Newborn screening for autism: in search of candidate biomarkers

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

Maternal mid-gestational and child cord blood immune signatures are strongly associated with offspring risk of ASD

Epidemiological studies and work in animal models indicate that immune activation may be a risk factor for autism spectrum disorders (ASDs). We measured levels of 60 cytokines and growth factors in 869 maternal mid-gestational (MMG) and 807 child cord blood (CB) plasma samples from 457 ASD (385 boys, 72 girls) and 497 control children (418 boys, 79 girls) from the Norwegian Autism Birth Cohort. We analyzed associations first using sex-stratified unadjusted and adjusted logistic regression models, and then employed machine learning strategies (LASSO + interactions, Random Forests, XGBoost classifiers) with cross-validation and randomly sampled test set evaluation to assess the utility of immune signatures as ASD biomarkers. We found prominent case-control differences in both boys and girls with alterations in a wide range of analytes in MMG and CB plasma including but not limited to IL1RA, TNFα, Serpin E1, VCAM1, VEGFD, EGF, CSF1, and CSF2. MMG findings were most striking, with particularly strong effect sizes in girls. Models did not change appreciably upon adjustment for maternal conditions, medication use, or emotional distress ratings. Findings were corroborated using machine learning approaches, with area under the receiver operating characteristic curve values in the test sets ranging from 0.771 to 0.965. Our results are consistent with gestational immunopathology in ASD, may provide insights into sex-specific differences, and have the potential to lead to biomarkers for early diagnosis.

OUP accepted manuscript

Multiple pieces of evidence support the prenatal predisposition of autism spectrum disorder (ASD). Nevertheless, robust data about abnormalities in foetuses later developing into children diagnosed with ASD are lacking. Prenatal ultrasound is an excellent tool to study abnormal foetal development as it is frequently used to monitor foetal growth and identify foetal anomalies throughout pregnancy. We conducted a retrospective case-sibling-control study of children diagnosed with ASD (cases); their own typically developing, closest-in-age siblings (TDS); and typically developing children from the general population (TDP), matched by year of birth, sex and ethnicity to investigate the association between ultrasonography foetal anomalies and ASD. The case group was drawn from all children diagnosed with ASD enrolled at the National Autism Research Center of Israel. Foetal ultrasound data from the foetal anatomy survey were obtained from prenatal ultrasound clinics of Clalit Health Services in southern Israel. The study comprised 659 children: 229 ASD, 201 TDS and 229 TDP. Ultrasonography foetal anomalies were found in 29.3% of ASD cases versus only 15.9% and 9.6% in the TDS and TDP groups [adjusted odds ratio (aOR) = 2.23, 95% confidence interval (CI) = 1.32-3.78, and aOR = 3.50, 95%CI = 2.07-5.91, respectively]. Multiple co-occurring ultrasonography foetal anomalies were significantly more prevalent among ASD cases. Ultrasonography foetal anomalies in the urinary system, heart, and head and brain were the most significantly associated with ASD diagnosis (aORUrinary = 2.08, 95%CI = 0.96-4.50 and aORUrinary = 2.90, 95%CI = 1.41-5.95; aORHeart = 3.72, 95%CI = 1.50-9.24 and aORHeart = 8.67, 95%CI = 2.62-28.63; and aORHead&Brain = 1.96, 95%CI = 0.72-5.30 and aORHead&Brain = 4.67, 95%CI = 1.34-16.24; versus TDS and TDP, respectively). ASD females had significantly more ultrasonography foetal anomalies than ASD males (43.1% versus 25.3%, P = 0.013) and a higher prevalence of multiple co-occurring ultrasonography foetal anomalies (15.7% versus 4.5%, P = 0.011). No sex differences were seen among TDS and TDP controls. ASD foetuses were characterized by a narrower head and a relatively wider ocular-distance versus TDP foetuses (ORBPD = 0.81, 95%CI = 0.70-0.94, and aOROcular distance = 1.29, 95%CI = 1.06-1.57). Ultrasonography foetal anomalies were associated with more severe ASD symptoms. Our findings shed important light on the multiorgan foetal anomalies associated with ASD.

Alterations of urinary perchlorate levels in euthyroid postpubertal children with autism spectrum disorder

BACKGROUND

Perchlorates ClO₄(^-) are known environmental and food contaminants that act as inhibitors of iodine uptake by the thyroid gland; however, information concerning their possible association with the development of autism spectrum disorder (ASD) is still missing. The current study is first presenting the alterations in perchlorate urine levels in euthyroid children with ASD.

OBJECTIVES

To examine urinary perchlorates and iodides in euthyroid children diagnosed with ASD, compared to age-, and BMI-matched neurotypical controls, and to verify the association between these two ions in ASD.

METHODS

Ions were determined in 24 h urine samples determined by ion chromatography-conductivity cell detection (IC-CD) and ion chromatography-pulsed amperometric detection (IC-PAD) techniques, respectively, in a total of 130 postpubertal euthyroid children with normal BMI (the mean age 14.46 years, SD = 1.32; the mean BMI 20.6, SD = 1.37), divided into age- and BMI-matched groups of ASD patients and neurotypical, healthy children (control).

RESULTS

The ASD group presented with significantly higher perchlorate urine levels than the controls (median = 1.05 μg/L, interquartile range(IQR) = 1.5 versus median = 0.09 μg/L, IQR = 0.097, respectively), as well as lower iodide urine levels (median = 100.2 μg/L, IQR = 37 versus median = 156.95 μg/L, IQR = 26.11, respectively). The ASD group presented significantly lower TSH and higher free thyroid hormone (fT4, fT3) levels than the controls. In regression analyses, perchlorate urine levels showed significant positive relationships with normal BMI values and serum TSH, and inverse relationships with serum fT4. Urinary iodide levels showed significant inverse relationships with BMI values. The absence of ASD was associated with decreased odds of perchlorate urine levels (OR = 0.012, 95 % confidence interval [CI] 0.0002-0.76), and increased odds of iodide urine levels (OR = 1.15, 95 %CI 1.05-1.27).

CONCLUSIONS

ASD may have an independent and significant impact on perchlorate as well as iodide levels in urine of euthyroid lean postpubertal children. Perchlorate levels do not appear to be directly associated with iodide levels in euthyroid children.

Studying Autism Using Untargeted Metabolomics in Newborn Screening Samples

Main risk factors of autism spectrum disorder (ASD) include both genetic and non-genetic factors, especially prenatal and perinatal events. Newborn screening dried blood spot (DBS) samples have great potential for the study of early biochemical markers of disease. To study DBS strengths and limitations in the context of ASD research, we analyzed the metabolomic profiles of newborns later diagnosed with ASD. We performed LC-MS/MS-based untargeted metabolomics on DBS from 37 case-control pairs randomly selected from the iPSYCH sample. After preprocessing using MZmine 2.41, metabolites were putatively annotated using mzCloud, GNPS feature-based molecular networking, and MolNetEnhancer. A total of 4360 mass spectral features were detected, of which 150 (113 unique) could be putatively annotated at a high confidence level. Chemical structure information at a broad level could be retrieved for 1009 metabolites, covering 31 chemical classes. Although no clear distinction between cases and controls was revealed, our method covered many metabolites previously associated with ASD, suggesting that biochemical markers of ASD are present at birth and may be monitored during newborn screening. Additionally, we observed that gestational age, age at sampling, and month of birth influence the metabolomic profiles of newborn DBS, which informs us on the important confounders to address in future studies.

Blood biomarker discovery for autism spectrum disorder: A proteomic analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. A wide range of putative biological markers for ASD is currently being investigated. Proteomic analyses indicate that the levels of many proteins in plasma/serum are altered in ASD, suggesting that a panel of proteins may provide a blood biomarker for ASD. Serum samples from 76 boys with ASD and 78 typically developing (TD) boys, 18 months-8 years of age, were analyzed to identify possible early biological markers for ASD. Proteomic analysis of serum was performed using SomaLogic’s SOMAScan^TM assay 1.3K platform. A total of 1,125 proteins were analyzed. There were 86 downregulated proteins and 52 upregulated proteins in ASD (FDR < 0.05). Combining three different algorithms, we found a panel of 9 proteins that identified ASD with an area under the curve (AUC) = 0.8599±0.0640, with specificity and sensitivity of 0.8217±0.1178 and 0.835±0.1176, respectively. All 9 proteins were significantly different in ASD compared with TD boys, and were significantly correlated with ASD severity as measured by ADOS total scores. Using machine learning methods, a panel of serum proteins was identified that may be useful as a blood biomarker for ASD in boys. Further verification of the protein biomarker panel with independent test sets is warranted.

Global metabolomic profiling reveals hepatic biosignatures that reflect the unique metabolic needs of late-term mother and fetus

OBJECTIVE

Gestational disorders including preeclampsia, growth restriction and diabetes are characterized, in part, by altered metabolic interactions between mother and fetus. Understanding their functional relevance requires metabolic characterization under normotypic conditions.

METHODS

We performed untargeted metabolomics on livers of pregnant, late-term C57Bl/6J mice (N = 9 dams) and their fetuses (pooling 4 fetuses/litter), using UPLC-MS/MS.

RESULTS

Multivariate analysis of 730 hepatic metabolites revealed that maternal and fetal metabolite profiles were highly compartmentalized, and were significantly more similar within fetuses (ρ_average = 0.81), or within dams (ρ_average = 0.79), than within each maternal-fetal dyad (ρ_average = - 0.76), suggesting that fetal hepatic metabolism is under distinct and equally tight metabolic control compared with its respective dam. The metabolite profiles were consistent with known differences in maternal-fetal metabolism. The reduced fetal glucose reflected its limited capacity for gluconeogenesis and dependence upon maternal plasma glucose pools. The fetal decreases in essential amino acids and elevations in their alpha-keto acid carnitine conjugates reflects their importance as secondary fuel sources to meet fetal energy demands. Whereas, contrasting elevations in fetal serine, glycine, aspartate, and glutamate reflects their contributions to endogenous nucleotide synthesis and fetal growth. Finally, the elevated maternal hepatic lipids and glycerol were consistent with a catabolic state that spares glucose to meet competing maternal-fetal energy demands.

CONCLUSIONS

The metabolite profile of the late-term mouse dam and fetus is consistent with prior, non-rodent analyses utilizing plasma and urine. These data position mouse as a suitable model for mechanistic investigation into how maternal-fetal metabolism adapts (or not) to gestational stressors.

Immune activity at birth and later psychopathology in childhood

Disruption of neurodevelopmental trajectories can alter brain circuitry and increase the risk of psychopathology later in life. While preclinical studies have demonstrated that the immune system and cytokines influence neurodevelopment, whether immune activity and in particular which cytokines at birth are associated with psychopathology remains poorly explored in children. We used data and biological samples from 869 mother-child pairs participating in the French mother-child cohort EDEN. As proxies for immune activity at birth, we measured the levels of 27 cytokines in umbilical cord blood sera (CBS). We then explored the association between CBS cytokine levels and five psychopathological dimensions assessed in 5-year-old children using the Strengths and Difficulties Questionnaire (SDQ). Five cytokines were positively associated with psychopathology: C-X-C motif chemokine Ligand (CXCL)10, interleukin (IL)-10 and IL-12p40 with emotional symptoms, C–C motif chemokine Ligand (CCL)11 with conduct problems, and CCL11, and IL-17A with peer relationships problems. In contrast, seven cytokines were negatively associated with psychopathology: IL-7, IL-15 and Tumor Necrosis Factor (TNF)-β with emotional symptoms, CCL4 and IL-6 with conduct problems, CCL26 and IL-15 with peer relationships problems, and CCL26, IL-7, IL-15, and TNF-α with abnormal prosocial behavior. Without implying causation, these associations support the notion that cytokines influence neurodevelopment in humans and the risk of psychopathology later in life.

•

Twelve cytokines at birth are associated with psychopathology in 5-year-old children.

•

IL-7, IL-10, IL-12p40, IL-15, TNF-β and CXCL10 are associated with emotional symptoms.

•

IL-6, CCL4 and CCL11 are associated with conduct problems.

•

IL-15, IL-17A, CCL11 and CCL26 are associated with peer relationship problems.

•

IL-7, IL-15, TNF-α and CCL26 are associated with prosocial behavior.

The association between newborn screening analytes as measured on a second screen and childhood autism in a Texas Medicaid population

Autism (or autism spectrum disorder [ASD]) is an often disabling childhood neurologic condition of mostly unknown cause. We previously explored whether there was an association of ASD with any analyte measured in the first newborn screening blood test. Here we explore the second screen. Our matched case-control study examined data on 3-5 year-old patients with any ASD diagnosis in the Texas Medicaid system in 2010-2012. Subjects were linked to their 2007-2009 newborn screening blood test data, which included values for 36 analytes or analyte ratios. Data were available for 3,005 cases and 6,212 controls. The most compelling associations were evident for fatty acid oxidation analytes octanoylcarnitine (C8) and octanoylcarnitine/acetylcarnitine (C8/C2). Their adjusted odds ratios comparing 10th versus first analyte deciles were between 1.42 and 1.54 in total births, term births, and males. C8 was consistent with first screen results. Adipylcarnitine (C6DC), an organic acid analyte, showed opposite results in the two screens. Several other analytes exhibiting significant associations in the first screen did not in the second. Our results provide evidence that abnormal newborn blood levels of some carnitines may be associated with risk of later ASD, possibly related to their involvement with mitochondrial function in the developing brain.

Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy

Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results.

The association between newborn screening analytes and childhood autism in a Texas Medicaid population, 2010-2012

Autism (or autism spectrum disorder [ASD]) is an often disabling childhood neurologic condition of mostly unknown cause. It is commonly diagnosed at 3 or 4 years of age. We explored whether there was an association of any analytes measured by newborn screening tests with a later diagnosis of ASD. A database was compiled of 3-5 year-old patients with any ASD diagnosis in the Texas Medicaid system in 2010-2012. Two controls (without any ASD diagnosis) were matched to each case by infant sex and birth year/month. All study subjects were linked to their 2007-2009 birth and newborn screening laboratory records, including values for 36 analytes or analyte ratios. We examined the association of analytes/ratios with a later diagnosis of ASD. Among 3,258 cases and 6,838 controls, seven analytes (e.g., 17-hydroxyprogesterone, acylcarnitines) were associated with a later ASD diagnosis. In this exploratory study, an ASD diagnosis was associated with 7 of 36 newborn screening analytes/ratios. These findings should be replicated in other population-based datasets.

Associations between SNPs and immune-related circulating proteins in schizophrenia

Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis.

Serum thyroid-stimulating hormone and interleukin-8 levels in boys with autism spectrum disorder

Background

Autism spectrum disorder (ASD) affects approximately 1 in 68 children in the USA. An ASD blood biomarker may enable early diagnosis and/or identification of new therapeutic targets. Serum samples from ASD and typically developing (TD) boys (n = 30/group) were screened for differences in 110 proteins using a multiplex immunoassay.

Results

Eleven proteins were found that together could confirm ASD with modest accuracy using multiple training and test sets. Two of the 11 proteins identified here were further tested using a different detection platform and with a larger sample of ASD and TD boys. The two proteins, thyroid-stimulating hormone (TSH) and interleukin-8 (IL-8), have been previously identified as putative biomarkers for ASD. TSH levels were significantly lower in ASD boys, whereas IL-8 levels were significantly elevated. The diagnostic accuracy for ASD based upon TSH or IL-8 levels alone varied from 74 to 76%, but using both proteins together, the diagnostic accuracy increased to 82%. In addition, TSH levels were negatively correlated with the Autism Diagnostic Observation Schedule subdomain scores.

Conclusions

These data suggest that a panel of proteins may be useful as a putative blood biomarker for ASD.

Assessing the iron delivery efficacy of transferrin in clinical samples by native electrospray ionization mass spectrometry

Serum transferrin is a key player in iron homeostasis, and its ability to deliver iron to cells via the endosomal pathway critically depends on the presence of carbonate that binds this protein synergistically with ferric ion. Oxalate is another ubiquitous anionic species that can act as a synergistic anion, and in fact its interaction with transferrin is notably stronger compared to carbonate, preventing the protein from releasing the metal in the endosomal environment. While this raises concerns that high oxalate levels in plasma may interfere with iron delivery to tissues, concentration of free oxalate in blood appears to be a poor predictor of impeded availability of iron, as previous studies showed that it cannot displace carbonate from ferro-transferrin on a physiologically relevant time scale under the conditions mimicing plasma. In this work we present a new method that allows different forms of ferro-transferrin (carbonate- vs. oxalate-bound) to be distinguished from each other by removing this protein from plasma without altering the composition of the protein/metal/synergistic anion complexes, and determining their accurate masses using native electrospray ionization mass spectrometry (ESI MS). The new method has been validated using a mixture of recombinant proteins, followed by its application to the analysis of clinical samples of human plasma, demonstrating that native ESI MS can be used in clinical analysis.

Activity-Regulated Cytoskeleton-Associated Protein Dysfunction May Contribute to Memory Disorder and Earlier Detection of Autism Spectrum Disorders

OBJECTIVE

To explore a possible role for activity-regulated cytoskeleton-associated (Arc/Arg3.1) protein in the clinical identification of children with autism.

SUBJECTS AND METHODS

The plasma levels of Arc/Arg3.1 in 62 boys with autism and 32 healthy boys were measured using an enzyme-linked immunosorbent assay (ELISA). The Childhood Autism Rating Scale (CARS) was used to assess the severity of autism as defined in the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). The Mann-Whitney U test was used for comparisons between children with autism and healthy children. The Spearman r correlation coefficient (r) was used to determine the relationship between the CARS scores among patients with autism and different variables.

RESULTS

The mean plasma level of Arc/Arg3.1 protein in autism was 1.689 ± 0.917 pg/ml, significantly higher than that of healthy controls, i.e. 0.792 ± 1.056 pg/ml (p < 0.001). No significant relationship was found between plasma levels of Arc/Arg3.1 protein and CARS scores (r = -0.06; p > 0.05) or age (r = -0.27; p > 0.05).

CONCLUSIONS

The mean plasma level of Arc/Arg3.1 protein was higher in children with autism than in controls, suggesting that Arc/Arg3.1 could be a potential early blood biomarker for diagnosis of autism.

Identification of an Immune-Neuroendocrine Biomarker Panel for Detection of Depression: A Joint Effects Statistical Approach

BACKGROUND/AIMS

Less than half of depression patients are correctly diagnosed within the primary care setting. Previous proteomic studies have identified numerous immune and neuroendocrine changes in patients. However, few studies have considered the joint effects of biological molecules and their diagnostic potential. Our aim was to develop and validate a diagnostic serum biomarker panel identified through joint effects analysis of multiplex immunoassay profiling data from 1,007 clinical samples.

METHODS

In stage 1, we conducted a meta-analysis of two independent cohorts of 78 first-/recent-onset drug-naive/drug-free depression patients and 156 controls and applied the 10-fold cross-validation with least absolute shrinkage and selection operator regression to identify an optimal diagnostic prediction model (biomarker panel). In stage 2, we tested the discriminatory performance of this biomarker panel using the naturalistic Netherlands Study of Depression and Anxiety (NESDA) cohort of 468 depression patients and 305 controls.

RESULTS

An optimal panel of 33 immune-neuroendocrine biomarkers and gender was selected in the meta-analysis. Testing this biomarker-gender panel using the NESDA cohort resulted in a moderate to good performance to differentiate patients from controls (0.69 < AUC < 0.86), particularly the first-episode patients free of chronic non-psychiatric diseases or medications and following incorporation of sociodemographic covariates (0.76 < AUC < 0.92).

CONCLUSION

Despite the need for additional validation studies, we demonstrated that a blood-based biomarker-sociodemographic panel can detect depression in naturalistic healthcare settings with good discriminatory power. Further refinements of blood biomarker panels aiding in the diagnosis of depression may provide a cost-effective means to increase accuracy of clinical diagnosis within the primary care setting.

Biomarkers in autism

Autism spectrum disorders (ASDs) are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression, and measures of the body's metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers.