1 Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
2 Department of Neurology, Walter Reed National Military Medical Center, Bethesda, MD 20889, USA
3 Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
4 Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817, USA
Abstract
Autism spectrum disorder (ASD) can be diagnosed as early as 18 months old, but more reliably after two years. Notably, no laboratory test exists to identify mothers at higher risk of having a child who will later be diagnosed with ASD or to identify at-risk infants before the manifestation of symptoms. One frequently described risk factor for neurodevelopmental disorders is vitamin B12 and folate deficiency, which results in macrocytic anemias.
We evaluated whether increased mean corpuscular volume (MCV), an indicator of macrocytic anemias in the mother or child, is associated with increased odds of a subsequent ASD diagnosis. Maternal mean MCV (mMCV) was calculated from any value in the year before birth, and the mMCV for the child was calculated from any MCV value from birth until the end of the follow-up time. Odds ratios with 95% confidence intervals were estimated from logistic regression models.
A total of 3798 mothers (984 cases—ASD/2814 controls) and 9633 children (3206 cases—ASD/6427 controls) had at least one MCV value. The mMCV for the mother one year before birth was not associated with a later diagnosis of ASD in their children. In children, compared to the reference group (mMCV 76 femtoliters (fL)), an mMCV of 81 fL, 84 fL, and 91 fL was increased odds of ASD of 26%, 38%, and 32%, respectively.
The MCV can be a potential inexpensive biomarker to identify a subset of children at risk of ASD or other developmental disorders; this exploratory study can inform larger studies to determine the clinical utility of MCV.
Keywords
- autism spectrum disorder
- folate
- vitamin B12
- mean corpuscular volume
- neurodevelopmental disorders
- nutrition
Autism Spectrum Disorder (ASD) is a developmental disability that causes a wide array of deficits, including significant difficulty in social communication and interaction, repetitive behaviors, and restricted interests [1]. Over the last 20 years, the prevalence of ASD in the United States has been steadily increasing, with a new study published in April 2025 reporting a prevalence of 3.22‰ (one in 31) in 2022 [2], up from 23.0 per 1000 children in the surveillance year 2018 [3] and approximately 4.8 times higher than the first ADDM estimate between 2000 to 2002 at 6.7 per 1000 (one in 150) [2]. Currently, ASD can be diagnosed as early as 18 months of age and more reliably after two years based on signs and symptoms showing behavioral or developmental delays [4, 5]. No laboratory test exists to identify mothers at higher risk of having a child later diagnosed with ASD or to identify at-risk infants before the manifestation of symptoms. Studies have assessed potential biomarkers for early diagnosis of ASD, specifically biomarkers of oxidative stress, which include folate and vitamin B12 (vB12) and its metabolites [6].
The multifactorial theory of ASD risk is broadly accepted and is complex, including genetic and environmental risk factors (e.g., maternal health, medications, and pollutants), to name a few [7, 8, 9]. One risk factor for neurodevelopmental disorders that has been described is maternal nutritional status, particularly during the critical period for developing ASD, in utero or early infancy [10, 11, 12, 13, 14]. Over the past six decades, case reports and literature reviews have reported developmental regression and negative consequences on brain development during infancy associated with maternal nutritional deficiencies, including folate and vB12 [11, 12, 13, 14, 15]. The use of medications that reduce folate or vB12 levels during pregnancy, such as valproic acid and metformin, as well as maternal hyperemesis [16], possibly a surrogate for maternal low nutritional status, have also been linked to increased risk of ASD [16, 17, 18]. The Methylenetetrahydrofolate-reductase (MTHFR) 677CT polymorphism, which impairs the efficiency of the one-carbon metabolic pathway and affects the ability to efficiently utilize folate and vB12 [19], is more common among children with ASD and their mothers [20] and may be associated with more severe ASD symptoms [21]. In addition, this polymorphism had shown to be a moderate predictor of ASD with synergistic interaction with hyperhomocysteinemia [22], a marker for both vB12 and/or folate deficiency.
In adults, screening for vB12 and folate deficiency is only recommended for high-risk individuals such as those with a vegetarian diet, with disorders of the intestines that may affect absorption, or those taking medications that cause drug-induced depletion [23, 24]. While there are currently no published guidelines for antenatal screening for vB12 and folate deficiency, it has been recommended [24]. VB12 deficiency in women of childbearing age and pregnant women worldwide is fairly common [18]. In a multi-national meta-analysis, the overall prevalence of vB12 insufficiency in pregnant women across all trimesters was estimated at 25% [25], and an Italian study found low vB12 levels during 48% of randomly selected pregnancies in healthy women [18].
In newborns, vB12 deficiency is most often of maternal origin [18]. Newborns are normally born with 25 ug of vB12 in the liver, which is thought to be enough for the first year of life [26]; however, fetal vB12 storage is significantly decreased in mothers with vB12 deficiency [27], especially those who are breastfed from deficient mothers [18]. Currently, in newborns, screening for vB12 and folate deficiencies is not the standard of care; infants are only screened after becoming symptomatic. While infants usually become symptomatic between 4–6 months of life, diagnosis is often not made until 6 months or later [18].
In this study, we aimed to find a laboratory biomarker that is routinely ordered during prenatal and well-baby visits. The complete blood count (CBC) is an inexpensive clinical laboratory test that can be routinely applied in clinical practice to screen for anemias in pregnancy [28]. The mean corpuscular volume (MCV), an index of the CBC, is used in conjunction with hemoglobin and hematocrit to assist with elucidating the type of anemia the patient may have based on the MCV value. In this study, we evaluated whether an increased mean MCV in the mother in the year before birth is associated with increased odds of having a child with ASD and whether the child’s mean MCV is associated with increased odds of ASD diagnosis.
Data came from a previously created retrospective matched case-control study using the Military Healthcare System (MHS) Data Repository (MDR). It is comprised of inpatient and outpatient records of low to no-cost healthcare provided to over 4 million uniformed service members, military retirees, and dependent family members, who demographically generally mirror the U.S. population, with some over-representation of minority groups [29]. A previously validated methodology [30] which found two or more International Classification of Disease, Ninth Revision (ICD-9) diagnoses was consistent with chart review validation, was used to identify cases of ASD with ICD-9 diagnostic codes between ages 2 and 18 at two separate inpatient or outpatient encounters between 01 October 2000 and 30 September 2013. All cases and controls have a birth record in the Military Health System. Three controls were matched to each case by the child’s date of birth, sex, and length of time the children were followed. For both cases and controls, children with only one diagnostic code were excluded, as were children diagnosed with ICD-9 code 330.8 (childhood disintegrative disorder), which includes Rett syndrome. The mothers of cases and controls were followed for at least one year before the child’s birth. All children were followed from birth. Included children had at least six months of documented care before the first diagnosis of ASD and at least 6 months of care following their second ASD diagnosis. Controls had at least 12 months of follow-up. In this present study, mothers and children were included if either the mother or child had at least one MCV lab value in their medical records, which could only be extracted for care provided at Military Treatment Facilities. The matched format from the original study was not maintained.
The MCV test is performed as part of the automated CBC in the laboratory. The whole blood is collected in a lavender top tube, avoiding hemolysis, and is transported to the hematology laboratory, in which the blood is passed through automated machines that calculate the red blood cell (RBC) indices. The MCV is a measure of the average volume, or size, of a single RBC and is therefore used in classifying anemias. MCV is expressed as femtoliters (fL) and is derived by dividing the hematocrit by the total RBC count: MCV = Hematocrit (%)
Maternal factors included in the analysis were the mother’s age at the time of the child’s birth, the total number of MCV results, mean MCV, and mean hemoglobin, calculated from any MCV or hemoglobin value at any point in the year before the child’s birth. In our previous study, an MCV cutoff above 93 fL correctly identified abnormal methylmalonic acid (MMA) levels (defined as MMA
Multiple MCV and hemoglobin values were available for some of our subjects, and the age at which lab tests were performed varied among the children. Ideally, using the first lab value available or analyzing specific time frames would have been preferable, given that myelination is most significant in the earlier years of development. However, using a specific timeframe based on when the lab tests were performed (e.g.,
Logistic regression analyses were used to calculate the unadjusted and adjusted odds ratio with a 95% confidence interval (CI) of ASD risk. For maternal data, mean MCV was analyzed per a 10 fL increase in MCV (mean MCV10 fL). To meet the linearity assumption, children’s mean MCV was optimally transformed by creating a categorical variable for children’s MCV by quartile. Trends across the categories were also assessed. In children, sensitivity analyses were performed using the first available MCV value and also the last available MCV value for the analysis. Lastly, in the children’s analysis, MCV was analyzed using low MCV, normal MCV, and high MCV groups. Normal MCV was defined separately for
Of the 8760 mothers of cases, 984 (11.2%) had at least one MCV value, and of the 26,280 control mothers, 2814 (10.7%) had at least one MCV value. Of the mothers with at least one MCV lab value, four mothers of children with ASD and nine mothers from the control group did not have a hemoglobin lab value available. 3206 (36.6%) children with ASD and 6427 (25%) controls had at least one MCV value. These proportions represent a percentage of the original cases and controls from the 1:3 matched birth cohort. All children with an MCV value had at least one hemoglobin value. Mothers who had at least one MCV lab value were younger (28.69 vs. 29.37, p
Fig. 1. Flow diagram of Mothers’ and Children’s data. MCV, mean corpuscular volume.
The mean MCV for mothers of children with ASD was not significantly different from mothers of children without ASD (88.36 vs. 88.64, p = 0.15). The mean age for mothers at birth was slightly higher in moms with children with ASD compared to those with children without ASD (28.06 vs. 28.56, p = 0.009). The median age of ASD diagnosis of the child, in the mother’s data, was 2.51 years old. No differences in the mean hemoglobin levels were found between the case and control groups (12.23 vs. 12.28 g/dL, p = 0.25), and when stratified by mean MCV levels, no differences were found. The mothers in the case group had similar mean hematocrit levels to the mothers in the control group (35.81 vs. 36.00, p = 0.07). When stratified by mean MCV levels, in mothers who had a mean MCV between
| Mothers | ||||||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 3798 | N = 984 | N = 2814 | ||||
| Mother’s age at child’s birth (years) | ||||||
| Mean (SD) | 28.43 (5.19) | 28.06 (5.24) | 28.56 (5.17) | 0.009 | ||
| MCV (fL) | ||||||
| Mean (SD) | 88.57 (5.18) | 88.36 (5.29) | 88.64 (5.14) | 0.15 | ||
| Gestational age of mother at time of MCV result (months) | ||||||
| Mean (SD) | 3.07 (3.28) | 3.09 (3.28) | 3.07 (3.27) | 0.84 | ||
| Age of child at ASD diagnosis | ||||||
| Median (range) | – | 2.51 (2.44–2.56) | – | |||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 3785 | N = 980 | N = 2805 | ||||
| Hemoglobin (g/dL) | ||||||
| Mean (SD) | 12.27 (1.05) | 12.23 (1.07) | 12.28 (1.04) | 0.25 | ||
| Hemoglobin/MCV Level | ||||||
| Mean MCV | 10.99 (1.31) | 11.18 (1.59) | 10.92 (1.18) | 0.19 | ||
| Mean MCV | 12.35 (0.98) | 12.31 (0.99) | 12.36 (0.98) | 0.17 | ||
| Mean MCV | 12.11 (1.10) | 11.46 (1.07) | 12.34 (1.04) | 0.09 | ||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 3773 | N = 973 | N = 2800 | ||||
| Hematocrit | ||||||
| Mean (SD) | 35.95 (2.88) | 35.81 (2.93) | 36.00 (2.85) | 0.07 | ||
| Hematocrit/MCV Level | ||||||
| Mean MCV | 33.33 (3.70) | 33.59 (4.40) | 33.23 (3.43) | 0.54 | ||
| Mean MCV | 36.11 (2.74) | 35.95 (2.76) | 36.17 (2.73) | 0.04 | ||
| Mean MCV | 35.75 (2.88) | 34.72 (1.51) | 36.05 (3.14) | 0.38 | ||
| Number of MCV labs available | ||||||
| Mean (SD) | 3.01 (2.24) | 3.23 (2.18) | 3.04 (2.26) | 0.02 | ||
| Children | ||||||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 9633 | N = 3206 | N = 6427 | ||||
| Mean child’s age (years) | ||||||
| Median (range) | 3.70 (0.00–10.79) | 3.90 (0.00–10.68) | 3.57 (0.00–10.79) | |||
| Mean age in categories (years) | N | |||||
| Median (range) | ||||||
| N = 1170 | N = 298 | N = 872 | ||||
| 0.34 (0.00–1.00) | 0.33 (0–1.00) | 0.34 (0.00–1.00) | ||||
| N = 1820 | N = 507 | N = 1313 | ||||
| 1.30 (1.00–2.00) | 1.42 (1.00–2.00) | 1.26 (1.00–2.00) | ||||
| N = 1093 | N = 426 | N = 667 | ||||
| 2.46 (2.00–3.00) | 2.47 (2.00–3.00) | 2.45 (2.00–3.00) | 0.09 | |||
| N = 1048 | N = 414 | N = 634 | ||||
| 3.47 (3.00–4.00) | 3.47 (3.00–3.99) | 3.48 (3.00–4.00) | 0.48 | |||
| N = 4502 | N = 1561 | N = 2941 | ||||
| 6.13 (4.00–10.79) | 6.10 (4.00–10.68) | 6.14 (4.00–10.79) | 0.13 | |||
| Age of child at ASD diagnosis | ||||||
| Median (min–max) | – | 3.38 (2.00–10.22) | – | |||
| Male child | ||||||
| N (%) | 7677 (80%) | 2526 (79%) | 5151 (80%) | 0.12 | ||
| MCV (fL) | ||||||
| Total Mean (SD) | 82.83 (7.03) | 83.15 (6.65) | 82.67 (7.21) | |||
| By Quartiles | ||||||
| (Q1) N = 2402 | 76 (3.86) | 76 (4.54) | 75.65 (3.58) | 0.96 | ||
| (Q2) N = 2408 | 80.68 (0.87) | 80.72 (0.86) | 80.67 (0.88) | 0.17 | ||
| (Q3) N = 2383 | 84 (0.88) | 83.61 (0.88) | 83.63 (0.88) | 0.69 | ||
| (Q4) N = 2440 | 91 (7.24) | 90.48 (6.48) | 91.68 (7.61) | |||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 9629 | N = 3206 | N = 6423 | ||||
| Hemoglobin (g/dL) | ||||||
| Mean (SD) | 12.65 (1.42) | 12.73 (1.37) | 12.61 (1.44) | |||
| Hemoglobin/MCV Level | ||||||
| Mean MCV | 12.10 (0.98) | 12.19 (0.96) | 12.06 (0.98) | 0.001 | ||
| Mean MCV | 12.69 (1.15) | 12.76 (1.10) | 12.65 (1.17) | |||
| Mean MCV | 16.42 (2.41) | 16.71 (2.80) | 16.31 (2.26) | 0.17 | ||
| All included† | Cases with ASD* | Controls, no ASD* | p value | |||
| N = 9630 | N = 3206 | N = 6424 | ||||
| Hematocrit | ||||||
| Mean (SD) | 37.03 (4.18) | 37.20 (4.00) | 36.94 (4.26) | 0.004 | ||
| Hematocrit/MCV Level | ||||||
| Mean MCV | 35.48 (2.87) | 35.69 (2.73) | 35.40 (2.91) | 0.01 | ||
| Mean MCV | 37.11 (3.39) | 37.26 (3.22) | 37.03 (3.48) | 0.008 | ||
| Mean MCV | 48.00 (7.33) | 48.92 (8.36) | 47.67 (6.92) | 0.15 | ||
| Number of MCV labs available | ||||||
| Mean (SD) | 1.90 (3.29) | 2.24 (4.32) | 1.74 (2.62) | |||
* ASD, Autism Spectrum Disorder.
† at least one MCV value.
The median age at the time of the lab test for children with ASD was higher than those without ASD (3.90 vs. 3.57, p
Mothers of children with ASD had a slightly higher mean number of MCV lab data values available compared to the controls (3.23 vs. 3.04, p = 0.02). Similarly, the mean number of MCV labs available for children with ASD was also slightly higher than for the non-ASD group (2.24 vs. 1.74, p
We did not find an association between mean maternal MCV, maternal factors, and ASD. The mother’s age was associated with decreased odds of ASD (adjusted odds ratio (aOR) 0.98%, 95% CI [0.97–1.00]). An increase in the mean number of labs available was associated with 4% increased odds of ASD. These results are summarized in Table 2.
| Model 1: Unadjusted odds of ASD by maternal MCV and maternal factors *† | ||||
| N | Maternal factors | Odds ratio | 95% Confidence interval | p |
| 3798 | Mean MCV (fL) | 0.99 | 0.98–1.00 | 0.145 |
| 3798 | Mean MCV (fL) Cutoff 93 | 0.91 | 0.76–1.11 | 0.36 |
| 3798 | Maternal age at child’s birth (years) | 0.98 | 0.97–1.00 | 0.009 |
| 3785 | Mean Hemoglobin (g/dL) | 0.96 | 0.90–1.02 | 0.251 |
| 3798 | Number of MCV labs per mother | 1.04 | 1.01–1.07 | 0.02 |
| Model 2: Adjusted odds of ASD by maternal MCV and maternal factors* | ||||
| N | Maternal factors | Odds ratio | 95% Confidence interval | p |
| 9629 | Mean MCV (fL) | 0.99 | 0.98–1.01 | 0.24 |
| Maternal age at child’s birth (years) | 0.98 | 0.97–1.00 | 0.02 | |
| Number of MCV labs per mother | 1.04 | 1.01–1.07 | 0.02 | |
* Number of labs available is not a maternal factor; however, added to the model to adjust for confounding; odds ratios adjusted for other independent variables in the table.
† Model 1 Odds ratios are run separately for each independent variable in the table.
Overall, there were significant interactions between child MCV and sex (p = 0.02) and between MCV and categorical age (p = 0.002); therefore, stratified odds ratios for MCV were reported. The mean MCV in quartile 2 (Q2), quartile 3 (Q3) and quartile 4 (Q4) was 81 fL, 84 fL and 91 fL. The mean MCV in the referent group, quartile 1 (Q1), was 76 fL (Table 3A,3B). In children, compared to the referent group, Q2, Q3, and Q4 were associated with 26%, 38%, and 32% increased odds of ASD, (aOR 1.26, 95% CI [1.11–1.43], aOR 1.38, 95% CI [1.22–1.57] and aOR 1.32, 95% CI [1.15–1.51]). When stratified by age and sex, compared to the referent group (mean MCV 76 fL), Q4 was associated with 83% and 96% increased odds of ASD in boys
| Model 1: Adjusted odds of ASD by mean child MCV quartile and child factors*† | |||||||||||||
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | ||||||||||
| Mean MCV 76 | Mean MCV 81 | Mean MCV 84 | Mean MCV 91 | ||||||||||
| N | Child factors | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p |
| 9629 | Mean MCV (quartiles) (fL) | Reference | 1.26 | 1.11–1.43 | 1.38 | 1.22–1.57 | 1.32 | 1.15–1.51 | |||||
| Mean Hemoglobin (g/dL) | 1.04 | 1.01–1.07 | 0.01 | n/a | n/a | n/a | n/a | n/a | n/a | ||||
| Number of MCV labs available | 1.06 | 1.01–1.07 | n/a | n/a | n/a | n/a | n/a | n/a | |||||
| Mean age (years) | 1.02 | 1.01–1.04 | |||||||||||
| Model 2: Unadjusted odds of ASD by mean child MCV quartile stratified by child’s age at the time of MCV lab study and sex* | |||||||||||||||
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | ||||||||||||
| Mean MCV 76 | Mean MCV 81 | Mean MCV 84 | Mean MCV 91 | ||||||||||||
| N | Age interval | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p | Odds ratio | 95% Confidence interval | p | Trend p†† | |
| Males | |||||||||||||||
| 957 | Reference | 1.60 | 0.87–2.92 | 0.13 | 1.75 | 0.94–3.23 | 0.07 | 1.83 | 1.20–2.82 | 0.005 | 0.008 | ||||
| 1431 | 1.29 | 0.97–1.72 | 0.08 | 2.05 | 1.48–2.83 | 2.35 | 1.57–3.51 | ||||||||
| 833 | 1.44 | 1.03–2.01 | 0.03 | 1.43 | 0.97–2.10 | 0.07 | 2.00 | 1.18–3.38 | 0.009 | 0.005 | |||||
| 820 | 1.14 | 0.77–1.66 | 0.51 | 1.63 | 1.10–2.44 | 0.02 | 1.96 | 1.24–3.10 | 0.004 | 0.001 | |||||
| 3635 | 1.07 | 0.85–1.33 | 0.58 | 1.14 | 0.93–1.41 | 0.21 | 1.17 | 0.94–1.45 | 0.17 | 0.27 | |||||
| Females | |||||||||||||||
| 213 | 4.58 | 1.08–19.38 | 0.04 | 1.67 | 0.35–7.84 | 0.65 | 3.09 | 0.87–10.91 | 0.08 | 0.260 | |||||
| 389 | 1.39 | 0.78–2.46 | 0.26 | 1.82 | 0.98–3.36 | 0.06 | 4.02 | 2.03–7.95 | |||||||
| 260 | 0.85 | 0.44–1.69 | 0.66 | 1.18 | 0.59–2.34 | 0.64 | 1.87 | 0.78–4.49 | 0.16 | 0.15 | |||||
| 228 | 0.84 | 0.39–1.81 | 0.66 | 1.08 | 0.51–2.29 | 0.84 | 1.42 | 0.63–3.22 | 0.40 | 0.29 | |||||
| 867 | 1.41 | 0.84–2.37 | 0.19 | 1.34 | 0.82–2.19 | 0.24 | 2.05 | 1.28–3.29 | 0.003 | 0.002 | |||||
* Odds ratios are compared to the referent group with mean MCV of 76.
† Odds ratios adjusted for other independent variables in the table.
†† Model for trend p included categorical mean MCV as a continuous variable.
Among female children compared to the referent group, Q4 is associated with a 4.02 and 2.05 times higher odds of ASD for those
The sensitivity analysis using the first available MCV value and last available MCV for the children demonstrated similar findings as the model with the MCV quartiles, that is, an overall increased odds of ASD with increasing MCV values (Supplementary Table 1). Similarly, the unadjusted odds of ASD when three groups were utilized (low MCV, normal MCV, and high MCV) demonstrated increased odds of ASD in the
Based on previous research demonstrating the detrimental effects of vB12 and folate deficiency on neurodevelopment, we hypothesized that maternal and child MCV, a marker of inadequate vB12 and folate, predicted a later diagnosis of ASD in the child. In unadjusted and adjusted analyses, mean MCV in the mother one year before birth was not associated with a later diagnosis of ASD in their children. In children, there was a broader overall increased odds of ASD, consistent across several statistical models. Compared to the referent group (mean MCV 76 fL), a mean MCV of 81 fL (Q2), 84 fL (Q3), and 91 fL (Q4) was associated with 26%, 38%, and 32% increased odds of ASD; when stratified by sex and age, compared to the referent group, the odds increased in males and females in some age groups.
Folate and vB12 are essential nutrients for myelination during in-utero and post-natal neurologic development [11, 37, 38]. Brain development begins prenatally, whereas central nervous system myelination begins as early as mid-gestation and continues through school age, with the most rapid period of brain growth during the first two years of life [11]. Micronutrients, specifically vB12, are needed to form myelin, the protective covering of nerve cells; brain myelination, which is greatest from mid-gestation to age two, can be affected by vB12 deficiency. Disruptions in myelination slow down nerve conduction, such as in the auditory and visual systems, which can lead to learning and social interaction difficulties. Furthermore, retardation of brain myelination in infancy can lead to delayed acquisition of cognitive skills and brain atrophy leading to regression of skills [11, 39].
Even though studies have demonstrated the potential benefits of prenatal folic acid supplementation to reduce autism risk, a modifiable risk factor for autism [40, 41], the fortification of foods with folic acid beginning in 1998 has not thus far been associated with a population-level decrease in ASD. On the contrary, as mentioned earlier, the incidence of ASD has increased in the post-fortification era. VB12 and folate have a close metabolic relationship in the complex interdependent folate-methylation cycle processes [40, 42]. VB12, along with folate, is an important cofactor for reactions in the folate and methylation cycle; in the methionine synthase reaction, which catalyzes the methylation of homocysteine (HCY) to methionine, and in the demethylation of methyltetrahydrofolate (MTHF) producing tetrahydrofolate (THF) in the one-carbon metabolism [40, 41, 42, 43]. The impairment of the MTHF demethylation in vB12 deficiency leads to a folate trap; that is, MTHF is no longer able to convert to the active form, THF, a transporter of the one-carbon unit to the site of DNA synthesis. In addition, the attenuation of MTHFR enzyme activity due to the 677CT polymorphism, which is strongly associated with ASD [20] and may be associated with severe ASD symptoms [21], further impairs the efficiency of this one-carbon cycle, leading to impaired DNA synthesis and gene expression [40]. Urine samples of children with ASD, showing simultaneous vB12, vitamin B6, and B9 deficiencies, also demonstrated increased concentrations of 5-MTHF, which leads to lower availability of methyl donors, justifying the well-known reduction of protein and DNA methylation reported in children with ASD [44].
In this study, in children, there was an overall increased odds of ASD with increasing MCV values compared to the referent group, and somewhat notable in the younger children. These findings may represent early vB12 levels dropping exponentially during the greatest period of myelination. Newborns who are breastfed by deficient mothers are at risk of developing a vB12 deficiency, usually becoming symptomatic between 4–6 months of life but diagnosed in the later portion of the first year of life [18]. Perhaps these hematologic changes demonstrate the slow depletion of their vB12 as they move into the second year of life. These children, may represent a subset of children born from vB12 deficient mothers leaving the infants with inadequate liver stores from not being adequately supported in utero [45] or breastfeeding and born to either vB12 deficient mothers or replete mothers with the MTHFR polymorphism who cannot keep up the micronutrient levels required after birth during the rapid myelination and growth period immediately after birth and through the first year of life. It is interesting to note that the median age of ASD diagnosis in the children was 3.38 years old, possibly indicating the slowing of neurodevelopment the two years prior.
This study demonstrated an interaction between sex and mean MCV on ASD status. For males with a mean MCV of 91 fL (Q4), we observed increased odds of ASD in all age groups
One would have expected our analysis to also demonstrate MCV changes in the mothers be associated with increased odds of ASD in their children, however, it had been well described that vB12 levels in the low normal range alone don’t exclude functional deficiency [18] and perhaps this also extends to lack of significant hematologic changes. The utility of MCV during pregnancy remains ambiguous. It has been suggested that the increase in MCV during pregnancy is not suggestive of vB12 and/or folate deficiencies but rather a measurement of increased red blood cell production to meet the demands of pregnancy (immature RBCs are larger) [52]. Conversely, a study of women in the first trimester of pregnancy reported that first-trimester folate-vB12 status interactions were associated with plasma methylmalonic acid (MMA) and MCV throughout pregnancy. They found a greater difference in MCV between elevated and non-elevated folate status in those in the top quartile of MMA values compared to those in the lower quartile of MMA values. The same study also reported that women with elevated folate had higher MMA levels and sub-optimal vB12 levels [53]. Perhaps the abnormal MMA range is representative of sub-clinical vB12 deficiency, which is rapidly brought on by the increasing demand for micronutrients during pregnancy [43], with one study reporting higher levels of MMA in the third trimester [54]. Lastly, even though we adjusted for hemoglobin in our analysis, women with macrocytic anemia, coexisting with other deficiencies such as iron deficiency, commonly seen in pregnancy, may have hematological changes caused by vB12 or folate deficiency, however, masked by the hematological changes in iron deficiency (microcytic anemia) [18].
Inconsistent with previous research [55], increased maternal age was associated with statistically significantly decreased odds of having a child with ASD. This finding may be a surrogate for socioeconomic status. In the military, older age may be a representation of higher rank and, therefore, income, which may translate to better access to and compliance with prenatal care. This finding was also similar to the one reported in the primary retrospective matched case-cohort study [16], making it less likely to be an indicator of selection bias due to breaking the match in this secondary analysis. Furthermore, to control for selection bias in the secondary analysis, we controlled for match variables, date of birth, and sex in the models.
Our study had several limitations, which may have restricted our ability to study the utility of the MCV value during pregnancy and in early childhood. First, the stratification of our data resulted in smaller strata across the age groups, which may have over-exaggerated the odds ratios or reduced the power to detect significant associations in the smaller strata. Second, the limited number of labs available may have introduced some sort of information bias. It had been reported that there may be MCV differences throughout pregnancy [53]; however, due to the limited lab values available, we were not able to assess differences across trimesters. If mothers received care in civilian facilities, we did not have access to that laboratory data, and if pregnancy and birth occurred before 2009, laboratory data were not available. Of note, the mothers of children later diagnosed with ASD and children with ASD had a slightly higher mean number of labs, which may be a marker of the mother’s and child’s health status. This may also represent confounding by indication bias; that is, the differences in the mean MCV observed could be attributed to eating preference, restrictive eating patterns, and issues with feeding in infancy that are common for children with ASD. To date, one case of vB12 induced megaloblastic anemia had been reported in a pediatric patient with ASD with a chronically unbalanced diet [56]. Future studies can inform this by assessing the first lab for those under 6 months of age. Lastly, we did not have data on parity or socioeconomic status.
Future studies should assess if the predictive MCV value differs throughout the pregnancy. In addition, assessing pre-pregnancy MCV values can help further understand if a change in the MCV from the mother’s baseline is associated with greater odds of having a child with ASD. Further consideration should be given to studying pregnant women with the MTHFR allele polymorphisms to identify an algorithm for screening women who may be at risk for vB12 or folate abnormalities. This analysis should also be extended to the children. Future studies of children with a larger population are warranted to further delineate any differences in predictive MCV values across the first few years of life. Additionally, consideration should be given to studying children with the MTHFR allele polymorphisms to identify an algorithm for screening children who may be at risk for inadequate levels of vB12 and folate and evaluating MCV in the children during the most significant time of myelination (birth to age 2), as this would also be a period for the greatest need for vB12. Lastly, if future studies also identify that a child’s increase in MCV is associated with increased odds of ASD diagnosis, further investigation of the underlying mechanisms should be explored since research had suggested that children with ASD often have significantly lower MCV levels compared to typically developing children attributed to possible iron deficiency however not all studies agree with this finding [57, 58].
This study reported data that is suggestive of an association between vB12 and folate levels in children, as represented by the association of increasing MCV values within the first few years of life and ASD. There exist promising studies suggesting that the treatment of vB12 at an early age may ameliorate clinical ASD symptoms [59]. If further studies confirm the association between inadequate levels of vB12 and ASD, this may inform public health clinical practice guidelines for vB12 and folate supplementation. Perhaps the MCV, a globally accessible, inexpensive biomarker can be utilized to trigger further evaluation of vB12 or folate deficiencies, to identify a subset of children at risk for ASD or other developmental disorders and lead to early treatment; this exploratory study can inform future larger studies to determine the clinical utility of MCV in early ASD detection, a possible pathway to early intervention to decrease ASD morbidity in the population.
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ÜSF conceptualized and designed the study, carried out the analyses, drafted and revised the manuscript, and critically reviewed the analysis, results, and manuscript for important intellectual content; AIS, CO, EH-G, WY, and AS assisted with the analysis and design of the study and critically reviewed the analyses, results, and manuscript for important intellectual content; WY and AS contributed to data interpretation. AS additionally secured the data.
All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
The Uniformed Services University institutional review board approved this study (Risk Factors and Co-Morbid Conditions, #20-10602).
Not applicable.
This research received no external funding.
The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the Uniformed Services University, the U.S. Air Force, the U.S. Public Health Service Commissioned Corps, the United States Department of Health and Human Services, the U.S. Department of Defense or the U.S. Government. None of the authors have any conflicts of interest to disclose.
Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/IJVNR26726.
References
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