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Original

The Platelet-Lymphocyte Count Ratio as a Biomarker in

Autism Spectrum Disorder

El índice de recuento de plaquetas-linfocitos como

biomarcador en el trastorno del espectro autista

Iris Dany Carmenate Rodriguez1

María de los Ángeles Robinson Agramonte2

Gladys Alejandra Rojas Sànchez3

Vicente Eloy Fardales Macias4

1José Martí Pediatric Hospital of Sancti Spíritus. University of Medical Sciences of Sancti Spíritus. Sancti Spíritus, Cuba

2International Center for Neurological Restoration, Neuroimmunology Department. University of Medical Sciences of

Havana, Havana, Cuba

3 University of Medical Sciences of Sancti Spíritus. Faustino Pérez Hernández Medical Faculty, Department of Psychology.

Sancti Spíritus, Cuba

4University of Medical Sciences of Sancti Spíritus, Faustino Pérez Hernández Medical Faculty. Sancti Spíritus, Cuba

Recibido: 11/07/2025

Aceptado: 20/09/2025

Editores: Rolando Rodríguez Puga

Magdalena Sosa

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Abstract

Introduction: Autism spectrum disorder is a neurodevelopmental disorder with multiple

causes. Research on biomarkers, such as the systemic inflammation index may improve early

intervention.

Objective: Analyze the platelet-lymphocyte count ratio as a biomarker in autism spectrum

disorder.

Methods: A case-control analytical study was conducted at the Pediatric Hospital of Sancti

Spíritus to measure the systemic inflammation index in patients with autism spectrum

disorder, from January to July, 2024. The universe and sample consisted of 30 children

diagnosed with autism spectrum disorder, and 29 neurotypical children, matched by age and

sex. Samples were taken to assess inflammatory indices derived from blood cell counts.

Results: The most significant index was the platelet-lymphocyte ratio. The area under the

curve for the platelet-lymphocyte ratio was 0.717, and the cut-off value was 70. It was found

to provide a sensitivity of 65.5%, a specificity of 67%, a positive predictive value of 70.3%,

a negative predictive value of 67.7%, and an accuracy of 66.6%.

Conclusions: In males, the platelet-lymphocyte count ratio was higher than in females. The

predominant risk factors were maternal infections and chronic diseases. The platelet-

lymphocyte ratio is a key parameter in neuroinflammation, and its study in a larger

population could be relevant as a biomarker of inflammation and a predictor of autism

severity.

Keywords: autism spectrum disorder, systemic inflammation index, neuroinflammatory

markers

Resumen

Introducción: el trastorno del espectro autista es una afección del neurodesarrollo con

múltiples causas. Investigar sobre los biomarcadores, como el índice de inflamación

sistémica, puede mejorar la intervención temprana.

Objetivo: analizar el índice de recuento de plaquetas-linfocitos como biomarcador en el

trastorno del espectro autista.

Métodos: se llevó a cabo un estudio analítico de casos y controles en el Hospital Pediátrico

de Sancti Spíritus, para medir el índice de inflamación sistémica en pacientes con trastorno

del espectro autista, en el periodo de enero a julio de 2024. El universo y la muestra

estuvieron constituidos por 30 niños diagnosticados con trastorno del espectro autista y 29

niños neurotípicos, emparejados por edad y sexo. Se tomaron muestras para evaluar los

índices inflamatorios derivados de los recuentos de células sanguíneas.

Resultados: el índice más significativo fue el relacionado con las plaquetas-linfocitos. El

área bajo la curva para la relación plaqueta-linfocito fue de 0,717 y el valor de corte de 70.

Se encontró que proporcionaba una sensibilidad del 65,5 %, una especificidad del 67 %, un

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valor predictivo positivo del 70,3 %, un valor predictivo negativo del 67,7 %, así como un

valor de precisión del 66,6 %.

Conclusiones: en el sexo masculino el índice de recuento plaqueta-linfocito fue más alto

que en el femenino. Los factores de riesgo predominantes fueron las infecciones maternas y

las enfermedades crónicas. El índice plaqueta-linfocito es clave en la neuroinflamación y su

estudio en mayores poblaciones podría ser relevante como biomarcador de inflamación y

predictor de la gravedad del autismo.

Palabras clave: trastorno del espectro autista, índice de inflamación sistémica, marcadores

neuroinflamatorios

Introduction

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with a multifactorial

etiology. It is characterized by altered brain development due to the influence of multiple

environmental and genetic factors. Synaptic connections are affected from an early age,

leading to poor communication and behavioral disorders in children with genetic

susceptibility.(1,2)

Immune system dysfunction contributes to the development of ASD and is linked to the

neuroinflammation present in neuropsychiatric disorders. Therefore, in recent years, the

scientific community has addressed these connections to establish parameters that contribute

to improving diagnosis, as well as predicting severity and complications.(3)

Until recently, ASD diagnoses were lower than the figures reported today in statistical

sources. It is believed that since its inclusion in classification systems, numerous cases have

been definitively diagnosed; however, the age at which this definition is made exceeds four

years. The prevalence of ASD worldwide reached 15 to 20 cases per 1,000 births. In 2018,

the World Health Organization reported a continued increase estimated at more than one per

160 children.(4)

In Latin America, high figures are reported. Epidemiological data show an ASD prevalence

between 1 and 1.5 %. In Mexico, values reach 0.87%, and in Brazil, it is estimated that 25

out of every 10,000 people suffer from ASD.(5)

In Cuba, there are few studies on the prevalence of ASD, but the incidence rate is known to

be 0.4 per 10,000 inhabitants. In the province of Villa Clara, the rate is 0.335 per 10,000

children, while in Sancti Spíritus, the rate is 0.5 per 10,000 children. This study is consistent

with findings of a similar rate of patients with ASD in other provinces in the country.(6,7,8)

Neuroinflammation has been shown to be responsible for brain tissue damage through several

mechanisms, such as a marked increase in the release of proinflammatory cytokines, which

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could modulate brain function aberrantly. In fact, increased levels of proinflammatory

cytokines (TNF-α and IL-6) have been found in both the blood and brain of autistic patients,

triggering chronic neuroinflammation in autism.(9,10,11)

Other studies show different levels of proinflammatory cytokines in serum, plasma, brain

tissue, and cerebrospinal fluid of autistic subjects compared to normal subjects. This could

affect the immune capacity of the central nervous system (CNS) in children with primary

autism.(10)

Blood mononuclear cell derivatives in the peripheral compartment have been relevant,

including tumor necrosis factor (TNF-α) and IL-1β 3 in neurodevelopmental disruption, as

well as IL-6 and TNF-α. These proinflammatory cytokines are found at high levels in the

brain of autistic patients.(12)

Increased inflammatory activity in children with ASD is demonstrated by an imbalance of

Th1 and Th2 plasma cytokines. Other groups have reported significant differences in IL-1β,

IL-6, IL-17, IL-12p40, and IL-12p70 levels compared to typically developing children, with

specific changes related to comorbidities.(13,14)

Neutrophils, monocytes, and lymphocytes play an important role in the inflammatory

process. In this regard, we propose analyzing the platelet-lymphocyte count ratio as a

biomarker in autism spectrum disorder.

Methods

A case-control analytical study was conducted at the Pediatric Hospital of Sancti Spíritus to

measure the systemic inflammation index in patients with autism spectrum disorder from

January to July, 2024. The selection process began with a group of 50 patients diagnosed in

the province of Sancti Spíritus who did not have any type of infection or were taking

medication at the time of the study.

The sample was selected by simple random sampling from a defined population and

according to exclusion criteria. A numbered list of eligible patients was created using Excel's

random number function, resulting in a group of 30 patients.

The control group consisted of 29 patients, matched by age and sex, who presented

neurotypical development, without immunological, neurological, or psychiatric diseases,

infections, or the use of antibiotics or other medications. A clinical characterization of the

study group was performed beforehand, which included prenatal and perinatal risk factors,

as well as the severity of the disorder, for example: maternal infections, chronic non-

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communicable diseases (NCDs), medication use, cesarean section and high obstetric risk

(HOR).

Eligibility criteria included:

Inclusion criteria

• Patients diagnosed with ASD from the province of Sancti Spíritus.

• Patients who did not have any type of infection, medication use, or decompensation at the

time of the study.

• Patients between the ages of 3 years and 18 years, 11 months, and 29 days.

Exclusion criteria

• Patients who meet the above criteria and whose parents did not provide consent to

participate in the study.

For the selection of controls

• Patients whose age and sex were consistent with those established for the study group.

• Patients without significant personal medical history, such as neurological, endocrine,

immunological, or hematological diseases, infections, or medication use.

• Patients with neurotypical development.

The age groups were established taking into account the aforementioned ages and the

sociodemographic characteristics of the child population in which the disorder occurs. They

were not organized into homogeneous groups because blood values were determined by age

group. Blood cell counts are known to vary by age.

The project was approved by the Scientific Council and the Ethics Committee of the Pediatric

Hospital of Sancti Spíritus (Agreement #: 234/2023). The ethical criteria contained in the

Declaration of Helsinki were met. Parents gave their approval by signing informed consent.

Data confidentiality was guaranteed, and the children received no additional medical

intervention resulting from the study.

Hematological Assessments

Common blood parameters were studied using an automated hematology analyzer (Cobas

c311, Roche). Blood cell counts, including neutrophils, lymphocytes, monocytes,

erythrocytes, and platelets, were measured using standard laboratory methods. The presence

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of inflammation was assessed by analyzing indices derived from blood cell counts, such as:

neutrophil-lymphocyte ratio (NLR; neutrophils/lymphocytes), systemic inflammation index

(SII; platelets x neutrophils/lymphocytes), and platelet-lymphocyte ratio (PLR;

platelets/lymphocytes).

These variables related to inflammation indices were determined using established indices.

First, the absolute neutrophil and lymphocyte counts were determined based on the blood

cell count by multiplying their values by the leukocyte count. The procedures established for

each to calculate the indices were applied, as described in the previous paragraph.

Statistical Analysis

Data analysis was performed using a commercially available software package (Statistical

Version 8). The normality of distribution of each variable in the study groups (autistic and

control subjects) and within the disorder severity groups (mild, moderate, and severe) was

assessed using the Kolmogorov-Smirnov test. Homogeneity of variance was determined

using the Levene test.

For variables that followed a normal distribution, data are presented as mean ± standard

deviation. Comparisons between the autistic and control groups were performed using the

Student t test for independent samples. In cases where homogeneity of variances was not met

(according to the Levene test), the Welch correction was applied to the t test.

Receiver operating characteristic (ROC) curves were used to test the ability of systemic

inflammation indices to differentiate autistic patients with poor or good prognosis for the

development of the disease in question. 95 % confidence intervals (CIs) were calculated for

the areas under the curves. Standard measures of test validity, including sensitivity and

specificity, were also estimated.

Results

The research data were taken from the medical records of patients diagnosed with autism

spectrum disorder (ASD). The patients in this study were 59 individuals, comprised of 29

developing/non-ASD patients and 30 patients diagnosed with ASD.

Table 1 shows the demographic and clinical characteristics and warning signs of subjects

with ASD. In this study, there was a higher prevalence of male subjects in the ASD group

(22/73.3 %) compared to the control group (17/58.6 %). The majority of patients were aged

5 to <10 years, representing 46.6 %, followed by those aged 10 years and older. High obstetric

risk was present in 22 of the mothers, with cesarean delivery being observed frequently (in

17 mothers of children with ASD).

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Table 1. Demographic and clinical characteristics and risk factors in subjects with ASD

Variables

Demographic

Clinical signs

Age

ASD

Control

Severity

3- < 5 ages

6 (20)

8 (27.6)

5- < 10 ages

14 (46.6)

12 (41.4)

Risk factors and severity

10- < 19 ages

10 (33.3)

9 (31.0)

HOR (n= 22)

Sex

Male

22(73.3)

17 (58.6)

Infections (n= 7)

Female

8 (26.7)

22 (41.4)

CNCD (n= 16)

Caesarean (n= 17)

Source: own elaboration

Note: ARO: high obstetric risk; NCDs: chronic non-communicable diseases

Regarding the average neutrophil, lymphocyte, and platelet counts, NLR, PLR, and IIS are

shown in table 2. Analysis of hematological and ratio tests showed that the ASD cohort

showed a significant reduction in platelet counts. Similar levels of all blood cell counts were

observed compared to controls (Table 2). The mean absolute neutrophil, lymphocyte, and

platelet counts of 30 ASD subjects are shown below. The average NLR was 1.24 ± 0.6 x 10

/μL (Fig. 1).

Table 2. Average neutrophil, lymphocyte and platelet counts

Blood cell count

ASD (n=30)

Controls (n=29)

Neutrophils

4.66  1.2

2.81  0.9

 0.01

Lymphocytes

4.12  1.1

3.03  1.0

 0.05

Platelets

243.6  30.4

264.4  98.9

 0.05

Source: own elaboration

Note: Values are given as absolute cell counts (100/μL). Significant differences in neutrophil counts were p=

0.01.

The inflammatory indices analyzed, except for the IPL, did not reach significant differences

in the ASD group compared to the controls (fig. 1).

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Fig. 1. Inflammatory indices based on cell counts in autism spectrum disorder (ASD) and age-matched

control subjects

Source: own elaboration

Note: LPI, platelet-to-lymphocyte ratio; *p significant with Welch's t correction

Following the significant differences observed in LPI in the autism group, inflammatory

indices were analyzed in relation to disease severity using the unpaired t test with Welch's

correction. Significant differences between the ASD-I and ASD-III patient groups are shown

in fig. 2.

Fig. 2. Inflammatory indices based on cell counts in autism spectrum disorder (ASD) severity versus healthy

controls

Source: own elaboration

Note: (B) Severity versus healthy controls. Welch-c, P value, Welch's critical value; LPR, platelet-lymphocyte

ratio

Unpaired t test with Welch's correction. ASD-I: *Statistical significance after Welch's t correction

Diagnostic tests were performed to determine the accuracy of inflammatory ratios as a

biomarker for stratifying ASD patients based on a history of prenatal and perinatal adverse

events. First, the analysis was performed using the area under the curve (AUC) and the

determination of the intercept. The cut-off value was then used to determine the LPR

category. The results can be seen in the 2 x 2 table (table 3, fig. 3).

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Table 3. Platelet-Lymphocyte Ratio

PLR

GOLD STANDARD (HISTORY OF PERINATAL NOXAE)

Positive

Negative

Positive  70

Negative 70

Source: own elaboration

The LPI cut-off was estimated using Welch's correction, yielding a cuto-ff of 0.68 (fig. 3).

This showed good discriminatory ability to determine the positive and negative categories of

the LPI test. The alternative hypothesis follows the criteria indicating that values below the

cut-off are predictors of the development of autism in patients with a history of risk factors

(table 2, fig. 2).

The AUC for the LPI was obtained at 0.717, and the cutoff of 0.68 was found to provide a

sensitivity of 65.5%, a specificity of 67 %, a positive predictive value of 70.3 %, a negative

predictive value of 67.7 %, and an accuracy of 66.6 %.

Fig. 3. ROC curve analysis using IPL to discriminate the risk of developing autism in children with a history

of risk factors

Source: own elaboration

Note: the AUC obtained was 0.717 (p = 0.04). A cut-off value of 0.68 determined using Welch correction is

indicated

Discussion

ASD symptoms typically appear between the ages of 3 and 4. However, they can also emerge

in children between 12 and 24 months (regressive autism). It has also been suggested that the

ratio of males to females with ASD is close to 4:1, attributed to the male hormone

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testosterone, which plays a role in microglial genes and neurotransmitter production in the

brain.(15)

Risk factors are associated with multiple disorders, and even events occurring during

pregnancy are considered relevant for analyzing and understanding disruptive behaviors that

may occur in children. A sociodemographic profile of 126 patients conducted in Ecuador

describes multiple factors of interest in the prenatal stage, including hypertensive disorders,

thyroid disorders, and infections.(16)

There is evidence that maternal infections put this behavior at risk. Once maternal immunity

is activated, a series of inflammatory events occur that cause damage to glial cells and

astrocytes, cells that are important in the nervous system for maintaining optimal

functioning.(17)

Similarly, maternal illnesses, medication use, and other factors may contribute to the

development of the disorder. An integrative review study on ASD describes other events of

interest that occur during the prenatal and perinatal stages, including the use of antiepileptic

medications and prematurity. The latter was not present in the study group.(18)

A high number of cases presented cesarean section as a risk factor, and a review of the

literature shows this relationship. Some epidemiological studies suggest an association

between cesarean delivery and an increased risk of ASD. In a cohort of Swedish children, a

significant association was found between cesarean delivery and ASD, even after adjusting

for confounding factors such as maternal age, socioeconomic status, and family history of

ASD.(19)

Other studies focused on the search for this relationship between cesarean section and ASD

have suggested increasing the number of investigations due to the contradictions reported in

the literature.(20)

Different values in the absolute neutrophil count have been observed in autism compared to

age-matched control subjects. One study reported a mean absolute neutrophil count of 3.88

± 0.24 x 103/μL,(14) while other authors report in their studies that the mean absolute

neutrophil count was 3,450 x 103/μL.(13)

In the present study, the mean absolute neutrophil count in autistic patients was 4.66 ± 1.2 x

103 /μL similar to that observed by Sibel and Cem,(21) while the mean absolute lymphocyte

count (4.12 ± 1.1 x 103/μL) was similar to other previously reported values, although without

a significant difference compared to controls.

The mean NLR and IIS did not reach significant differences in any case. The LLR showed

considerable ability to predict the risk of developing ASD in patients with a history of

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prenatal harmful effects (sensitivity, 65.5 %) and to predict a better prognosis, which means

a negative risk for developing autism (specificity, 67 %).

The authors of this study believe that these results could be related to the small number of

patients studied. Other studies demonstrate changes in these inflammatory indices and have

even found different immune dysfunctions in different groups of patients depending on their

developmental stage.(22,23)

Platelet activation, in response to vascular injury, induces the secretion of several cytokines

and chemokines, which interact with the vascular endothelium to promote the expression of

adhesion molecules and the secretion of cytokines, which in turn induces chemotaxis and

adhesion of neutrophils and monocytes.(24,25) Furthermore, platelets contain serotonin in their

granules, which is absorbed from the plasma through the serotonin transporter (SERT). Once

secreted from their granules, it is capable of producing vasoconstriction and also preventing

apoptosis.(26)

These inflammatory indices have been linked to the prognosis, progression, and severity of

some diseases such as Alzheimer's. The severity of ASD symptoms could also underscore

inflammatory events in the brain; unlike other peripheral indices, the platelet-lymphocyte

ratio (PLR) could be a key parameter for detecting early signs of ASD.(27)

Although the study is based on the hypothesis of the value of the platelet/lymphocyte count

as a biomarker in ASD, the results presented are not definitive, as they must be applied to

broader population groups and related to other clinical characteristics of the disorder, this

being one of the main limitations. The study of markers for this disorder should be expanded,

and in addition to indices of systemic inflammation, the relationship between the immune

and neurological systems should be taken into account, and the search for new

neuroinflammatory markers for ASD should be pursued.

Conclusions

In males, the platelet-lymphocyte count ratio was higher than in females. The predominant

risk factors were maternal infections and chronic diseases. The platelet- lymphocyte ratio is

a key parameter in neuroinflammation, and its study in a larger population could be relevant

as a biomarker of inflammation and a predictor of autism severity.

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Conflicts of interests

Authors declare no conflicts of interests.

Authors’ contribution

Conceptualization: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson

Agramonte.

Formal analysis: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson

Agramonte.

Methodology: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson Agramonte.

Project manager: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson

Agramonte.

Resources: Gladys Alejandra Rojas Valdés

Software: Vicente Eloy Fardales Macías

Supervision: Gladys Alejandra Rojas Valdés

Validation: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson Agramonte.

Original draft: Iris Dany Carmenate Rodríguez, María de los Ángeles Robinson Agramonte.

Writting-revision and edition: Iris Dany Carmenate Rodríguez, María de los Ángeles

Robinson Agramonte, Gladys Alejandra Rojas Valdez.