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Multinutrient Supplementation in Children with ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial

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Title: Multinutrient Supplementation in Children with ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial
Language: English
Authors: Jennifer M. Loftis (ORCID 0000-0003-1773-9365), Hayleigh K. Ast (ORCID 0000-0002-2521-0309), Alisha M. Bruton (ORCID 0000-0002-5929-3149), Priya Srikanth (ORCID 0000-0002-0906-6757), Ramya Ramesh, David W. Erikson (ORCID 0000-0002-3383-9297), Lisa M. Robinette, Irene E. Hatsu (ORCID 0000-0003-0501-9088), Brenda M. Y. Leung, Taryn A. Machingo, L. Eugene Arnold, Jeanette M. Johnstone (ORCID 0000-0003-3947-5540)
Source: Journal of Attention Disorders. 2026 30(6):727-746.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 20
Publication Date: 2026
Sponsoring Agency: National Center for Complementary and Integrative Health (NCCIH) (DHHS/NIH)
National Center for Advancing Translational Sciences (NCATS) (DHHS/NIH)
National Institutes of Health (NIH) (DHHS)
Office of Research and Development (ORD) (VA)
Contract Number: 5R90AT00892403
T32AT002688
Document Type: Journal Articles
Reports - Research
Descriptors: Attention Deficit Hyperactivity Disorder, Children, Nutrition, Symptoms (Individual Disorders), Program Effectiveness, Physiology, Child Health, Intervention
DOI: 10.1177/10870547251397701
ISSN: 1087-0547
1557-1246
Abstract: Objective: While individual nutrients have shown effects on inflammatory mechanisms, the effects of multinutrients (vitamins + minerals, antioxidants, and amino acids) on inflammation are unknown. We investigated whether 8 weeks of multinutrient supplementation, in a randomized controlled trial of 83 children with ADHD, would alter immune factors compared to placebo. Methods: Multiplex technology was used to measure 25 immune factors in blood samples collected at baseline and week 8. Immune factors were compared between multinutrient and placebo groups using the Mann-Whitney test. Linear mixed effects models evaluated immune factor change over time. To understand the functional relevance of the immune factors affected by multinutrient supplementation, pathway analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.7 Bioinformatics Resources. Results: Interleukin (IL)-5 and IL-13 levels differed following multinutrient supplementation versus placebo (p = 0.005 and 0.03, respectively). IL-5 decreased by 1.3% in the multinutrient group (95% CI [-8.6%, 6.7%]) and increased by 17.5% in the placebo group (95% CI [6.9%, 29.2%]). IL-13 decreased by 11.4% in the multinutrient group (95% CI [-18.2%, -4.0%]), compared to a 2.4% increase in the placebo group (95% CI [-7.2%, 13.1%]). When comparing immune factors between treatment responders versus non-responders in the multinutrient group, there was a 4.3% increase in IL-15 in multinutrient responders (95% CI [-6.8%, 16.8%]) and a 14.3% decrease in non-responders (p = 0.03, 95% CI [-24.9%, -2.4%]). Pathway analysis identified T helper type 2 (Th2) signaling pathways affected by multinutrient supplementation, including IL-17 and cytokine-cytokine receptor interaction pathways. Conclusion: Th2 immune factors may be influenced by multinutrient supplementation and associated with behavioral improvements in ADHD.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1504298
Database: ERIC
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  Value: <anid>AN0193250478;gs001jun.26;2026Apr28.02:16;v2.2.500</anid> <title id="AN0193250478-1">Multinutrient Supplementation in Children With ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial </title> <p>Objective: While individual nutrients have shown effects on inflammatory mechanisms, the effects of multinutrients (vitamins + minerals, antioxidants, and amino acids) on inflammation are unknown. We investigated whether 8 weeks of multinutrient supplementation, in a randomized controlled trial of 83 children with ADHD, would alter immune factors compared to placebo. Methods: Multiplex technology was used to measure 25 immune factors in blood samples collected at baseline and week 8. Immune factors were compared between multinutrient and placebo groups using the Mann-Whitney test. Linear mixed effects models evaluated immune factor change over time. To understand the functional relevance of the immune factors affected by multinutrient supplementation, pathway analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.7 Bioinformatics Resources. Results: Interleukin (IL)-5 and IL-13 levels differed following multinutrient supplementation versus placebo (p =.005 and.03, respectively). IL-5 decreased by 1.3% in the multinutrient group (95% CI [−8.6%, 6.7%]) and increased by 17.5% in the placebo group (95% CI [6.9%, 29.2%]). IL-13 decreased by 11.4% in the multinutrient group (95% CI [−18.2%, −4.0%]), compared to a 2.4% increase in the placebo group (95% CI [−7.2%, 13.1%]). When comparing immune factors between treatment responders versus non-responders in the multinutrient group, there was a 4.3% increase in IL-15 in multinutrient responders (95% CI [−6.8%, 16.8%]) and a 14.3% decrease in non-responders (p =.03, 95% CI [−24.9%, −2.4%]). Pathway analysis identified T helper type 2 (Th2) signaling pathways affected by multinutrient supplementation, including IL-17 and cytokine-cytokine receptor interaction pathways. Conclusion: Th2 immune factors may be influenced by multinutrient supplementation and associated with behavioral improvements in ADHD.</p> <p>Keywords: ADHD; cytokines; biomarkers; children; inflammation; multinutrients</p> <p>PHOTO (COLOR): Graphical Abstract</p> <hd id="AN0193250478-2">Introduction</hd> <p>ADHD is a neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity, impulsivity, and its associated feature of emotional dysregulation ([<reflink idref="bib3" id="ref1">3</reflink>]; [<reflink idref="bib45" id="ref2">45</reflink>]; [<reflink idref="bib81" id="ref3">81</reflink>]). A systematic review of the global prevalence of ADHD indicates that the disorder affects 7.6% of children and adolescents ([<reflink idref="bib96" id="ref4">96</reflink>]). The emotional dysregulation associated with ADHD typically begins in childhood and continues to adulthood. Standard medications may treat hallmark ADHD symptoms but are less effective for emotional dysregulation ([<reflink idref="bib114" id="ref5">114</reflink>]) and fail to alter negative outcomes ([<reflink idref="bib60" id="ref6">60</reflink>]). Medication for ADHD, stimulants in particular, are limited by side effects including cardiovascular concerns ([<reflink idref="bib44" id="ref7">44</reflink>]), appetite suppression and reduced growth trajectory ([<reflink idref="bib37" id="ref8">37</reflink>]), and changes in peripheral and central immune responses ([<reflink idref="bib16" id="ref9">16</reflink>]), which may contribute to patient discontinuation ([<reflink idref="bib23" id="ref10">23</reflink>]; [<reflink idref="bib36" id="ref11">36</reflink>]; [<reflink idref="bib69" id="ref12">69</reflink>]).</p> <p>Non-pharmacological supplements are emerging as a promising approach for ADHD and other mental health conditions, showing benefits such as improved emotional regulation, reduced aggression, and better attention in some individuals ([<reflink idref="bib54" id="ref13">54</reflink>], [<reflink idref="bib53" id="ref14">53</reflink>]; [<reflink idref="bib91" id="ref15">91</reflink>]). Three randomized controlled trials (RCTs) have tested the same or similar multinutrient formulas in ADHD – one in adults ([<reflink idref="bib92" id="ref16">92</reflink>]) and two in children ([<reflink idref="bib53" id="ref17">53</reflink>]; [<reflink idref="bib91" id="ref18">91</reflink>]) – all demonstrating greater clinician-rated treatment response with multinutrients versus placebo. In the fully blinded Micronutrients for ADHD in Youth (MADDY) study of children with ADHD and emotional dysregulation (<emph>N</emph> = 126), 54% of those receiving multinutrients were treatment responders compared to 18% on placebo ([<reflink idref="bib53" id="ref19">53</reflink>]), replicating earlier findings ([<reflink idref="bib91" id="ref20">91</reflink>]) using the Clinical Global Impression-Improvement (CGI-I) measure ([<reflink idref="bib31" id="ref21">31</reflink>]; [<reflink idref="bib39" id="ref22">39</reflink>]). Parent reports showed improvements in both groups, but inattention and internalizing symptoms (depression, anxiety) improved more with multinutrients when parents rated target problems ([<reflink idref="bib105" id="ref23">105</reflink>]). Long-term follow-up supports sustained benefit: 84% of initial responders maintained improvement at 1 year without side effects ([<reflink idref="bib93" id="ref24">93</reflink>]), and a 1.5 to 5 year observational study found continued improvement in scores for ADHD, mood, and anxiety, with scores in the "normal," non-clinical range ([<reflink idref="bib90" id="ref25">90</reflink>]). These replicated findings highlight the need to investigate mechanisms underlying multinutrient benefits, including the hypothesized role of cytokines in ADHD ([<reflink idref="bib84" id="ref26">84</reflink>]).</p> <p>There is substantial evidence that inflammatory pathways are dysregulated in many mental health disorders ([<reflink idref="bib61" id="ref27">61</reflink>]; [<reflink idref="bib115" id="ref28">115</reflink>]), including ADHD ([<reflink idref="bib4" id="ref29">4</reflink>]; [<reflink idref="bib26" id="ref30">26</reflink>]; [<reflink idref="bib38" id="ref31">38</reflink>]; [<reflink idref="bib106" id="ref32">106</reflink>]). Further, cross-sectional studies, systematic reviews, and meta-analyses have confirmed that ADHD is associated with inflammatory and immune conditions, such as asthma, allergic rhinitis, conjunctivitis, and atopic dermatitis ([<reflink idref="bib94" id="ref33">94</reflink>]). Dysregulated inflammatory responses are also observed in individuals with intermittent explosive disorder (severe emotional dysregulation), with elevated levels of circulating pro-inflammatory factors in blood (e.g., C-reactive protein [CRP], interleukin [IL]-6, and tumor necrosis factor-alpha [TNF-α]; [<reflink idref="bib22" id="ref34">22</reflink>], [<reflink idref="bib21" id="ref35">21</reflink>]). Thus, inflammatory mechanisms appear to be associated with ADHD pathogenesis and symptomatology; importantly, a better understanding of the inflammatory pathways involved, and a reduction of inflammatory factors may improve ADHD symptoms.</p> <p>Supplementation with single nutrients may result in anti-inflammatory and therapeutic effects for ADHD (e.g., vitamin D; [<reflink idref="bib95" id="ref36">95</reflink>]). However, the effect on circulating levels of inflammatory factors from the combination of multinutrients supplemented in the MADDY study compared to placebo has not been studied. In addition, we explored whether changes in inflammatory cytokine levels are associated with a dichotomous "treatment responder" versus "non-responder" variable in those who received multinutrients.</p> <p>Given the range of anti-inflammatory ingredients in the formula tested and the improvement in behavior seen in two previous child RCTs, we hypothesized that 8 weeks of multinutrient supplementation in children with ADHD would show a reduction in inflammatory factors compared to placebo. To test this initial hypothesis, we examined whether there was a differential change in inflammatory immune factors over the 8-week intervention period between the two treatment groups. We also sought to examine immune factor differences between the responder and non-responder groups to generate hypotheses about possible biological mechanisms underpinning behavioral improvement. To this end, functional enrichment analyses of immune factors were conducted using the Database for Annotation, Visualization, and Integrated Discovery v6.7 (DAVID) Bioinformatics Resources. To identify biological processes and pathways that may be affected by multinutrient supplementation, we analyzed placebo versus multinutrient groups and multinutrient responder versus non-responder groups. Examining immune changes in ADHD may identify the therapeutic interventions' biological mechanisms.</p> <hd id="AN0193250478-3">Methods</hd> <p></p> <hd id="AN0193250478-4">Study Design and Participants</hd> <p>Children participating in this study were from the two United States (U.S.) MADDY sites – a placebo-controlled trial in which participants were initially randomized to either multinutrient or placebo capsules for 8 weeks, followed by an open-label extension of 8 weeks. The MADDY study was approved by two Institutional Review Boards: Oregon Health & Science University, Portland, Oregon, U.S. (#16870; Oregon site) and Ohio State University, Columbus, Ohio, U.S. (#2017H0188; Ohio site); participants at both sites provided blood samples. Parental written consent and child verbal assent were obtained from all participants. The study was prospectively registered with the National Clinical Trials Registry (NCT03252522) and the U.S. Food and Drug Administration (FDA IND#127832). The research was done according to The Code of Ethics of the World Medical Association (Declaration of Helsinki).</p> <p>Details on study rationale, design, and enrollment are reported elsewhere ([<reflink idref="bib55" id="ref37">55</reflink>], [<reflink idref="bib53" id="ref38">53</reflink>]; [<reflink idref="bib65" id="ref39">65</reflink>]). Briefly, unmedicated children aged 6 to 12 years were screened for ADHD and symptoms of emotional dysregulation. Participants met the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for ADHD assessed via the parent-reported Child and Adolescent Symptom Inventory, version 5 (CASI-5), Inattention and Hyperactive/Impulsive subscales ([<reflink idref="bib34" id="ref40">34</reflink>].). Additionally, parents endorsed that their child had at least one impairing symptom of irritability or anger, occurring "often" or "very often," assessed via the Oppositional Defiant Disorder or Disruptive Mood Dysregulation Disorder subscales of the CASI-5.</p> <hd id="AN0193250478-5">Intervention</hd> <p>The intervention was a multinutrient supplement containing 36 ingredients (all known vitamins and essential minerals, plus amino acids and antioxidants; Table 1). Dose was determined by age (up to 9 capsules for children 6–8; up to 12 capsules for children 9–12) and was divided into three daily doses with meals. The placebo contained cellulose fiber and 0.1 mg of vitamin B<subs>2</subs> (riboflavin) per capsule to make the urine fluorescent yellow in both treatment groups to ensure blinding was maintained. Of the 36 ingredients in the active capsules, 7 were above Upper Tolerable Intake Level (UL; copper, manganese, selenium, zinc, vitamin A [retinyl palmitate], vitamin B6 [pyridoxine], and vitamin B9 [folate]), while 2 (magnesium and vitamin B<subs>3</subs> [as niacin]) were above the adult Lowest Observed Adverse Effect Level (LOAEL; [<reflink idref="bib52" id="ref41">52</reflink>]). Treatment adherence was calculated from the number of pills returned at each visit, which were counted by research staff not associated with the study. The adherence calculation considered the number of returned capsules, the number dispensed, the number of days between visits, and the assigned dosage per day.</p> <p>Table 1. Vitamins and Essential Minerals, Besides Amino Acids and Antioxidants, in the Multinutrient Supplement.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Ingredient</th><th align="center">Unit</th><th align="center">1 Cap</th><th align="center">9 Caps</th><th align="center">12 Caps</th><th align="center">RDA<xref ref-type="table-fn" rid="tfn3">a</xref> or AI<xref ref-type="table-fn" rid="tfn4">b</xref></th><th align="center">LOAEL<xref ref-type="table-fn" rid="tfn5">c</xref></th></tr></thead><tbody><tr><td>Vitamin A (as retinyl palmitate)</td><td>IU</td><td>480</td><td>4,320</td><td>5,760</td><td>2,000</td><td>46,667</td></tr><tr><td>Vitamin C (as ascorbic acid)</td><td>mg</td><td>50</td><td>450</td><td>600</td><td>45</td><td>3,000</td></tr><tr><td>Vitamin D (as cholecalciferol)</td><td>IU</td><td>250</td><td>2,250</td><td>3,000</td><td>600</td><td>3,800</td></tr><tr><td>Vitamin E (as d-alpha tocopheryl succinate)</td><td>IU</td><td>30</td><td>270</td><td>360</td><td>16.5</td><td>750</td></tr><tr><td>Vitamin K (as 75% phylloquinone, 25% menaquinone-7)</td><td>mcg</td><td>10</td><td>90</td><td>120</td><td>60</td><td>NE</td></tr><tr><td>Vitamin B1 (as thiamin mononitrate)</td><td>mg</td><td>5</td><td>45</td><td>60</td><td>0.9</td><td>NE</td></tr><tr><td>Vitamin B2 (riboflavin)</td><td>mg</td><td>1.5</td><td>13.5</td><td>18</td><td>0.9</td><td>NE</td></tr><tr><td>Niacin – Vitamin B3 (as niacinamide)</td><td>mg</td><td>7.5</td><td>67.5</td><td>90</td><td>12</td><td>50</td></tr><tr><td>Vitamin B6 (as pyridoxine hydrochloride)</td><td>mg</td><td>5.8</td><td>52.5</td><td>70</td><td>1.0</td><td>500</td></tr><tr><td>Folate – B9 (as calcium L-5 methyltetrahydrofolate)</td><td>mcg</td><td>66.6</td><td>600</td><td>799.9</td><td>300</td><td>5,000</td></tr><tr><td>Vitamin B12 (as 75% adenosylcobalamin, 25% methylcobalamin)</td><td>mcg</td><td>75</td><td>675</td><td>900</td><td>1.8</td><td>NE</td></tr><tr><td>Biotin – Vitamin H</td><td>mcg</td><td>90</td><td>810</td><td>1,080</td><td>20</td><td>NE</td></tr><tr><td>Pantothenic acid (as d-calcium pantothenate)</td><td>mg</td><td>2.5</td><td>22.5</td><td>30</td><td>4</td><td>NE</td></tr><tr><td>Calcium (as NutraTek™ chelation complex)</td><td>mg</td><td>110</td><td>990</td><td>1,320</td><td>1,300</td><td>4,000</td></tr><tr><td>Iron (as NutraTek™ chelation complex)</td><td>mg</td><td>1.15</td><td>10.35</td><td>13.8</td><td>8</td><td>70</td></tr><tr><td>Phosphorus (as NutraTek™ chelation complex)</td><td>mg</td><td>70</td><td>630</td><td>840</td><td>1,250</td><td>10,200</td></tr><tr><td>Iodine (as NutraTek™ chelation complex)</td><td>mcg</td><td>17</td><td>153</td><td>204</td><td>120</td><td>1,700</td></tr><tr><td>Magnesium (as NutraTek™ chelation complex)</td><td>mg</td><td>50</td><td>450</td><td>600</td><td>240</td><td>360</td></tr><tr><td>Zinc (as NutraTek™ chelation complex)</td><td>mg</td><td>4</td><td>36</td><td>48</td><td>8</td><td>60</td></tr><tr><td>Selenium (as NutraTek™ chelation complex)</td><td>mcg</td><td>17</td><td>153</td><td>204</td><td>40</td><td>913</td></tr><tr><td>Copper (as NutraTek™ chelation complex)</td><td>mg</td><td>0.6</td><td>5.4</td><td>7.2</td><td>0.7</td><td>10</td></tr><tr><td>Manganese (as NutraTek™ chelation complex)</td><td>mg</td><td>0.8</td><td>7.2</td><td>9.6</td><td>1.9</td><td>15</td></tr><tr><td>Chromium (as NutraTek™ chelation complex)</td><td>mcg</td><td>52</td><td>468</td><td>624</td><td>25</td><td>NE</td></tr><tr><td>Molybdenum (as NutraTek™ chelation complex)</td><td>mcg</td><td>12</td><td>108</td><td>144</td><td>34</td><td>1,500</td></tr><tr><td>Potassium (as NutraTek™ chelation complex)</td><td>mg</td><td>20</td><td>180</td><td>240</td><td>4,500</td><td>NE</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>. NE = not established. Unit measurements: mg = milligram (<reflink idref="bib1" id="ref42">1</reflink>,000 milligrams = 1 gram); mcg = microgram (<reflink idref="bib1" id="ref43">1</reflink>,000 micrograms = 1 milligram).</p> <ulist> <item>2 DEN Proprietary blend ingredients: Choline bitartrate, Alpha-lipoic acid, Mineral wax (shilajit), Inositol, Acetyl-L-carnitine, Grape seed extract, Ginkgo biloba leaf extract, L-methionine, N-acetyl-L-cysteine, Boron (as NutraTek™ chelation complex), Vanadium (as chelate), Lithium orotate (as chelate), Nickel (as chelate), Gelatin capsule (Bovine derived, 100% BSE-free), Microcrystalline cellulose, Glycine.</item> <item>3 Recommended Daily Allowance</item> <item>4 Adequate Intake.</item> <item>5 Lowest Observed Adverse Effects Level.</item> </ulist> <hd id="AN0193250478-6">Measures</hd> <p>The Clinical Global Impressions (CGI) scale is a validated, clinician-rated tool with subscales that assess severity of illness (CGI-S) and global improvement after an intervention (CGI-I). The CGI-I has seven ratings, ranging from 1 (very much improved) to 7 (very much worse). A "treatment responder" is a participant rated as a CGI-I of 1 (very much improved) or 2 (much improved). Treatment non-responders are rated as 3 (mildly improved), 4 (no change), or 5 to 7 (mildly, much, or very much worse; [<reflink idref="bib18" id="ref44">18</reflink>]). The CGI-I scale was assessed after 8 weeks of supplementation.</p> <p>Fasted venous blood samples were collected in lavender top K2 EDTA tubes (BD, Franklin Lakes, NJ) at baseline and week 8 between 8 and 9 am. Plasma was separated within an hour of collection, frozen, and stored at −80°C until assayed.</p> <hd id="AN0193250478-7">Immune Factor Detection</hd> <p>Plasma cytokine concentrations were measured by the Endocrine Technologies Core at Oregon National Primate Research Center using multiplex assays on a Luminex LX-200 instrument (Luminex, Austin, TX). Twenty-five analytes with a putative role in psychiatric pathology and treatment response were assessed ([<reflink idref="bib4" id="ref45">4</reflink>]; [<reflink idref="bib38" id="ref46">38</reflink>]). The immune factors were measured across two separate panels, one measuring leptin, human growth factor (HGF), and vascular endothelial growth factor-A (VEGF-A; Cancer Multipex Assay, HAGP1MAG-12, MilliporeSigma, Burlington, MA) and one measuring the remaining 22 targets (Immunology Multiplex Assay, HCYTOMAG-60K, MilliporeSigma), following the manufacturer's instructions. We used a single imputation method of detection limit (DL)/√2 to replace measurements with values below the level of detection ([<reflink idref="bib40" id="ref47">40</reflink>]). In addition to sample characteristics, Table 2 also includes a list of the immune factors measured. Supplemental Table 1 provides the limits of detection for each of the factors. Rationale for the immune factor classifications (i.e., pro-or anti-inflammatory) used in this paper is provided in Supplemental Table 2.</p> <p>Table 2. Sample Characteristics and Baseline Immune Factor Levels by Total Sample and Intervention Group in Children with ADHD.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Characteristics</th><th align="center">Total (<italic>N</italic> = 83)</th><th align="center">Multinutrient (<italic>n</italic> = 49)</th><th align="center">Placebo (<italic>n</italic> = 34)</th><th align="center"><italic>p</italic>-value</th></tr></thead><tbody><tr><td>Child's age, years<xref ref-type="table-fn" rid="tfn7">a</xref></td><td>9.8 (1.7)</td><td>9.9 (1.7)</td><td>9.7 (1.6)</td><td>.52</td></tr><tr><td>Child sex<xref ref-type="table-fn" rid="tfn8">b</xref></td><td /><td /><td /><td>.<bold>04</bold></td></tr><tr><td> Male</td><td>59 (71.1%)</td><td>39 (79.6%)</td><td>20 (58.8%)</td><td /></tr><tr><td> Female</td><td>24 (28.9%)</td><td>10 (20.4%)</td><td>14 (41.2%)</td><td /></tr><tr><td>School grade<xref ref-type="table-fn" rid="tfn8">b</xref></td><td /><td /><td /><td>.72</td></tr><tr><td> Grades K-4</td><td>42 (50.6%)</td><td>24 (49.0%)</td><td>18 (52.9%)</td><td /></tr><tr><td> Grades 5–7</td><td>41 (49.4%)</td><td>25 (51.0%)</td><td>16 (47.1%)</td><td /></tr><tr><td>Household income<xref ref-type="table-fn" rid="tfn9">c</xref></td><td /><td /><td /><td>.44</td></tr><tr><td> ≤15K</td><td>2 (2.4%)</td><td>2 (4.1%)</td><td>0 (0.0%)</td><td /></tr><tr><td> >15K–≤30K</td><td>5 (6.0%)</td><td>3 (6.1%)</td><td>2 (5.9%)</td><td /></tr><tr><td> >30K–≤60K</td><td>13 (15.7%)</td><td>6 (12.2%)</td><td>7 (20.6%)</td><td /></tr><tr><td> >60K–≤80K</td><td>10 (12.0%)</td><td>8 (16.3%)</td><td>2 (5.9%)</td><td /></tr><tr><td> >80K</td><td>53 (63.9%)</td><td>30 (61.2%)</td><td>23 (67.6%)</td><td /></tr><tr><td>Marital status<xref ref-type="table-fn" rid="tfn9">c</xref></td><td /><td /><td /><td>1.00</td></tr><tr><td> Married</td><td>67 (80.7%)</td><td>39 (79.6%)</td><td>28 (82.4%)</td><td /></tr><tr><td> Divorced</td><td>10 (12.0%)</td><td>6 (12.2%)</td><td>4 (11.8%)</td><td /></tr><tr><td> Single</td><td>6 (7.2%)</td><td>4 (8.2%)</td><td>2 (5.9%)</td><td /></tr><tr><td>Parent education<xref ref-type="table-fn" rid="tfn9">c</xref></td><td /><td /><td /><td>.96</td></tr><tr><td> High school</td><td>6 (7.2%)</td><td>4 (8.2%)</td><td>2 (5.9%)</td><td /></tr><tr><td> Technical/professional college</td><td>16 (19.3%)</td><td>10 (20.4%)</td><td>6 (17.6%)</td><td /></tr><tr><td> University or higher</td><td>60 (72.3%)</td><td>34 (69.4%)</td><td>26 (76.5%)</td><td /></tr><tr><td> Other</td><td>1 (1.2%)</td><td>1 (2.0%)</td><td>0 (0.0%)</td><td /></tr><tr><td>Immune factor, pg/ml<xref ref-type="table-fn" rid="tfn10">d</xref></td><td /><td /><td /><td /></tr><tr><td>Eotaxin</td><td><bold>72.3 (56.8-90.5)</bold></td><td><bold>77.2 (61.6-93.0)</bold></td><td><bold>67.6 (51.6-86.3)</bold></td><td>.<bold>09</bold></td></tr><tr><td>G-CSF</td><td>16.8 (11.3-29.4)</td><td>16.6 (11.3-28.9)</td><td>20.6 (11.3-29.4)</td><td>.42</td></tr><tr><td>HGF</td><td>133.5 (101.0-169.7)</td><td>128.6 (101.0-196.1)</td><td>133.5 (101.0-152.8)</td><td>.63</td></tr><tr><td>IFN-γ</td><td>17.1 (7.4-35.3)</td><td>16.6 (7.1-36.0)</td><td>17.7 (9.4-34.8)</td><td>.82</td></tr><tr><td>IL-1α</td><td>44.4 (8.4-221.7)</td><td>28.8 (7.7-148.7)</td><td>76.6 (9.8-370.8)</td><td>.21</td></tr><tr><td>IL-1β</td><td>2.1 (0.9-6.0)</td><td>1.9 (1.0-5.4)</td><td>2.3 (0.9-6.0)</td><td>.59</td></tr><tr><td>IL-1RA</td><td>21.6 (14.7-33.8)</td><td>21.6 (14.4-34.6)</td><td>21.4 (15.7-29.6)</td><td>.82</td></tr><tr><td>IL-2<xref ref-type="table-fn" rid="tfn10">e</xref></td><td>2.3 (2.3-2.3)</td><td>2.3 (2.3-2.3)</td><td>2.3 (2.3-2.3)</td><td>.58</td></tr><tr><td>IL-4</td><td>126.6 (11.3-993.6)</td><td>73.0 (11.3-633.6)</td><td>353.0 (11.3-1,555.0)</td><td>.16</td></tr><tr><td>IL-5</td><td>6.8 (2.3-20.7)</td><td>6.6 (2.3-11.7)</td><td>8.3 (2.3-39.1)</td><td>.29</td></tr><tr><td>IL-6</td><td>28.4 (3.9-98.4)</td><td>16.6 (3.9-59.3)</td><td>42.9 (4.3-129.2)</td><td>.21</td></tr><tr><td>IL-8</td><td>24.3 (6.7-78.7)</td><td>16.5 (7.1-56.1)</td><td>39.8 (6.2-132.7)</td><td>.29</td></tr><tr><td>IL-10</td><td>8.2 (4.5-28.4)</td><td>7.5 (4.8-15.2)</td><td>12.2 (4.3-44.6)</td><td>.38</td></tr><tr><td>IL-12p70</td><td>5.1 (3.3-7.0)</td><td>5.1 (3.8-6.9)</td><td>4.7 (3.3-7.0)</td><td>.61</td></tr><tr><td>IL-13</td><td>38.4 (6.8-146.2)</td><td>28.5 (6.9-89.7)</td><td>54.8 (6.1-198.7)</td><td>.41</td></tr><tr><td>IL-15</td><td>8.0 (5.2-15.7)</td><td>7.7 (5.5-14.7)</td><td>11.8 (4.2-17.3)</td><td>1.00</td></tr><tr><td>IL-17A</td><td>4.1 (2.3-8.0)</td><td>4.1 (2.3-8.0)</td><td>4.2 (2.3-7.5)</td><td>.98</td></tr><tr><td>IP-10</td><td>357.9 (301.7-458.6)</td><td>354.5 (282.7-458.6)</td><td>359.3 (301.9-451.4)</td><td>.81</td></tr><tr><td>Leptin</td><td>6,198.0 (2,813.3-15,672.0)</td><td>6,858.0 (2,946.6-17,526.0)</td><td>5,286.0 (2,758.3-9,834.0)</td><td>.48</td></tr><tr><td>MCP-1</td><td>216.0 (184.9-268.4)</td><td>228.0 (192.0-268.4)</td><td>209.1 (173.4-267.4)</td><td>.19</td></tr><tr><td>MDC</td><td><bold>696.7 (579.1-855.9)</bold></td><td><bold>716.9 (637.8-912.6)</bold></td><td><bold>629.4 (536.9-793.7)</bold></td><td>.<bold>03</bold></td></tr><tr><td>MIP-1α<xref ref-type="table-fn" rid="tfn10">e</xref></td><td>11.3 (2.3-11.3)</td><td>11.3 (4.5-11.3)</td><td>11.3 (2.3-11.3)</td><td>.59</td></tr><tr><td>MIP-1β</td><td>18.5 (12.5-25.1)</td><td>18.9 (15.2-25.1)</td><td>17.8 (11.3-25.1)</td><td>.21</td></tr><tr><td>TNF-α</td><td>17.9 (14.6-21.8)</td><td>18.4 (14.5-22.9)</td><td>16.3 (15.3-20.3)</td><td>.44</td></tr><tr><td>VEGF-A</td><td>79.7 (29.0-129.4)</td><td>72.9 (41.4-127.2)</td><td>89.5 (29.0-129.4)</td><td>.88</td></tr></tbody></table> </ephtml> </p> <ulist> <item>6 <emph>Note</emph>. K = thousand. pg/ml = picogram per milliliter; G-CSF = granulocyte-colony stimulating factor; HGF = hepatocyte growth factor; IFN = interferon; IL = interleukin; MIP = monocyte chemoattractant protein; MCP = macrophage derived chemokine; MIP = macrophage inflammatory protein; RA = receptor antagonist; TNF = tumor necrosis factor; VEGF = vascular endothelial growth factor.</item> <item>7 Two-sample <emph>t</emph>-test, mean (standard deviation).</item> <item>8 chi-square test.</item> <item>9 Fisher's exact test.</item> <item>10 Mann-Whitney test, median (interquartile range (IQR)); analyses with <emph>p</emph>-values <.15 are in bold; <sups>e</sups>The majority of values were below detection limit; these factors were excluded from models examining change over time. Grade K, kindergarten/first year of school.</item> </ulist> <hd id="AN0193250478-8">Statistical Analysis</hd> <p></p> <hd id="AN0193250478-9">Descriptive Analysis</hd> <p>We used two-sample <emph>t</emph>-tests to compare continuous variables and chi-square tests or Fisher's exact tests (if expected counts were <5) to compare categorical variables at baseline between the multinutrient and placebo groups. We compared median immune factor levels at baseline between multinutrient and placebo groups using the Mann-Whitney test. We also compared median baseline immune factor levels for all responders and non-responders, regardless of group allocation, and among responders and non-responders who received the multinutrient supplement. All analyses were conducted in [<reflink idref="bib102" id="ref48">102</reflink>], v16. Statistical significance or Type I error was set at.05 without correction for multiple testing in these exploratory analyses ([<reflink idref="bib35" id="ref49">35</reflink>]; [<reflink idref="bib79" id="ref50">79</reflink>]). To flag analytes of interest for the exploratory biological pathway analysis only, we used a higher threshold of 0.15 ([<reflink idref="bib35" id="ref51">35</reflink>]; [<reflink idref="bib89" id="ref52">89</reflink>]).</p> <hd id="AN0193250478-10">Immune Factor Change Over Time Between Multinutrient and Placebo Groups</hd> <p>We used natural log-transformed immune factors since most cytokines had a right-skewed distribution. For our base model, we used a linear mixed-effects model with the log-transformed immune factors as the outcome, a random effect for subject, an indicator for site, and an interaction between time and treatment group to quantify change between baseline and week 8 and compare the change between the multinutrient and placebo groups after adjusting for site. We also added sex as a covariate to examine if adjustment for sex changed estimates from the base model ([<reflink idref="bib5" id="ref53">5</reflink>]; [<reflink idref="bib17" id="ref54">17</reflink>]). We report mean site-adjusted within-group percent change and 95% confidence intervals (CIs) in the geometric mean between baseline and week 8 for each randomized group and the corresponding <emph>p</emph>-values for between-group change (comparing within-group change between multinutrient and placebo groups).</p> <hd id="AN0193250478-11">Immune Factor Change Over Time Between Multinutrient Responder and Non-responder Groups</hd> <p>To compare immune-factor change over time between multinutrient responder and non-responder groups, for our base model we used a linear mixed effects model with log-transformed immune factor as the outcome adjusted for site and a random effect for subject to quantify change in immune factor levels between week 8 and baseline. We also added sex as a covariate to examine if adjustment for sex changed estimates from the base model. We report mean site-adjusted within-group percent change and 95% CI in the geometric mean between baseline and week 8 for the multinutrient responder group, multinutrient non-responder group, and corresponding <emph>p</emph>-values for the between-group change.</p> <hd id="AN0193250478-12">Sensitivity Analyses</hd> <p>We compared median immune factor concentrations at week 8 between the multinutrient and placebo groups using a Mann-Whitney test. There were three parts to the model-based sensitivity analyses. The first part was to examine whether there were site-specific differences using a linear mixed-effects model with the log-transformed immune factor as the outcome, a random effect for subject, and a three-way interaction of time, treatment group, and site. We examined change in immune factor concentrations between multinutrient and placebo groups, stratified by site. The second part was to use a change-score model where we calculated subject-level percent change in immune factor by taking the difference between week 8 and baseline levels and dividing it by the baseline levels. We then fit a linear regression model with the percent change in immune factor level as the outcome with covariates of treatment group and site. We fit this change-score model, both adjusting for site and stratifying by site to examine if site-specific differences were evident within a change-score model (Supplemental Table 3). The third part of the sensitivity analysis was to examine change over time in immune factor levels between all responders and non-responders from the multinutrient and placebo groups, after adjusting for randomization group and site (Supplemental Table 4).</p> <hd id="AN0193250478-13">Exploratory Bioinformatics Pathway Analysis</hd> <p>Functional analysis of the data was performed using the Database for Annotation, Visualization, and Integrated Discovery v6.7 (DAVID) Bioinformatics Resources (http://david.abcc.ncifcrf.gov/home.jsp; [<reflink idref="bib46" id="ref55">46</reflink>], [<reflink idref="bib47" id="ref56">47</reflink>]), with minor modifications from published studies ([<reflink idref="bib48" id="ref57">48</reflink>]; [<reflink idref="bib113" id="ref58">113</reflink>]). Immune factors reaching the threshold of interest for the biological pathway analysis flagged as possibly differentially changed over time (<emph>p</emph> <.15) between the multinutrient and placebo groups, and between the multinutrient responder and multinutrient non-responder groups, were assessed for enrichment of biological processes using the terms of the fifth level of Gene Ontology (GO). The name of each factor was converted to an analyzable identifier via Universal Protein Resource (UniProt) and then entered in the DAVID functional annotation tool. Pathway analysis was carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) module within DAVID. Statistical analysis for GO and pathway analyses were done using a modified Fisher Exact Test (Expression Analysis Systematic Explorer [EASE]).</p> <hd id="AN0193250478-14">Results</hd> <p></p> <hd id="AN0193250478-15">Group Characteristics and Baseline Immune Factor Data</hd> <p>Table 2 summarizes the group characteristics and baseline immune factor data. Our analytic sample size was 83 participants, <emph>n</emph> = 49 (59% multinutrients) and <emph>n</emph> = 34 (41% placebo), reflecting the 3:2 active to placebo randomization ratio. There was a higher proportion of males in the multinutrient group (79.6%, <emph>n</emph> = 39) compared to the placebo group (58.8%, <emph>n</emph> = 20; <emph>p</emph> =.04). There were no significant differences in other demographic variables between the two groups. For macrophage inflammatory protein (MIP-1α), 89% of samples were below detection limit (DL) at baseline and 92% at week 8. For IL-2, 87% of samples were below DL at baseline and 83% at week 8. Hence, both were excluded from the models.</p> <p>Baseline median macrophage-derived chemokine (MDC) and eotaxin levels were higher in the multinutrient group (716.9 and 77.2 pg/ml, respectively) compared to the placebo group (629.4 and 67.6 pg/ml, respectively; <emph>p</emph> =.03 and.09, respectively). All other immune factors had similar baseline values for the two groups (all <emph>p</emph> >.15; Table 2).</p> <hd id="AN0193250478-16">Immune Factor Change Over Time Between Multinutrient and Placebo Groups</hd> <p>Changes over time in concentrations of IL-5 and IL-13 differed significantly between multinutrients and placebo. IL-5, considered a pro-inflammatory cytokine, decreased by 1.27% (95% CI [−8.60, 6.66]) in the multinutrient group, but increased 17.5% (95% CI [6.87, 29.22]) in the placebo group (<emph>p</emph> =.005). IL-13, an anti-inflammatory cytokine, decreased by 11.4% (95% CI [−18.17, −3.96]) in the multinutrient group and increased 2.4% (95% CI [−7.17, 13.05]) in the placebo group (<emph>p</emph> =.03; Table 3, Figure 1). Adding sex as a covariate did not change these results (<emph>not shown</emph>). Taken together, these results underscore a pattern of both pro-and anti-inflammatory cytokines decreasing in participants on multinutrients and increasing on placebo.</p> <p>Table 3. Percent Change in Immune Factor Levels by Treatment Groups in Children with ADHD, Adjusted for Site.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Immune factor<xref ref-type="table-fn" rid="tfn12">a</xref></th><th align="center">Multinutrient (<italic>n</italic> = 49)</th><th align="center">Placebo (<italic>n</italic> = 34)</th><th align="center"><italic>p</italic>-value of difference</th></tr></thead><tbody><tr><td>Eotaxin</td><td>−7.81 (−15.84, 0.99)</td><td>−4.61 (−14.62, 6.57)</td><td>.64</td></tr><tr><td>G-CSF</td><td>−2.57 (−18.77, 16.86)</td><td>11.89 (−10.28, 39.55)</td><td>.34</td></tr><tr><td>HGF</td><td>−6.29 (−16.08, 4.64)</td><td>4.48 (−8.64, 19.48)</td><td>.22</td></tr><tr><td>IFN-γ</td><td>−9.73 (−22.69, 5.4)</td><td>−4.19 (−20.77, 15.87)</td><td>.63</td></tr><tr><td>IL-1α</td><td>−9.82 (−19.72, 1.3)</td><td>0.8 (−12.64, 16.3)</td><td>.23</td></tr><tr><td>IL-1β</td><td>−7.95 (−21.01, 7.26)</td><td>2.34 (−15.17, 23.45)</td><td>.39</td></tr><tr><td>IL-1RA</td><td>1.43 (−11.2, 15.86)</td><td>4.09 (−11.53, 22.47)</td><td>.81</td></tr><tr><td><bold>IL-4</bold></td><td><bold>−5.39 (−13.28, 3.21)</bold></td><td><bold>6.35 (−4.45, 18.38)</bold></td><td>.<bold>10</bold></td></tr><tr><td><bold>IL-5</bold></td><td><bold>−1.27 (−8.60, 6.66)</bold></td><td><bold>17.52 (6.87, 29.22)</bold></td><td>.<bold>005</bold></td></tr><tr><td><bold>IL-6</bold></td><td><bold>−8.18 (−15.88, 0.23)</bold></td><td><bold>2.90 (−7.62, 14.62)</bold></td><td>.<bold>11</bold></td></tr><tr><td>IL-8</td><td>−9.20 (−15.99, −1.86)</td><td>−3.16 (−12, 6.57)</td><td>.30</td></tr><tr><td>IL-10</td><td>4.53 (−4.29, 14.18)</td><td>1.92 (−8.56, 13.61)</td><td>.72</td></tr><tr><td>IL-12p70</td><td>−1.66 (−14.28, 12.82)</td><td>6.01 (−10.37, 25.38)</td><td>.50</td></tr><tr><td><bold>IL-13</bold></td><td><bold>−11.35 (−18.17, −3.96)</bold></td><td><bold>2.44 (−7.17, 13.05)</bold></td><td>.<bold>03</bold></td></tr><tr><td>IL-15</td><td>−4.10 (−12.46, 5.06)</td><td>3.92 (−7.10, 16.25)</td><td>.28</td></tr><tr><td>IL-17A</td><td>−7.83 (−21.15, 7.74)</td><td>−3.60 (−20.34, 16.65)</td><td>.72</td></tr><tr><td>IP-10</td><td>−0.02 (−10.28, 11.41)</td><td>7.31 (−5.91, 22.38)</td><td>.42</td></tr><tr><td>Leptin</td><td>−2.82 (−19.71, 17.62)</td><td>16.00 (−8.18, 46.55)</td><td>.25</td></tr><tr><td>MCP-1</td><td>−7.9 (−14.79, −0.45)</td><td>−5.75 (−14.29, 3.63)</td><td>.71</td></tr><tr><td>MDC</td><td>−1.38 (−8.63, 6.43)</td><td>0.47 (−8.44, 10.25)</td><td>.76</td></tr><tr><td>MIP-1β</td><td>1.85 (−10.51, 15.92)</td><td>−5.85% (−19.54, 10.17)</td><td>.45</td></tr><tr><td>TNF-α</td><td>3.72 (−2.57, 10.42)</td><td>−0.84(−8.13, 7.02)</td><td>.37</td></tr><tr><td>VEGF-A</td><td>6.48 (−8.92, 24.48)</td><td>−2.70 (−19.59, 17.75)</td><td>.47</td></tr></tbody></table> </ephtml> </p> <ulist> <item>11 <emph>Note</emph>. pg/ml = picograms per milliliter; G-CSF = granulocyte-colony stimulating factor; HGF = hepatocyte growth factor. IFN = interferon; IL = interleukin; MCP = monocyte chemoattractant protein; MDC = macrophage derived chemokine; MIP = macrophage inflammatory protein; RA = receptor antagonist; TNF = tumor necrosis factor; VEGF = vascular endothelial growth factor.</item> <item>12 % change (95% CI); analyses with <emph>p</emph>-values <.15 are in bold.</item> </ulist> <p>Graph: Figure 1. Visual representation of mean % change (with 95% CI) in immune factor levels between multinutrient and placebo groups in children with ADHD. Immune factors that were significantly different (p <.05) and those that reached the threshold of interest for the pathway analysis (p <.15) are shown. Note. MN = multinutrient.</p> <hd id="AN0193250478-17">Immune Factor Changes Over Time Between Multinutrient Responder and Multinutrient Non-respond...</hd> <p>One participant was missing treatment responder status (CGI-I), so our analytic sample size was 28 multinutrient responders and 20 multinutrient non-responders. The pro-inflammatory cytokine IL-15 increased by 4.3% (95% CI [−6.83, 16.77]) in the multinutrient responder group but decreased 14.3% (95% CI [−24.86, −2.36]) in the non-responder group (<emph>p</emph> =.03). Additional patterns of change were observed for several other immune factors that were flagged for inclusion in the pathway analysis (<emph>p-</emph>values between.05 and.15): pro-inflammatory factors interferon (IFN)-γ, leptin, and VEGF-A and anti-inflammatory cytokine IL-1RA all increased in the multinutrient responder group and decreased in the non-responder group, while levels of IL-6 decreased in both groups. The decrease was larger for the multinutrient non-responder group (see Table 4 for 95% CIs and <emph>p</emph>-values; Supplemental Figure 1, <emph>see Discussion section for interpretation of these findings</emph>). Adding sex as a covariate did not change these results (<emph>not shown</emph>).</p> <p>Table 4. Percent Change and 95% CI in Immune Factor Levels by Multinutrient Responder and Multinutrient Non-responder Groups in Children with ADHD, Adjusted for Site.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Immune factor<xref ref-type="table-fn" rid="tfn14">a</xref></th><th align="center">Multinutrient responder (<italic>n</italic> = 28<xref ref-type="table-fn" rid="tfn15">b</xref>)</th><th align="center">Multinutrient non-responder (<italic>n</italic> = 20)</th><th align="center"><italic>p</italic>-value of difference</th></tr></thead><tbody><tr><td>Eotaxin</td><td>−3.19 (−14.62, 9.76)</td><td>−13.72 (−25.35, −0.27)</td><td>.24</td></tr><tr><td>G-CSF</td><td>1.96 (−21.11, 31.77)</td><td>−8.22 (−31.71, 23.37)</td><td>.60</td></tr><tr><td>HGF</td><td>−0.21 (−14.41, 16.34)</td><td>−13.71 (−27.73, 3.04)</td><td>.22</td></tr><tr><td><bold>IFN-γ</bold></td><td><bold>1.24 (−17.72, 24.57)</bold></td><td><bold>−22.87 (−39.36, −1.89)</bold></td><td>.<bold>09</bold></td></tr><tr><td>IL-1α</td><td>−8.96 (−21.21, 5.18)</td><td>−10.97 (−24.72, 5.29)</td><td>.84</td></tr><tr><td>IL-1β</td><td>−1.26 (−20.35, 22.40)</td><td>−15.99 (−34.51, 7.76)</td><td>.33</td></tr><tr><td><bold>IL-1RA</bold></td><td><bold>11.69 (−7.17, 34.38)</bold></td><td><bold>−10.43 (−27.69, 10.95)</bold></td><td>.<bold>12</bold></td></tr><tr><td>IL-4</td><td>−3.60 (−15.60, 10.10)</td><td>−7.63 (−20.84, 7.80)</td><td>.68</td></tr><tr><td>IL-5</td><td>2.53 (−8.02, 14.29)</td><td>−6.11 (−17.23, 6.51)</td><td>.30</td></tr><tr><td><bold>IL-6</bold></td><td><bold>−2.62 (−13.52, 9.65)</bold></td><td><bold>−15.14 (−26.07, −2.60)</bold></td><td>.<bold>14</bold></td></tr><tr><td>IL-8</td><td>−7.40 (−16.35, 2.50)</td><td>−11.52 (−21.37, −0.44</td><td>.56</td></tr><tr><td>IL-10</td><td>7.55 (−5.92, 22.95)</td><td>0.78 (−13.72, 17.72)</td><td>.53</td></tr><tr><td>IL-12p70</td><td>3.21 (−15.43, 25.97)</td><td>−7.68 (−26.67, 16.22)</td><td>.47</td></tr><tr><td>IL-13</td><td>−11.68 (−20.78, −1.54)</td><td>−10.88 (−21.45, 1.12)</td><td>.91</td></tr><tr><td><bold>IL-15</bold></td><td><bold>4.31 (−6.83, 16.77)</bold></td><td><bold>−14.34 (−24.86, −2.36)</bold></td><td>.<bold>03</bold></td></tr><tr><td>IL-17A</td><td>−3.64 (−20.63, 16.99)</td><td>−13.16 (−30.64, 8.72)</td><td>.49</td></tr><tr><td>IP-10</td><td>2.07 (−9.18, 14.71)</td><td>−2.17 (−14.51, 11.95)</td><td>.64</td></tr><tr><td><bold>Leptin</bold></td><td><bold>10.47 (−13.37, 40.86)</bold></td><td><bold>−18.11 (−38.22, 8.54)</bold></td><td>.<bold>11</bold></td></tr><tr><td>MCP-1</td><td>−3.60 (−12.89, 6.69)</td><td>−13.72 (−23.26, −3.00)</td><td>.16</td></tr><tr><td>MDC</td><td>2.66 (−7.96, 14.50)</td><td>−6.82 (−17.86, 5.71)</td><td>.26</td></tr><tr><td>MIP-1®</td><td>4.36 (−12.67, 24.71)</td><td>−1.5 (−19.76, 20.97)</td><td>.68</td></tr><tr><td>TNF-α</td><td>6.32 (−1.17, 14.38)</td><td>0.57 (−7.58, 9.44)</td><td>.33</td></tr><tr><td><bold>VEGF-A</bold></td><td><bold>20.49 (−4.96, 52.76)</bold></td><td><bold>−9.36 (−31.11, 19.24)</bold></td><td>.<bold>12</bold></td></tr></tbody></table> </ephtml> </p> <ulist> <item>13 <emph>Note</emph>. G-CSF = granulocyte-colony stimulating factor; HGF = hepatocyte growth factor; IFN = interferon; IL = interleukin; MIP = monocyte chemoattractant protein; MCP = macrophage derived chemokine; MIP = macrophage inflammatory protein; RA = receptor antagonist; TNF = tumor necrosis factor; VEGF = vascular endothelial growth factor.</item> <item>14 % change (95% CI); analyses with <emph>p</emph>-values <.15 are in bold.</item> <item>15 One missing treatment responder status.</item> </ulist> <hd id="AN0193250478-18">Sensitivity Analyses</hd> <p>Examining median immune factor levels at week 8 between multinutrient and placebo groups, the only significant difference detected was for MDC, with the multinutrient group having higher median macrophage-derived chemokine (MDC) levels compared to placebo (<emph>p</emph> =.04; Supplemental Table 1). Because one participant was missing immune marker concentrations at week 8, the analytic sample size was 82 participants: 48 (59%) in the multinutrient group, and 34 (41%) in the placebo group. The first part of the model-based sensitivity analyses detected a greater number of immune factors that decreased over time in the Ohio multinutrient group compared to the Oregon multinutrient group, including pro-inflammatory factors eotaxin, IFN-γ, IL-1α, IL-6, and IL-17A and anti-inflammatory factors HGF and IL-13. For example, IL-6 decreased by 13.9% at the Ohio site (95% CI [−23.94, −2.52], <emph>p</emph> =.02) compared to a 2.4% decrease at the Oregon site (95% CI [−13.5, 10.3], <emph>p</emph> =.92). In addition, IFN-γ decreased by 19.9% in the multinutrient group at the Ohio site (95% CI [−35.02, −1.20], p =.01) and increased by 1.3% in the multinutrient group at the Oregon site (95% CI [−17.48, 24.30], p =.07; Supplemental Table 3).</p> <p>For the second part of the sensitivity analyses, associations were stronger with the linear mixed effects model compared to a change-score model (<emph>results not shown</emph>). For the third part, although there was a pattern of decreasing levels of pro-inflammatory cytokines between baseline and week 8 among all non-responders compared to all responders, the associations were stronger when comparing just the multinutrient non-responders and multinutrient responders (Supplemental Table 4).</p> <hd id="AN0193250478-19">Exploratory Bioinformatics Pathway Analysis</hd> <p>We analyzed the immune factors that showed a differential pattern of change over time (<emph>p</emph> <.15) between the multinutrient and placebo groups (Table 3) and between the multinutrient responder and multinutrient non-responder groups (Table 4) for enrichment of biological processes (i.e., processes that were over-represented in the list of immune factors). In doing so, five functional pathways were identified that incorporated all four of the immune factors that showed a signal of change over time between multinutrient and placebo groups (IL-4, IL-5, IL-6, IL-13). These pathways included <emph>inflammatory bowel disease</emph> (<emph>p</emph> = 4.1 × 10<sups>−7</sups>); <emph>IL-17 signaling pathway</emph> (<emph>p</emph> = 1.2 × 10<sups>−6</sups>); <emph>Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway</emph> (<emph>p</emph> = 7.0 × 10<sups>−6</sups>); <emph>cytokine-cytokine receptor interaction</emph> (<emph>p</emph> = 4.0 × 10<sups>−5</sups>); and <emph>pathways in cancer</emph> (<emph>p</emph> = 2.3 × 10<sups>−4</sups>). Figure 2 summarizes the functional roles of the immune factors and key pathways identified, while Figure 3 highlights the specific cytokine-cytokine receptor interaction pathways, which are important in deciphering how signaling molecules coordinate immune responses.</p> <p>Graph: Figure 2. Functional pathway analysis. Common pathways of Th2 cytokines IL-4, IL-5, IL-6, and IL-13 that were found to have a significantly greater reduction in the multinutrient group versus the placebo group. IL-4 plays a large part in B cell activation, mast cell release, and induces monocytes to differentiate into dendrites and ultimately macrophages. IL-5 stimulates eosinophil growth and differentiation. IL-6 activates the HPA-axis, promotes B- and T-cell growth and regulates neuron development by stimulating differentiation of stem cells. IL-13 inhibits macrophage inflammatory cytokine production, and B-cell growth and development.</p> <p>Graph: Figure 3. Enlarged images of cytokine-cytokine receptor interaction pathways that differentially changed over time between the multinutrient and placebo groups. Note : for cytokines interacting with multiple receptors and receptor subtypes, only a single receptor is shown with the names of the receptors listed. Note. IL-4R = interleukin-4 receptor; IL-2RG = interleukin-2 receptor subunit gamma; IL-6R = interleukin-6 receptor; IL-6ST = interleukin-6 signal transducer; IL-5RA = interleukin-5 receptor subunit alpha; CSF2RB = colony stimulating factor 2 receptor subunit beta; IL-13RA1 = interleukin-13 receptor subunit alpha 1; IL-13RA2 = interleukin-13 receptor subunit alpha 2.</p> <p>Our analysis of the multinutrient responder and multinutrient non-responder groups identified the <emph>cytokine–cytokine receptor interaction pathway</emph> as most relevant (<emph>p</emph> = 6.6 × 10<sups>−6</sups>), incorporating five of the previously identified six immune factors that showed a differential signal of change over time between these groups (i.e., IL-1RA, IL-6, IL-15, IFN-γ, and leptin; VEGF-A was not part of this pathway). Three other pathways – <emph>rheumatoid arthritis, JAK-STAT signaling pathway</emph>, and <emph>pathways in cancer</emph> – were also generated by the database, but these pathways only incorporated four of the six immune factors (<emph>results not shown</emph>).</p> <hd id="AN0193250478-20">Discussion</hd> <p>This study was an exploratory analysis of secondary data, and the study was not powered to detect differences in immune factors. For this exploratory analysis, we examined 25 plasma immune factors in 83 children with ADHD and emotional dysregulation who were randomized to receive either multinutrients or placebo for 8 weeks. Our hypothesis that 8 weeks of multinutrient supplementation in children with ADHD would reduce pro-inflammatory immune factors was confirmed; however, our hypothesis that multinutrient supplementation would result in an increase in anti-inflammatory factors was not. Rather, we saw a decrease in anti-inflammatory factors for certain immune markers (e.g., IL-13) in the multinutrient group. We propose two complementary explanations for this unexpected finding – multinutrient supplementation contributed to: (<reflink idref="bib1" id="ref59">1</reflink>) a reduced need for anti-inflammatory signaling (i.e., counter-regulation), as inflammation resolved, and/or (<reflink idref="bib2" id="ref60">2</reflink>) an upstream reduction of immune activation that reduced the production of both pro- and anti-inflammatory factors, as discussed below. Overall, two patterns were evident: on average, a greater number of pro-inflammatory immune factors decreased in the multinutrient group than in the placebo group (even among non-responders), while a greater number of anti-inflammatory immune factors increased in the placebo group than in the multinutrient group, supporting our hypothesis that inflammatory cytokines were reduced after multinutrients.</p> <p>Plasma and serum cytokines have been evaluated over the past 30 years in children with ADHD, showing some consistent results. Most prominently, elevation of IL-6, IL-10, IL-13, and IL-16 have been repeatedly observed in children with ADHD, both on and off medication ([<reflink idref="bib4" id="ref61">4</reflink>]; [<reflink idref="bib24" id="ref62">24</reflink>]; [<reflink idref="bib71" id="ref63">71</reflink>]). In our study, IL-6 decreased after multinutrient treatment, suggesting a potential correlation with multinutrient pharmacodynamics. Three ingredients in the multinutrient supplement (i.e., magnesium, vitamin D, and vitamin C) are known to reduce or inhibit IL-6 production ([<reflink idref="bib2" id="ref64">2</reflink>]; [<reflink idref="bib78" id="ref65">78</reflink>]; [<reflink idref="bib103" id="ref66">103</reflink>]), consistent with our finding (see also Table 5 for a summary of nutrients in the supplement studied that may impact inflammation and neurotransmission). Previous observational studies have demonstrated elevated IL-6 levels in children with ADHD compared to healthy controls ([<reflink idref="bib26" id="ref67">26</reflink>]; [<reflink idref="bib29" id="ref68">29</reflink>]; [<reflink idref="bib75" id="ref69">75</reflink>]) and one study demonstrated reduced IL-6 after supplementation with omega-3 fatty acids in children with ADHD ([<reflink idref="bib41" id="ref70">41</reflink>]). Additionally, IL-13 had a greater decrease after multinutrient treatment than placebo, potentially suggesting less physiological need for anti-inflammatory factors following multinutrient supplementation. Indeed, a post-treatment reduction in circulating anti-inflammatory cytokines does not necessarily mean a reduced anti-inflammatory capacity. Research shows that this drop in anti-inflammatory activity can reflect the waning need for counter-regulation as inflammation resolves (e.g., as reported in studies on tuberculosis; [<reflink idref="bib27" id="ref71">27</reflink>]; [<reflink idref="bib107" id="ref72">107</reflink>]; and asthma; [<reflink idref="bib72" id="ref73">72</reflink>]). Consistent with this theory are previous studies that report elevated IL-13 in children with ADHD, compared to children without ([<reflink idref="bib4" id="ref74">4</reflink>]; [<reflink idref="bib76" id="ref75">76</reflink>]).</p> <p>Table 5. Nutrients in the Supplement Studied that Affect Inflammation and Neurotransmission.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /></colgroup><thead><tr><th align="left">Nutrient</th><th align="center">Impact</th></tr></thead><tbody><tr><td>Vitamin A</td><td>Decreases severity of chronic inflammation (<xref ref-type="bibr" rid="bibr59">Kim, 2011</xref>); lower levels associated with lower tryptophan in major depressive disorder (<xref ref-type="bibr" rid="bibr49">Islam et al., 2020</xref>)</td></tr><tr><td>Vitamin B2</td><td>Minimizes inflammatory pain; detoxifies homocysteine (<xref ref-type="bibr" rid="bibr12">Bertollo et al., 2006</xref>); essential for the synthesis of myelin (<xref ref-type="bibr" rid="bibr83">Plantone et al., 2021</xref>)</td></tr><tr><td>Vitamin B6</td><td>Decreases IL-1, IL-6, IL-23, and TNF-α expression in monocyte and macrophage cells (<xref ref-type="bibr" rid="bibr70">Mikkelsen et al., 2023</xref>)</td></tr><tr><td>Vitamin C</td><td>Increases red blood cell glutathione (<xref ref-type="bibr" rid="bibr51">Johnston et al., 1993</xref>), reduces TNF-α and IL-6 (<xref ref-type="bibr" rid="bibr2">Akolkar et al., 2017</xref>); reduces IL-1β (<xref ref-type="bibr" rid="bibr6">Arablou et al., 2019</xref>); decreased levels associated with lower tryptophan, major depressive disorder (<xref ref-type="bibr" rid="bibr49">Islam et al., 2020</xref>)</td></tr><tr><td>Vitamin D</td><td>Turns off chronic inflammatory responses; inhibits IL-6 production, reduces circulating MCP-1 levels (<xref ref-type="bibr" rid="bibr78">Omidian et al., 2019</xref>); moderates vulnerability to depression through serotonergic system (<xref ref-type="bibr" rid="bibr14">Bonk et al., 2020</xref>)</td></tr><tr><td>Vitamin E</td><td>Reduces damage from TNF-α (<xref ref-type="bibr" rid="bibr111">Wells et al., 2010</xref>); exerts a significant reducing effect on serum levels of CRP (<xref ref-type="bibr" rid="bibr7">Asbaghi et al., 2020</xref>); macrophage migration inhibitory factor (<xref ref-type="bibr" rid="bibr43">Hegde et al., 2012</xref>)</td></tr><tr><td>Alpha-Lipoic Acid</td><td>Protects endothelial cells from inflammation (<xref ref-type="bibr" rid="bibr99">Shay et al., 2009</xref>); downregulates IL-1β and IL-6 (<xref ref-type="bibr" rid="bibr28">Dinicola et al., 2017</xref>)</td></tr><tr><td>Cysteine</td><td>Protects blood vessels, brain and liver from inflammatory damage (<xref ref-type="bibr" rid="bibr98">Sekhar et al., 2011</xref>); a precursor for glutathione; actives N-methyl-D-aspartate receptors; antagonizes GABAAρ1 receptors (<xref ref-type="bibr" rid="bibr25">Dalangin et al., 2020</xref>)</td></tr><tr><td>Manganese</td><td>Cofactor for antioxidant superoxide dismutase that fights inflammation within the cells (<xref ref-type="bibr" rid="bibr50">Jensen, 1999</xref>)</td></tr><tr><td>Zinc</td><td>Pro-inflammatory cytokines (IL-1β and TNF-α) decrease in response to zinc repletion (<xref ref-type="bibr" rid="bibr112">Wessels et al., 2013</xref>)</td></tr><tr><td>Magnesium</td><td>Decreases pro-inflammatory cytokines (TNF-α and IL-6; <xref ref-type="bibr" rid="bibr103">Sugimoto et al., 2012</xref>); decreases serum CRP levels; increases nitric oxide levels (<xref ref-type="bibr" rid="bibr108">Veronese et al., 2022</xref>), decreases IL-5 and IL-13 (<xref ref-type="bibr" rid="bibr67">Liang et al., 2012</xref>)</td></tr><tr><td>Iodine</td><td>Acts as an antioxidant by neutralizing hydrogen peroxide (<xref ref-type="bibr" rid="bibr1">Aceves et al., 2013</xref>); essential for myelin development and maintenance (<xref ref-type="bibr" rid="bibr85">Redman et al., 2016</xref>)</td></tr><tr><td>Potassium</td><td>Decreases macrophage infiltration; lowers expression of inflammatory cytokines (e.g., IL-1β); decreases NF-κB activation (W. <xref ref-type="bibr" rid="bibr110">Wang et al., 2007</xref>)</td></tr></tbody></table> </ephtml> </p> <p>The cytokines IL-4, IL-5, IL-6, and IL-13 had a significantly greater reduction in the multinutrient group versus the placebo group. In sensitivity analyses, these patterns were stronger at the Ohio site compared to the Oregon site, which may be due to geographic/climate differences in allergens, pathogens, and environmental exposures. For example, in unpublished data, urinary concentrations of glyphosate, a non-selective herbicide sold under the brand Roundup, were higher in Ohio than Oregon participants ([<reflink idref="bib53" id="ref76">53</reflink>]; [<reflink idref="bib56" id="ref77">56</reflink>]). All four cytokines (IL-4, IL-5, IL-6, and IL-13) are involved in a cell-mediated immune pathway, the Th2 pathway, which promotes allergic and atopic responses through the antibody immunoglobulin E (IgE; [<reflink idref="bib87" id="ref78">87</reflink>]). The reduction in Th2 cytokines, IL-4, IL-5, IL-6, and IL-13, suggests a reduction in Th2 signaling (Figure 2) and further, may correlate to biological changes in ADHD. Overactivation of the Th2 pathway can result in atopy, which may include allergies, asthma, or atopic dermatitis ([<reflink idref="bib11" id="ref79">11</reflink>]). Interestingly, atopic diseases are associated with ADHD and ADHD symptomatology ([<reflink idref="bib19" id="ref80">19</reflink>]). One theory suggests inflammation from atopic disease may impact the prefrontal cortex and anterior cingulate cortex of the growing brain, resulting in or aggravating ADHD behaviors ([<reflink idref="bib82" id="ref81">82</reflink>]; [<reflink idref="bib97" id="ref82">97</reflink>]).</p> <p>Further, these Th2-type cytokines may impact the hypothalamus-pituitary-adrenal (HPA) axis known to support regulation of stress and the autonomic nervous system and thus exacerbate ADHD symptomatology ([<reflink idref="bib19" id="ref83">19</reflink>]; [<reflink idref="bib68" id="ref84">68</reflink>]; [<reflink idref="bib104" id="ref85">104</reflink>]). In animal models, intracerebroventricular administration of IL-4 has been shown to induce hypothalamic inflammation, suggesting activation of M2 macrophages (alternatively activated) and microglia in that brain region ([<reflink idref="bib77" id="ref86">77</reflink>]). IL-4 can be released by certain microglia and directly affects the parasympathetic response as seen in the reduction of blood pressure ([<reflink idref="bib109" id="ref87">109</reflink>]). The parasympathetic nervous system can moderate an individual's stress response by either inhibiting or disinhibiting the sympathetic nervous system and HPA axis ([<reflink idref="bib88" id="ref88">88</reflink>]). The HPA axis plays a key role in the integration of adaptive responses to stress ([<reflink idref="bib101" id="ref89">101</reflink>]) and is commonly dysregulated in children with ADHD ([<reflink idref="bib10" id="ref90">10</reflink>]).</p> <p>Th1 and Th2 balance is ideal, as a Th2-weighted imbalance can contribute to overactive allergic responses ([<reflink idref="bib11" id="ref91">11</reflink>]). One study compared Th1- and Th2-type cytokines in ADHD, autism spectrum disorder, and a comparison group of children and found multiple differences between groups, including IL-4, as well as the ratio of all Th1/Th2 cytokines and the ratio of pro-inflammatory/anti-inflammatory cytokines ([<reflink idref="bib32" id="ref92">32</reflink>]). This aligns with decades of research on allergy and ADHD, which has identified that allergic diseases are more common in individuals with ADHD than in the general population and are associated with ADHD symptom severity ([<reflink idref="bib19" id="ref93">19</reflink>]). Thus, the decrease in Th2-type cytokines observed after multinutrient supplementation may have positive implications for these signaling pathways and common co-morbidities associated with ADHD.</p> <p>IL-4 and IL-13 are anti-inflammatory cytokines compared to IL-5 and IL-6, which are typically considered pro-inflammatory. It was unexpected that the anti-inflammatory cytokines, as well as the pro-inflammatory cytokines, decreased following multinutrient supplementation. Another interpretation of these findings is that multinutrient supplementation may have contributed to upstream immune pathway blockade (or broad immunosuppression) that reduced both pro- and anti-inflammatory cytokine production, as has been reported in other anti-inflammatory treatment studies (e.g., psoriasis, [<reflink idref="bib33" id="ref94">33</reflink>]; and Crohn's disease, [<reflink idref="bib9" id="ref95">9</reflink>]). As the immune system responds to cues, it works to balance pro- and anti-inflammatory cells and signals. The immune system's ability to maintain this balance in ADHD may be impaired. It has been suggested that a better understanding of the dynamically balanced immune response can help shape treatment strategies ([<reflink idref="bib20" id="ref96">20</reflink>]).</p> <p>When evaluating immune factor changes among those participants who received the multinutrient supplement, we found that 5 of 12 pro-inflammatory cytokines (IFN-γ, IL-6, IL-15, and immune factors leptin and VEGF-A) decreased to a greater extent in multinutrient non-responders than multinutrient responders. Although multinutrient responders unexpectedly had smaller decreases in some pro-inflammatory cytokines, they did have decreases. One hypothesis for this finding is that multinutrients regulated immune responses and reduced the demand for pro-inflammatory factors, as has been shown for major depressive disorder ([<reflink idref="bib62" id="ref97">62</reflink>]). While a causal relationship cannot be determined based on the current study, measuring immune factors at earlier timepoints following multinutrient supplementation could help test this hypothesis. Interestingly, IL-6 has been shown <emph>in vitro</emph> to increase in response to dopamine in a dose-dependent manner ([<reflink idref="bib73" id="ref98">73</reflink>]; [<reflink idref="bib80" id="ref99">80</reflink>]). Although this seems paradoxical, given the presumed dopamine deficiency of ADHD and the elevated pro-inflammatory factors associated with ADHD, it reaffirms a possible connection between neurotransmitter and cytokine imbalances and phenotypical presentations of ADHD. Thus, additional questions to address are whether multinutrient responders have improved dopamine production or improved dopamine signaling. Further clinical research is needed to better understand how neurotransmitters, such as dopamine, are affected by cytokines and other immune factors.</p> <p>An additional question to consider is why we observed a pattern of decreased immune factors (in particular, IFN-γ and IL-15) in the multinutrient non-responder group compared to multinutrient responders (Supplemental Figure 1). IFN-γ and IL-15 are both crucial for immune system regulation ([<reflink idref="bib13" id="ref100">13</reflink>]; [<reflink idref="bib64" id="ref101">64</reflink>]) and were positively correlated to each other in our study (<emph>r</emph> =.41, <emph>p</emph> =.0001; <emph>data not shown</emph>). Although elevations in these factors can be indicative of inflammation, reductions in these factors could indicate a weakened immune system ([<reflink idref="bib57" id="ref102">57</reflink>]; [<reflink idref="bib100" id="ref103">100</reflink>]). It is unlikely; however, that participants in the multinutrient non-responder group were immunocompromised. Additionally, IFN-γ and IL-15 may also act as anti-inflammatory cytokines ([<reflink idref="bib74" id="ref104">74</reflink>]). We also found that levels of IL-6 decreased in the non-responder group, as well as in the responder group. Given that treatment response was defined by scores on the CGI-I, it may be that reductions in IL-6 were associated with improvements in other aspects of functioning (e.g., depression and anxiety) not specifically measured by this treatment responder variable. In the context of the hypothesis-generating focus of this study, interpretation of these findings requires integration of the immune factors measured and analysis of variables that are beyond the scope of this paper (e.g., antibody response, immune cell proliferation, and other neuropsychiatric symptoms).</p> <p>To integrate the immune factors measured, and to understand the biological and clinical implications of the changes we observed in Th2 cytokines, we conducted bioinformatics pathway analysis. We identified four functionally relevant signaling pathways associated with the Th2 cytokines affected by multinutrient supplementation, including inflammatory bowel disease, IL-17 signaling, JAK-STAT signaling, and the most relevant: the cytokine-cytokine receptor pathway. Study results identified changes in five of the six cytokines in this pathway. The cytokine-cytokine receptor pathway interactions are pivotal in initiating intracellular signaling cascades that regulate cellular responses, including allergic immune responses and inflammation (Figure 2).</p> <p>With respect to previous studies examining multinutrient supplementation and immune factors, one other study investigated supplementation for 12 weeks: a sample of pregnant women who endorsed depression and anxiety. Supplementation improved self-reported mood and anxiety symptoms, but did not significantly change levels of the four immune marker levels measured (i.e., CRP, IL-6, IL-10, and TNF-α). Perhaps the lack of inflammatory marker changes in this selected group of immune markers reflected an increased need for nutrients during the pregnancy, as improved birth outcomes were reported for both mother and baby among women who were supplemented with the multinutrients ([<reflink idref="bib15" id="ref105">15</reflink>]; [<reflink idref="bib42" id="ref106">42</reflink>]; [<reflink idref="bib58" id="ref107">58</reflink>]). In contrast, a preclinical study found significant decreases in IL-4 and IL-5 following a combination nutrient treatment with choline chloride, vitamin C, and selenium ([<reflink idref="bib8" id="ref108">8</reflink>]). Similarly, a study on the effects of an aloe polymannose multinutrient complex reported decreased Th1/Th2 cytokine ratios at 12 months follow-up, as well as significant relationships between changes in Th1/Th2 ratios and cognitive function in adults with Alzheimer's disease ([<reflink idref="bib66" id="ref109">66</reflink>]). Less is known about the association between multinutrient supplementation and cytokines changes in children.</p> <hd id="AN0193250478-21">Limitations and Future Directions</hd> <p>These findings should be considered in the context of a few limitations. As this was an exploratory, hypothesis-generating study, one of the first examining possible biological mechanisms that might influence behavioral response to multinutrients, we did not correct for multiple testing. Other explanations for changes in immune factors, aside from multinutrient supplementation, were not accounted for in this study, including immune cell function and responses and other neuropsychiatric symptoms. Given the sample size, exploratory nature, and focus of this examination, we did not control for the variables: season of enrollment, age, allergies, or dietary patterns reported in this study; all of which may contribute to an individual's immune response. However, the RCT study design minimizes the impact of these baseline characteristics, and diet did not differ between randomized groups at baseline. Further, response to the multinutrients did not differ based on diet ([<reflink idref="bib86" id="ref110">86</reflink>]). The study was powered based on our primary behavioral outcomes (CASI-5, CGI-I), so we may not have been powered to detect changes in cytokines. Larger prospective studies would provide the opportunity to include these, and other key clinical and demographic factors, to enable a further examination of the possible role of multinutrients in counteracting inflammation and improving ADHD and emotional dysregulation symptoms. Future studies to assess the long-term effects of multinutrient supplementation on immune factors and ADHD symptoms would also be valuable.</p> <hd id="AN0193250478-22">Conclusions</hd> <p>A wide range of nutrients (all included in the multinutrient supplement studied) are associated with counteracting excessive inflammation, which affects neurotransmission (see, e.g., [<reflink idref="bib2" id="ref111">2</reflink>]; [<reflink idref="bib12" id="ref112">12</reflink>]; [<reflink idref="bib14" id="ref113">14</reflink>]; [<reflink idref="bib28" id="ref114">28</reflink>]; [<reflink idref="bib59" id="ref115">59</reflink>]; [<reflink idref="bib78" id="ref116">78</reflink>]; [<reflink idref="bib103" id="ref117">103</reflink>]). Understanding immune function in ADHD may guide therapeutic interventions for treating the disorder, while examining immune factor change in therapeutic interventions for ADHD may identify biomarkers' mechanisms underlying treatment response. Future studies may also consider the role of genetic variability, as polymorphisms in cytokine genes in children with ADHD can have implications for cognitive function and attention phenotypes ([<reflink idref="bib30" id="ref118">30</reflink>]; [<reflink idref="bib63" id="ref119">63</reflink>]).</p> <hd id="AN0193250478-23">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-1-jad-10.1177_10870547251397701 for Multinutrient Supplementation in Children With ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial by Jennifer M. Loftis, Hayleigh K. Ast, Alisha M. Bruton, Priya Srikanth, Ramya Ramesh, David W. Erikson, Lisa M. Robinette, Irene E. Hatsu, Brenda M.Y. Leung, Taryn A. Machingo, L. Eugene Arnold and Jeanette M. Johnstone in Journal of Attention Disorders</p> <p>The authors thank Dr. Barbara Gracious, MD, for her work to secure the Investigational New Drug application, and Dr. Alanna Welsh, ND, for additional references added to Table 4. The graphical abstract and Figure 2 were created with BioRender.com.</p> <ref id="AN0193250478-24"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref42" type="bt">1</bibl> <bibtext> Jennifer M. Loftis</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib2" idref="ref60" type="bt"></bibl> <bibtext>https://orcid.org/0000-0003-1773-9365 Hayleigh K. Ast</bibtext> </blist> <blist> <bibl id="bib3" idref="ref1" type="bt"></bibl> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib4" idref="ref29" type="bt"></bibl> <bibtext>https://orcid.org/0000-0002-2521-0309 Alisha M. Bruton</bibtext> </blist> <blist> <bibl id="bib5" idref="ref53" type="bt"></bibl> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib6" type="bt"></bibl> <bibtext>https://orcid.org/0000-0002-5929-3149 Priya Srikanth</bibtext> </blist> <blist> <bibl id="bib7" type="bt"></bibl> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib8" idref="ref108" type="bt"></bibl> <bibtext>https://orcid.org/0000-0002-0906-6757 David W. Erikson</bibtext> </blist> <blist> <bibl id="bib9" idref="ref95" type="bt"></bibl> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib10" idref="ref90" type="bt"></bibl> <bibtext>https://orcid.org/0000-0002-3383-9297 Irene E. Hatsu</bibtext> </blist> <blist> <bibl id="bib11" idref="ref79" type="bt"></bibl> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib12" idref="ref112" type="bt"></bibl> <bibtext>https://orcid.org/0000-0003-0501-9088 Jeanette M. Johnstone</bibtext> </blist> <blist> <bibl id="bib13" idref="ref100" type="bt"></bibl> <bibtext>Graph https://orcid.org/0000-0003-3947-5540</bibtext> </blist> <blist> <bibtext> The MADDY study was approved by two Institutional Review Boards: Oregon Health & Science University, Portland, Oregon, U.S. (#16870; Oregon site) and Ohio State University, Columbus, Ohio, U.S. (#2017H0188; Ohio site); participants at both sites provided blood samples. The study was prospectively registered with the National Clinical Trials Registry (NCT03252522; Micronutrients for Attention-Deficit Hyperactivity Disorder in Youth [MADDY] Study) and vetted by the US Food and Drug Administration (FDA IND#127832). The research was done according to The Code of Ethics of the World Medical Association (Declaration of Helsinki).</bibtext> </blist> <blist> <bibtext> Parental written consent and child verbal assent were obtained from all participants.</bibtext> </blist> <blist> <bibtext> Jennifer M. Loftis: Writing – review & editing, Conceptualization, Visualization, Supervision. Hayleigh K. Ast: Data Collection, Writing – original draft preparation, review & editing, Visualization. Alisha M. Bruton: Writing: original draft preparation, Writing: review & editing, Data Collection. Priya Srikanth: Formal Analysis, Writing: original draft preparation, review & editing. Ramya Ramesh: Formal Analysis, Writing: review & editing. David W. Erikson: Investigation, Methodology, Formal analysis. Lisa Robinette: Writing: review & editing, Data Collection. Irene E. Hatsu: Funds acquisition, Project administration, Supervision, Writing – review and editing. Brenda MY Leung: Funds acquisition, Project administration, Writing – review & editing. Taryn A. Machingo: Writing – review and editing, visualization. L. Eugene Arnold: Project Conceptualization, Writing – review and editing, Supervision. Jeanette M. Johnstone: Project Conceptualization, Funding acquisition, Project administration, Data collection, Writing – review, editing, finalizing, Supervision.</bibtext> </blist> <blist> <bibtext> The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Micronutrients for ADHD in Youth (MADDY) study was funded through private donations to the Nutrition and Mental Health Research Fund, managed by the Foundation for Excellence in Mental Health Care (FEMHC), and a direct grant from FEMHC, and from the Gratis Foundation. Authors also received support for the study from the National Institutes of Health (NIH) National Center for Complementary and Integrative Health (NCCIH) 5R90AT00892403 (JMJ) to the National University for Natural Medicine, NCCIH T32 AT002688 to OHSU (HKA, AMB, TAM, JMJ); the National Center for Advancing Translational Sciences of the NIH, UL1TR000128, UL1TR002369; 8UL1TR000090-05 at Oregon Health & Science University (OHSU) and Ohio State University; OHSU's Department of Child and Adolescent Psychiatry; the Department of Behavioral Health and Psychiatry and the Research Institute at Nationwide Children's Hospital, the Department of Psychiatry and Behavioral Health as well as the Department of Human Sciences at Ohio State University. BMYL is supported by the Emmy Droog Chair in Complementary and Alternative Healthcare. JMJ, AMB, TAM and HKA are supported by the Center for Mental Health Innovation at OHSU. JMJ is also supported by the NIH (NIH-NCCIH K23AT012068) and the Gratis Foundation. The Endocrine Technologies Core (DE) is supported in part by NIH P51OD011092 for operation of OHSU's Oregon National Primate Research Center. The study funders had no role in the design or reporting of the study. This paper was also supported, in part, by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Clinical Sciences Research and Development Merit Review Award I01 CX002668 (JML). Some work was conducted using facilities at Veterans Affairs Portland Health Care System (Portland, Oregon, United States). JML is a Research Scientist at the Veterans Affairs Portland Health Care System. The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.</bibtext> </blist> <blist> <bibtext> The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Arnold has received research funding from Supernus Pharmaceuticals, Roche/Genentech Phamaceuticals, Otsuka Pharmaceuticals, Axial, Yamo, Maplight. Myndlift, YoungLiving Essential Oils and National Institute of Health (R01 MH 100144), has consulted with Pfizer Pharmaceuticals, Yamo, and CHADD, and been on advisory boards for Otsuka and Roche/Genentech. The other authors declare no conflicts of interest.</bibtext> </blist> <blist> <bibtext> Data will be shared upon reasonable request.</bibtext> </blist> <blist> <bibtext> Supplemental material for this article is available online.</bibtext> </blist> <blist> <bibtext> † Deceased, author died on April 27, 2025.</bibtext> </blist> </ref> <ref id="AN0193250478-25"> <title> References </title> <blist> <bibtext> Aceves C., Anguiano B., Delgado G. (2013). The extrathyronine actions of iodine as antioxidant, apoptotic, and differentiation factor in various tissues. Thyroid, 23(8), 938–946. https://doi.org/10.1089/THY.2012.0579</bibtext> </blist> <blist> <bibtext> Akolkar G., da Silva Dias D., Ayyappan P., Bagchi A. K., Jassal D. S., Salemi V. M. C., Irigoyen M. C., De Angelis K., Singal P. K., Omidian M., Mahmoudi M., Javanbakht M. H., Eshraghian M. R., Abshirini M., Daneshzad E., Hasani H., Alvandi E., Djalali M. (2017). 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Loftis; Hayleigh K. Ast; Alisha M. Bruton; Priya Srikanth; Ramya Ramesh; David W. Erikson; Lisa M. Robinette; Irene E. Hatsu; Brenda M.Y. Leung; Taryn A. Machingo; L. Eugene Arnold and Jeanette M. Johnstone</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author</p> <p></p> <p>Jennifer M. Loftis, PhD, is a Research Scientist at the VA Portland Health Care System and a Professor in the Departments of Psychiatry and Behavioral Neuroscience at Oregon Health & Science University. Her translational research program studies the psychoneuroimmunological mechanisms contributing to mood disorders, cognitive impairments, and addiction and tests immunotherapeutic strategies to treat these conditions.</p> <p>Hayleigh K. Ast, ND, is an NIH Postdoctoral Fellow within the Science for Nutrition Affect and Cognition for Kids (SNACK) lab in the Center for Mental Health and Innovation at Oregon Health & Science University. Her research examines the gut-brain-immune axis in children with neurodevelopmental disorders, with a focus on integrative medicine.</p> <p>Alisha M. Bruton, ND, MS, MS, is a Research Scientist and Biostatistician in the Center for Mental Health Innovation at Oregon Health & Science University. Her work focuses on the role of nutrition in emotion regulation and attention in children as part of the Science of Nutrition Affect and Cognition in Kids (SNACK) Lab. She is also passionate about evidence synthesis.</p> <p>Priya Srikanth is a biostatistics faculty with the OHSU-PSU School of Public Health. She has collaborated on clinical trials and other observational studies. Her notable publications include her work on inflammatory markers (Srikanth et al., Osteoporos Int., 2016) and the primary outcomes manuscript of the MADDY study (Johnstone et al., Journal of the American Academy of Child & Adolescent Psychiatry, 2022).</p> <p>Ramya Ramesh is a data-driven biostatistician trained at Oregon Health & Science University, where she earned a Master of Science in Biostatistics. Her expertise includes data management, visualization, and analysis; longitudinal data analysis; regression modeling; and medical device quality systems and reliability engineering, and she is a co-author of a Journal of Orthopaedic Research article on intramuscular pH in tibia fractures.</p> <p>David W. Erikson, Ph.D. is a Senior Staff Scientist and Director of the Endocrine Technologies Core at Oregon National Primate Research Center. Dr. Erikson's main areas of expertise include reproductive biology, and development and application of assay methodologies. His research has been published in journals such as Biology of Reproduction, Contraception, and Nature Communications.</p> <p>Lisa M. Robinette, PhD, is a Postdoctoral Scientist at the Abigail Wexner Research Institute at Nationwide Children's Hospital (Columbus, Ohio, USA). She earned her PhD in Nutrition from The Ohio State University (Columbus, Ohio, USA). Her research focuses on nutrition and neurodevelopment.</p> <p>Irene E. Hatsu, PhD, RDN, is an Associate Professor of Human Nutrition and an Extension State Specialist at The Ohio State University (Columbus, Ohio, USA). Her research focuses on the nexus between food and nutrition security and chronic physical and mental diseases in vulnerable and underserved populations.</p> <p>Brenda M. Y. Leung, PhD, is an Associate Professor, Faculty of Health Sciences, University of Lethbridge. Trained in epidemiology, her research focuses on maternal and child health, mental health, nutrition epidemiology, diabetes, and integrative medicine. A notable publication is Micronutrients for ADHD in youth (MADDY) study: comparison of results from RCT and open label extension (doi: 10.1007/s00787-023-02236-2).</p> <p>Taryn A. Machingo, PhD, is an NIH T32 Postdoctoral Research Fellow in the Department of Psychiatry at Oregon Health & Science University. Her research focuses on nutritional psychiatry and immune-inflammatory mechanisms in mental health. She combines this work with clinical practice, clinical trial operations, and interdisciplinary research in child and adolescent populations.</p> <p>L. Eugene Arnold, MD, MEd, was Professor Emeritus of Psychiatry at The Ohio State University, known for his work in child and adolescent psychiatry and neurodevelopmental disorders. He authored more than 300 peer-reviewed articles, along with numerous books and chapters, advancing research and clinical care in ADHD and autism. Dr. Arnold passed away in April 2025.</p> <p>Jeanette M. Johnstone, PhD, MA, is an Associate Professor and Clinical Psychologist in the Center for Mental Health Innovation at Oregon Health & Science University. She directs the Science of Nutrition Affect and Cognition in Kids (SNACK) lab, focused on integrative treatments for ADHD and emotional dysregulation, and is particularly interested in the biological mechanisms of response to the multinutrients.</p> </aug> <nolink nlid="nl1" bibid="bib45" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib81" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib96" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib114" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib60" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib44" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib37" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib16" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib23" firstref="ref10"></nolink> <nolink nlid="nl10" bibid="bib36" firstref="ref11"></nolink> <nolink nlid="nl11" bibid="bib69" firstref="ref12"></nolink> <nolink nlid="nl12" bibid="bib54" firstref="ref13"></nolink> <nolink nlid="nl13" 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Multinutrient Supplementation in Children with ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Jennifer+M%2E+Loftis%22">Jennifer M. Loftis</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1773-9365">0000-0003-1773-9365</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hayleigh+K%2E+Ast%22">Hayleigh K. Ast</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2521-0309">0000-0002-2521-0309</externalLink>)<br /><searchLink fieldCode="AR" term="%22Alisha+M%2E+Bruton%22">Alisha M. Bruton</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5929-3149">0000-0002-5929-3149</externalLink>)<br /><searchLink fieldCode="AR" term="%22Priya+Srikanth%22">Priya Srikanth</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0906-6757">0000-0002-0906-6757</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ramya+Ramesh%22">Ramya Ramesh</searchLink><br /><searchLink fieldCode="AR" term="%22David+W%2E+Erikson%22">David W. Erikson</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-3383-9297">0000-0002-3383-9297</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lisa+M%2E+Robinette%22">Lisa M. Robinette</searchLink><br /><searchLink fieldCode="AR" term="%22Irene+E%2E+Hatsu%22">Irene E. Hatsu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0501-9088">0000-0003-0501-9088</externalLink>)<br /><searchLink fieldCode="AR" term="%22Brenda+M%2E+Y%2E+Leung%22">Brenda M. Y. Leung</searchLink><br /><searchLink fieldCode="AR" term="%22Taryn+A%2E+Machingo%22">Taryn A. Machingo</searchLink><br /><searchLink fieldCode="AR" term="%22L%2E+Eugene+Arnold%22">L. Eugene Arnold</searchLink><br /><searchLink fieldCode="AR" term="%22Jeanette+M%2E+Johnstone%22">Jeanette M. Johnstone</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3947-5540">0000-0003-3947-5540</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Attention+Disorders%22"><i>Journal of Attention Disorders</i></searchLink>. 2026 30(6):727-746.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 20
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2026
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Center for Complementary and Integrative Health (NCCIH) (DHHS/NIH)<br />National Center for Advancing Translational Sciences (NCATS) (DHHS/NIH)<br />National Institutes of Health (NIH) (DHHS)<br />Office of Research and Development (ORD) (VA)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: 5R90AT00892403<br />T32AT002688
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Attention+Deficit+Hyperactivity+Disorder%22">Attention Deficit Hyperactivity Disorder</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Nutrition%22">Nutrition</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms+%28Individual+Disorders%29%22">Symptoms (Individual Disorders)</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Physiology%22">Physiology</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Health%22">Child Health</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/10870547251397701
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1087-0547<br />1557-1246
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: While individual nutrients have shown effects on inflammatory mechanisms, the effects of multinutrients (vitamins + minerals, antioxidants, and amino acids) on inflammation are unknown. We investigated whether 8 weeks of multinutrient supplementation, in a randomized controlled trial of 83 children with ADHD, would alter immune factors compared to placebo. Methods: Multiplex technology was used to measure 25 immune factors in blood samples collected at baseline and week 8. Immune factors were compared between multinutrient and placebo groups using the Mann-Whitney test. Linear mixed effects models evaluated immune factor change over time. To understand the functional relevance of the immune factors affected by multinutrient supplementation, pathway analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.7 Bioinformatics Resources. Results: Interleukin (IL)-5 and IL-13 levels differed following multinutrient supplementation versus placebo (p = 0.005 and 0.03, respectively). IL-5 decreased by 1.3% in the multinutrient group (95% CI [-8.6%, 6.7%]) and increased by 17.5% in the placebo group (95% CI [6.9%, 29.2%]). IL-13 decreased by 11.4% in the multinutrient group (95% CI [-18.2%, -4.0%]), compared to a 2.4% increase in the placebo group (95% CI [-7.2%, 13.1%]). When comparing immune factors between treatment responders versus non-responders in the multinutrient group, there was a 4.3% increase in IL-15 in multinutrient responders (95% CI [-6.8%, 16.8%]) and a 14.3% decrease in non-responders (p = 0.03, 95% CI [-24.9%, -2.4%]). Pathway analysis identified T helper type 2 (Th2) signaling pathways affected by multinutrient supplementation, including IL-17 and cytokine-cytokine receptor interaction pathways. Conclusion: Th2 immune factors may be influenced by multinutrient supplementation and associated with behavioral improvements in ADHD.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2026
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1504298
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1504298
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  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/10870547251397701
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 727
    Subjects:
      – SubjectFull: Attention Deficit Hyperactivity Disorder
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: Nutrition
        Type: general
      – SubjectFull: Symptoms (Individual Disorders)
        Type: general
      – SubjectFull: Program Effectiveness
        Type: general
      – SubjectFull: Physiology
        Type: general
      – SubjectFull: Child Health
        Type: general
      – SubjectFull: Intervention
        Type: general
    Titles:
      – TitleFull: Multinutrient Supplementation in Children with ADHD Reduced Pro- and Anti-Inflammatory Immune Factors in the MADDY Randomized Controlled Trial
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            NameFull: Ramya Ramesh
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            NameFull: David W. Erikson
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            – D: 01
              M: 06
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1087-0547
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