary constraint, and experimentally-confirmed functional effects, strongly supports ZMYM3 as a novel NDD gene.

Autism Spectrum Disorder (ASD or autism) is a clinically and etiologically heterogeneous condition. Stratification of autistic individuals into subpopulations with shared metabolic phenotypes can improve understanding of the underlying pathophysiology leading to more precise interventions. We performed metabolomic profiling of 499 autistic and 209 typically developing children, ages 18-48 months, enrolled in the Children’s Autism Metabolome Project (CAMP). Through application of plasma metabolomic analyses of a large population of autistic and typically developing children, individuals were stratified using metabolic phenotypes (metabotypes). Metabotypes associated with autism provide insight into the heterogeneity of this condition. Fifty-four metabolites, mainly associated with amino acid, organic acid, acylcarnitine, and purine metabolism, were quantified using liquid chromatography-tandem mass spectrometry, including important metabolites and ratios related to energy homeostasis not evaluated in earlier studies. Quantitative thresholds of the concentrations of 4 metabolites and 149 ratios of concentrations of metabolites were identified that could stratify CAMP participants into metabolic subpopulations of primarily autistic individuals. One or more metabotypes were present in 83% of the autistic participants. based on the similarity of metabotype profiles of the participants. The metabotypes were grouped into 30 clusters based on the similarity of metabotype profiles of the participants. The clusters displayed 7 broader metabolic patterns of changes in metabolites associated with glycolysis, tricarboxylic acid cycle (TCA), amino acid, purine, and acylcarnitine metabolism. Metabolic phenotypes related to cellular bioenergetics, especially mitochondrial dysmetabolism, were commonly observed in this large cohort of autistic participants. A subset of 42 metabotypes could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. As the number of metabotype clusters increased in each individual, so did the autism severity. Metabolic profiling of autistic children can support diagnosis, enhance understanding of the underlying pathophysiology and suggest targeted metabolic treatments.

Neurodevelopmental disorders (NDDs) result from highly penetrant variation in hundreds of different genes, some of which have not yet been identified. Using the MatchMaker Exchange, we assembled a cohort of 27 individuals with rare, protein-altering variation in the transcriptional coregulator ZMYM3, located on the X chromosome. Most (n = 24) individuals were males, 17 of which have a maternally inherited variant; six individuals (4 male, 2 female) harbor de novo variants. Overlapping features included developmental delay, intellectual disability, behavioral abnormalities, and a specific facial gestalt in a subset of males. Variants in almost all individuals (n = 26) are missense, including six that recurrently affect two residues. Four unrelated probands were identified with inherited variation affecting Arg441, a site at which variation has been previously seen in NDD-affected siblings, and two individuals have de novo variation resulting in p.Arg1294Cys (c.3880C>T). All variants affect evolutionarily conserved sites, and most are predicted to damage protein structure or function. ZMYM3 is relatively intolerant to variation in the general population, is widely expressed across human tissues, and encodes a component of the KDM1A-RCOR1 chromatin-modifying complex. ChIP-seq experiments on one variant, p.Arg1274Trp, indicate dramatically reduced genomic occupancy, supporting a hypomorphic effect. While we are unable to perform statistical evaluations to definitively support a causative role for variation in ZMYM3, the totality of the evidence, including 27 affected individuals, recurrent variation at two codons, overlapping phenotypic features, protein-modeling data, evolutionary constraint, and experimentally confirmed functional effects strongly support ZMYM3 as an NDD-associated gene.

Adults with intellectual or developmental disability (IDD) comprise 1-2% of the population worldwide. IDD is a significant risk factor for premature morbidity or mortality. This is likely due in part to preventable health conditions, which are modifiable with the intervention of direct care providers in areas including nutrition, promotion of an active lifestyle and effective identification of health or functional deterioration. Adults with IDD are also at increased risk for neglect or mistreatment, a finding that has been documented across multiple countries and in a variety of care settings. Contributing factors include resource availability, lack of person-centered care, management culture and care worker training. Practical and economical interventions may address the known disparities and challenges facing the large community of adults with IDD. To promote person-centered care, improve record-keeping/documentation, and aid in protecting the health and safety of this vulnerable population, we propose incorporation of a video into the evaluation of adults with IDD living outside the home.

Medical schools face a challenge when trying to include new topics, such as climate change and health (CCH), in their curricula because of competing demands from more traditional biomedical content. At the same time, an understanding of CCH topics is crucial for physicians as they have clear implications for clinical practice and health care delivery. Although some medical schools have begun to incorporate CCH into curricula, the inclusion usually lacks a comprehensive framework for content and implementation. The authors propose a model for integrating CCH into medical school curricula using a practical, multistakeholder approach designed to mitigate competition for time with existing content by weaving meaningful CCH examples into current curricular activities. After the authors identified stakeholders to include in their curricular development working group, this working group determined the goals and desired outcomes of the curriculum; aligned those outcomes with the school’s framework of educational objectives, competencies, and milestones; and strove to integrate CCH goals into as many existing curricular settings as possible. This article includes an illustration of the proposed model for one of the curricular goals (understanding the impacts of climate change on communities), with examples from the CCH curriculum integration that began in the fall of 2020 at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. The authors have found that this approach does minimize competition for time with existing content and allows mapping of content to existing curricular competencies and milestones, while encouraging a broad understanding of CCH in the context of individual patients, populations, and communities. This model for curricular integration can be applied to other topics such as social determinants of health, health equity, disability studies, and structural racism.

Autism spectrum disorder (ASD) is biologically and behaviorally heterogeneous. Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48 months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty‐four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4‐hydroxyproline, or α‐ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%–57%) and 91% specificity (95% CI, 86%–94%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments.Lay SummaryAnalysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18 months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood‐based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. Autism Res 2020, 13: 1270–1285. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.

MORC2 encodes an ATPase that plays a role in chromatin remodeling, DNA repair, and transcriptional regulation. Heterozygous variants in MORC2 have been reported in individuals with autosomal-dominant Charcot-Marie-Tooth disease type 2Z and spinal muscular atrophy, and the onset of symptoms ranges from infancy to the second decade of life. Here, we present a cohort of 20 individuals referred for exome sequencing who harbor pathogenic variants in the ATPase module of MORC2. Individuals presented with a similar phenotype consisting of developmental delay, intellectual disability, growth retardation, microcephaly, and variable craniofacial dysmorphism. Weakness, hyporeflexia, and electrophysiologic abnormalities suggestive of neuropathy were frequently observed but were not the predominant feature. Five of 18 individuals for whom brain imaging was available had lesions reminiscent of those observed in Leigh syndrome, and five of six individuals who had dilated eye exams had retinal pigmentary abnormalities. Functional assays revealed that these MORC2 variants result in hyperactivation of epigenetic silencing by the HUSH complex, supporting their pathogenicity. The described set of morphological, growth, developmental, and neurological findings and medical concerns expands the spectrum of genetic disorders resulting from pathogenic variants in MORC2.

HERC2 is a giant protein with E3 ubiquitin ligase activity and other known and suspected functions. Mutations of HERC2 are implicated in the pathogenesis of various cancers and result in severe neurological conditions in Herc2-mutant mice. Recently, a pleotropic autosomal recessive HERC2-associated syndrome of intellectual disability, autism and variable neurological deficits was described; its pathogenetic basis is largely unknown. Using peripheral blood-derived lymphoblasts from 3 persons with homozygous HERC2 variants and 14 age- and gender-matched controls, we performed label-free unbiased HPLC-tandem mass spectrometry-based proteomic analyses to provide insights into HERC2-mediated pathobiology. We found that out of 3427 detected proteins, there were 812 differentially expressed proteins between HERC2-cases vs. controls. 184 canonical pathways were enriched after FDR adjustment, including mitochondrial function, energy metabolism, EIF2 signaling, immune functions, ubiquitination and DNA repair. Ingenuity Pathway Analysis® identified 209 upstream regulators that could drive the differential expression, prominent amongst which were neurodegeneration-associated proteins. Differentially expressed protein interaction networks highlighted themes of immune function/dysfunction, regulation of cell cycle/cell death, and energy metabolism. Overall, the analysis of the HERC2-associated proteome revealed striking differential protein expression between cases and controls. The large number of differentially expressed proteins likely reflects HERC2's multiple domains and numerous interacting proteins. Our canonical pathway and protein interaction network findings suggest derangements of multiple pathways in HERC2-associated disease.

Autism Spectrum Disorder (ASD) is a set of heterogeneous neurodevelopmental conditions defined by impairments in social communication and restricted, repetitive behaviors, interests or activities. Only a minority of ASD cases are determined to have a definitive etiology and the pathogenesis of most ASD is poorly understood. We hypothesized that a global analysis of the proteomes of human ASD vs. control brain, heretofore not done, would provide important data with which to better understand the underlying neurobiology of autism. In this study, we characterized the proteomes of two brain regions, Brodmann area 19 (BA19) and posterior inferior cerebellum (CB), from carefully selected idiopathic ASD cases and matched controls using label-free HPLC-tandem mass spectrometry. The data revealed marked differences between ASD and control brain proteomes for both brain regions. Unlike earlier transcriptomic analyses using frontal and temporal cortex, however, our proteomic analysis did not support ASD attenuating regional gene expression differences. Bioinformatic analyses of the differentially expressed proteins between cases and controls highlighted canonical pathways involving glutamate receptor signaling and glutathione-mediated detoxification in both BA19 and CB; other pathways such as Sertoli cell signaling and fatty acid oxidation were specifically enriched in BA19 or CB, respectively. Network analysis of both regions of ASD brain showed up-regulation of multiple pre- and post-synaptic membrane or scaffolding proteins including glutamatergic ion channels and related proteins, up-regulation of proteins involved in intracellular calcium signaling, and down-regulation of neurofilament proteins, with DLG4 and MAPT as major hub proteins in BA19 and CB protein interaction networks, respectively. Upstream regulator analysis suggests neurodegeneration-associated proteins drive the differential protein expression for ASD in both BA19 and CB. Overall, the proteomic data provide support for shared dysregulated pathways and upstream regulators for two brain regions in human ASD brain, suggesting a common ASD pathophysiology that has distinctive regional expression.

Reanalysis of Clinical Exome Data and Diagnostic Yield As knowledge about genetic causes of disease improves, periodic reanalysis of clinical exome sequence could yield new genetic information. Thi...

Proteomics is a powerful tool to study biological systems and is potentially useful in identifying biomarkers for clinical screening and diagnosis, for monitoring treatment, and for exploring pathogenetic mechanisms in autism. Unlike numerous other experimental approaches employed in autism research, there have been few proteomic-based analyses. Herein, we discuss the findings of studies regarding autism that utilized a proteomic approach and review key considerations in sample acquisition, processing, and analysis. Most proteomic studies on autism used blood or other peripheral tissues. Few studies used brain tissue, the main site of biological difference between persons with autism and others. The findings have varied and are not yet replicated. Some showed abnormalities of synaptic proteins or proteins of mitochondrial bioenergetics. Various abnormalities of proteins relating to immune processes and lipid metabolism have also been noted. Whether any of the proteomic differences between autism and control cases are primary or secondary phenomena is currently unclear. Consequently, no definitive biomarkers for autism have been identified, and the pathophysiological insights provided by proteomic studies to date are uncertain in the absence of replication. Based on this body of work and the challenges in using proteomics to study autism, we suggest considerations for future study design. These include attention to subject and specimen inclusion/exclusion criteria, attention to the state of specimens prior to proteomic analysis, and use of a replicate set of specimens. We end by discussing especially promising applications of proteomics in the study of autism pathobiology.

The major diseases affecting the thoracic aorta are aneurysms and acute dissections, and pathogenic variants in 11 genes are confirmed to lead to heritable thoracic aortic disease. However, many families in which multiple members have thoracic aortic disease do not have alterations in the known aortopathy genes. Genes highly expressed in the aorta were assessed for rare variants in exome sequencing data from such families, and compound rare heterozygous variants (p.Pro45Argfs*25 and p.Glu750*) in LTBP3 were identified in affected members of one family. A homozygous variant (p.Asn678_Gly681delinsThrCys) that introduces an additional cysteine into an epidermal growth factor (EGF)-like domain in the corresponding protein, latent TGF-beta binding protein (LTBP-3), was identified in a second family. Individuals with compound heterozygous or homozygous variants in these families have aneurysms and dissections of the thoracic aorta, as well as aneurysms of the abdominal aorta and other arteries, along with dental abnormalities and short stature. Heterozygous carriers of the p.Asn678_Gly681delinsThrCys variant have later onset of thoracic aortic disease, as well as dental abnormalities. In these families, LTBP3 variants segregated with thoracic aortic disease with a combined LOD score of 3.9. Additionally, heterozygous rare LTBP3 variants were found in individuals with early onset of acute aortic dissections, and some of these variants disrupted LTBP-3 levels or EGF-like domains. When compared to wild-type mice, Ltbp3(-/-) mice have enlarged aortic roots and ascending aortas. In summary, homozygous LTBP3 pathogenic variants predispose individuals to thoracic aortic aneurysms and dissections, along with the previously described skeletal and dental abnormalities.

Background: Intellectual disability (ID) is a common condition with a population prevalence frequency of 1-3% and an enrichment for males, driven in part by the contribution of mutant alleles on the X-chromosome. Among the more than 500 genes associated with ID, DDX3X represents an outlier in sex specificity. Nearly all reported pathogenic variants of DDX3X are de novo, affect mostly females, and appear to be loss of function variants, consistent with the hypothesis that haploinsufficiency at this locus on the X-chromosome is likely to be lethal in males. Results: We evaluated two male siblings with syndromic features characterized by mild-to-moderate ID and progressive spasticity. Quad-based whole-exome sequencing revealed a maternally inherited missense variant encoding p.R79K in DDX3X in both siblings and no other apparent pathogenic variants. We assessed its possible relevance to their phenotype using an established functional assay for DDX3X activity in zebrafish embryos and found that this allele causes a partial loss of DDX3X function and thus represents a hypomorphic variant. Conclusions: Our genetic and functional data suggest that partial loss of function of DDX3X can cause syndromic ID. The p.R79K allele affects a region of the protein outside the critical RNA helicase domain, offering a credible explanation for the observed retention of partial function, viability in hemizygous males, and lack of pathology in females. These findings expand the gender spectrum of pathology of this locus and suggest that analysis for DDX3X variants should be considered relevant for both males and females.

Background Metabolic syndrome (MS) is a construct used to separate “healthy” from “unhealthy” obese patients, and is a major risk factor for type 2 diabetes (T2D) and cardiovascular disease. There is controversy over whether obese “metabolically well” persons have a higher morbidity and mortality than lean counterparts, suggesting that MS criteria do not completely describe physiologic risk factors or consequences of obesity. We hypothesized that metabolomic analysis of plasma would distinguish obese individuals with and without MS and T2D along a spectrum of obesity-associated metabolic derangements, supporting metabolomic analysis as a tool for a more detailed assessment of metabolic wellness than currently used MS criteria. Methods Fasting plasma samples from 90 adults were assigned to groups based on BMI and ATP III criteria for MS: (1) lean metabolically well (LMW; n = 24); (2) obese metabolically well (OBMW; n = 26); (3) obese metabolically unwell (OBMUW; n = 20); and (4) obese metabolically unwell with T2D (OBDM; n = 20). Forty-one amino acids/dipeptides, 33 acylcarnitines and 21 ratios were measured. Obesity and T2D effects were analyzed by Wilcoxon rank-sum tests comparing obese nondiabetics vs LMW, and OBDM vs nondiabetics, respectively. Metabolic unwellness was analyzed by Jonckheere-Terpstra trend tests, assuming worsening health from LMW → OBMW → OBMUW. To adjust for multiple comparisons, statistical significance was set at p < 0.005. K-means cluster analysis of aggregated amino acid and acylcarnitine data was also performed. Results Analytes and ratios significantly increasing in obesity, T2D, and with worsening health include: branched-chain amino acids (BCAAs), cystine, alpha-aminoadipic acid, phenylalanine, leucine + lysine, and short-chain acylcarnitines/total carnitines. Tyrosine, alanine and propionylcarnitine increase with obesity and metabolic unwellness. Asparagine and the tryptophan/large neutral amino acid ratio decrease with T2D and metabolic unwellness. Malonylcarnitine decreases in obesity and 3-OHbutyrylcarnitine increases in T2D; neither correlates with unwellness. Cluster analysis did not separate subjects into discreet groups based on metabolic wellness. Discussion Levels of 15 species and metabolite ratios trend significantly with worsening metabolic health; some are newly recognized. BCAAs, aromatic amino acids, lysine, and its metabolite, alpha-aminoadipate, increase with worsening health. The lysine pathway is distinct from BCAA metabolism, indicating that biochemical derangements associated with MS involve pathways besides those affected by BCAAs. Even those considered “obese, metabolically well” had metabolite levels which significantly trended towards those found in obese diabetics. Overall, this analysis yields a more granular view of metabolic wellness than the sole use of cardiometabolic MS parameters. This, in turn, suggests the possible utility of plasma metabolomic analysis for research and public health applications.