Project DyAdd: Fatty acids and cognition in adults with dyslexia, ADHD, or both

ARTICLE IN PRESS Prostaglandins, Leukotrienes and Essential Fatty Acids 81 (2009) 79–88

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Prostaglandins, Leukotrienes and Essential Fatty Acids journal homepage: www.elsevier.com/locate/plefa

Project DyAdd: Fatty acids and cognition in adults with dyslexia, ADHD, or both$ Marja Laasonen a,b,, Laura Hokkanen a, Sami Leppa¨ma¨ki c, Pekka Tani c, Arja T. Erkkila¨ d a

Department of Psychology, University of Helsinki, P.O. Box 9 (Siltavuorenpenger 20), FIN-00014, Helsinki, Finland Department of Phoniatrics, Helsinki University Central Hospital, Helsinki, Finland c Department of Psychiatry, Clinic for Neuropsychiatry, Helsinki University Central Hospital, Helsinki, Finland d School of Public Health and Clinical Nutrition, University of Kuopio, Kuopio, Finland b

a r t i c l e in fo

abstract

Article history: Received 19 October 2008 Received in revised form 6 January 2009 Accepted 21 April 2009

Both attention deficit hyperactivity disorder (ADHD) and dyslexia are suggested to co-occur with altered fatty acid (FA) metabolism, but it is unknown how FAs are associated with the cognitive domains that characterize these disorders. In the project DyAdd, we investigated the associations between FAs in serum phospholipids and phonological processing, reading, spelling, arithmetic, executive functions, and attention. Healthy controls (n ¼ 36), adults with ADHD (n ¼ 26), dyslexia (n ¼ 36), or both (n ¼ 9) were included in the study. FAs included saturated, monounsaturated, total polyunsaturated, n-3, and n-6 FAs, together with n-6/n-3, AA/EPA, and LA/ALA ratios. When all the study subjects were included in the analyses, especially polyunsaturated FAs (PUFAs) were positively associated with cognition, but reading was least associated with FAs. These associations were modulated by gender, intelligence, n-3 PUFA intake, and group. Accordingly, within the ADHD group, only few associations emerged with PUFAs, n-6 PUFAs, and cognitive domains, whereas in the dyslexia group the more prevalent associations appeared with PUFAs and n-3 PUFAs. & 2009 Elsevier Ltd. All rights reserved.

Keywords: DyAdd Adult Dyslexia ADHD Fatty acids Cognition

1. Introduction The human brain and its cell membranes constitute predominantly of lipids that themselves are composed of saturated, monounsaturated, and polyunsaturated fatty acids (FAs) [1]. Most of the cerebrum consists of saturated and monounsaturated FAs [2], while polyunsaturated FAs (PUFAs) constitute only 15–30% of the dry mass of the brain [3]. However, the role of PUFAs in central nervous system structure and functioning has been emphasized. In general, PUFAs contribute to the flexibility of the neuronal cell walls [4] and their metabolites have important functional roles [5,6]. Furthermore, n-3 and n-6 PUFAs differ in their metabolism, for example, production of eicosanoids [2]. Especially, four PUFAs are important: dihomo-g-linolenic acid (20:3 n-6, DGLA), arachidonic acid (20:4 n-6, AA), eicosapentaenoic acid (20:5 n-3, EPA), and docosahexaenoic acid (22:6 n-3, DHA). Of these, DHA appears to be of specific importance [2,7,8]: It makes up 10–20% of the

$ Sources of support: We thank Academy of Finland (project 108410), Emil Aaltonen Foundation, Otologic Research Foundation, Otto A. Malm Foundation, and ¨ flund Foundation for financial support. Oskar O  Corresponding author at: Department of Psychology, University of Helsinki, P.O. Box 9 (Siltavuorenpenger 20), FIN-00014, Helsinki, Finland. Tel.: +358 9 19129532; fax: +358 9 19129443. E-mail address: Marja.Laasonen@helsinki.fi (M. Laasonen).

0952-3278/$ - see front matter & 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.plefa.2009.04.004

cortical tissue FAs [1], it is prevalent in neuronal phospholipid membranes [9], and it is concentrated at synapses where it contributes to cell signaling and neurotransmission [8–11]. Therefore, it is not surprising that the role of PUFAs in various cognitive conditions, including attention deficit hyperactivity disorder (ADHD) and developmental dyslexia, has been investigated. Previous research suggests that ADHD is related to lowered status of n-3 PUFAs and to elevated status of n-6 PUFAs [12]. An elevated ratio of n-6/n-3 PUFAs is suggested to be of importance to both ADHD and dyslexia [12,13]. More specifically, males with ADHD and dyslexia have been shown to share an elevated n-6/n-3 ratio [12]. One explanation for these aspects of FA status is the membrane phospholipid hypothesis [14], which suggests that subjects with ADHD and dyslexia suffer from a genetic abnormality in their phospholipid metabolism [15,16]. However, it is not resolved how FAs are associated with the cognitive domains that characterize ADHD or dyslexia. The few studies that have investigated the relations between FAs and cognition are reviewed below. 1.1. Fatty acids in ADHD cognition Some PUFAs, that is, linoleic acid (18:2 n-6, LA) and a-linolenic acid (18:3 n-3, ALA), are called essential FAs (EFAs) since they cannot be synthesized by humans and have to be provided by the

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diet. EFA deficiency symptoms have been found to correlate with ADHD symptoms in children [17] when assessed with questionnaires (10-item abbreviated version of Conners’ ADHD index [18] and Questionnaire for FADS [19]). However, significant relations emerged only within the general population (n ¼ 347) but not within a subgroup of children who had ‘‘ADHD symptoms’’ (n ¼ 104). This pattern of results suggests that EFA deficiency signs are not related to a possible diagnosis of ADHD but, instead, to characteristics that are related to the condition and manifest also in those without a diagnosis. Another line of research has investigated the relations between FA status and cognition in those with ADHD. Mitchell and colleagues [20] showed that ADHD children with low serum AA status had higher rate of speech difficulties and were more often regarded as having slow development or learning difficulties than those with high AA status. However, DHA or DGLA were not associated with cognitive functioning. The role of other FAs was not reported. In one study Stevens and colleagues [19] found negative relations between DHA in plasma or red blood cells and ADHD rating scales (Conners’ Parent but not Teacher Rating Scale [21]) in a group combining ADHD children and controls. Associations between AA and rating scales were not significant and findings for other FAs were not reported. In another study, Stevens and colleagues [22] compared boys with low plasma n-3 or n-6 PUFA status to those with a high status. The study groups consisted of those with and without ADHD. Those with low n-3 PUFA status had more difficulties as assessed with ADHD rating scales (‘‘Health Questionnaire’’ and Conners’ Parent and Teacher Rating Scales [21]) in the areas of conduct, anxiety, hyperactivity/ impulsivity, temper tantrums, problems getting to sleep, problems getting up in the morning, and learning problems. In children with or without ADHD, Colter and colleagues [23] reported that DHA in red blood cells correlated negatively with scores on questionnaires assessing ADHD (Conners’ Parent Rating Scales Long Version, CPRS:L [21]) in the areas of oppositional behavior, hyperactivity, cognitive problems, restlessness, problematic behavior, DSM-IV inattention, and DSM-IV total. Total n-3 PUFAs correlated negatively with restlessness and n-6/n-3 ratio positively with oppositional behavior, restlessness, and problematic behavior. n-6 PUFAs correlated positively with oppositional behavior, restlessness, problematic behavior, DSM-IV inattentive, DSM-IV total, and ADHD-index scales. There are few correlative studies on ADHD adults. Young and colleagues [24] showed that DHA in red blood cells or serum was not related to ADHD symptoms, as assessed with a questionnaire (AMEN [25]) in adults with or without ADHD. Other correlations were not reported. Antalis and colleagues [26] found in a combined group of control adults and those with ADHD that the status of DHA in red blood cells or plasma correlated negatively with a questionnaire assessing ADHD symptoms (Conners’ Adult ADHD Rating Scales, CAARS-SV [21]) in the areas of inattention, impulsivity/hyperactivity, and DSM-IV. Only the correlations for n-3 PUFAs were reported. Taken together, previous research suggests that low status of n-3 PUFAs is associated with elevated behavioral and perhaps also cognitive symptoms of ADHD. Fewer findings on n-6 PUFAs suggest an opposite pattern. However, these relations have been shown only with rating scales and when assessed in groups combining subjects with ADHD and controls. Also, all of the ADHD samples have had limitations, such as, unreliable diagnoses [19,20,22], concomitant special diet or medication [19,20,22–24,26], or a comorbid condition [23]. Further, the relations have been assessed with statistically liberal tests, most often Pearson correlations, without controlling for any intervening factors, such as, gender, intelligence, or diet.

1.2. Fatty acids in dyslexic cognition The relevance of FAs for dyslexia has been emphasized mainly by the magnocellular theory [27]. It suggests that a system of rapidly functioning large neurons that spans the visual system is affected in at least some dyslexic readers. This system mediates the processing of rapidly changing visual information and is involved in visual attention. Also other perceptual domains and the cerebellum are suggested to be affected. The magnocellular theory notes the fact that modern diet is low in n-3 PUFAs [28]. Magnocells are suggested to be vulnerable to the resulting PUFA deficiency [29], since their functioning depends on the rapid dynamics of the membrane ion channels which is facilitated by the surrounding PUFAs [27,30]. Further, the alleles related to poor reading are suggested to be involved also in PUFA metabolism [27,28,30]. This altered metabolism would be reflected in, for example, immune reactions that could mobilize PUFAs from the cell membranes of those with dyslexia [28,30]. Also, the membrane phospholipid hypothesis by Horrobin et al. suggest that dyslexia results from a genetic impairment in neuronal FA metabolism, which could result in reduced incorporation of both AA and DHA into the cell membranes [16]. There is less research on dyslexia, FAs, and cognition. Richardson and colleagues [31] reported that high scores in EFA deficiency sign questionnaire (FADS [19]) were related to poor reading, spelling, and auditory working memory as assessed with the British Ability Scales (Word reading ability, Similarities, Matrices, Spelling, and Recall of digits [32]). This was observed in dyslexic boys but not in girls or in the total study group. In a study by Taylor and colleagues [33], EFA deficiency signs in adults correlated with symptoms of dyslexia when assessed with questionnaires (FADS [19] and Adult Dyslexia Check List [34]). In all participants and within the dyslexic readers, EFA deficiency signs correlated positively with cognitive domains related to visual reading-related, visual general, auditory/language, spoken language, and motor problems. Within the group of controls, the correlations were significant only for the visual problems. Again, the relations within males and females differed. Cyhlarova and colleagues [13] investigated the relations between FA status in red blood cells and literacy skills as assessed with the Word reading and Spelling tasks of Wide Range Achievement Test (WRAT [35]). There was a positive relation between reading and n-3 PUFAs (including total n-3 PUFAs, stearidonic acid (18:4 n-3), and DHA) and a negative relation between reading and n-6 PUFAs (including n-6 adrenic acid, n-6/ n-3 ratio, and AA/EPA ratio) when dyslexic and control adults were combined. Spelling was positively related to n-3 PUFAs (including total n-3 PUFAs and DHA). Within the group of controls, reading was positively associated with total n-3 PUFAs and DHA and spelling was positively associated with DHA. Within the dyslexia group, reading was again positively associated n-3 PUFAs (including total n-3 PUFAs and ALA) and negatively associated with n-6 PUFAs (including adrenic acid, AA/EPA ratio, and LA/ALA ratio). Spelling was also negatively associated with n-6 PUFAs (LA/ALA ratio). Taken together, low status of n-3 PUFAs and high status of n-6 PUFAs seem to be associated with cognitive symptoms of dyslexia, that is, impaired reading and spelling. Further, the relations seem to be more frequent in the dyslexic readers compared to the controls, and for variables related to reading compared to spelling.

1.3. Focus of the current study Low status of n-3 PUFAs and high status of n-6 PUFAs are suggested to be related to an elevated amount of difficulties

ARTICLE IN PRESS M. Laasonen et al. / Prostaglandins, Leukotrienes and Essential Fatty Acids 81 (2009) 79–88

related to both ADHD and dyslexia. However, previous ADHD studies suffer from methodological limitations and there is very little research on dyslexia. Further, to our knowledge there are no studies that would have investigated the associations between FA status and cognitive functioning in both ADHD and dyslexia. In the current study, we will investigate the associations between FA profiles in serum phospholipids and cognitive domains that characterize dyslexia or ADHD, that is, phonological processing, reading, spelling, arithmetic, executive functions, and attention. The study groups include healthy controls and adults with ADHD, dyslexia, or both. We will investigate also the effects of gender, intelligence, group, and sources of n-3 PUFAs on the relations between FAs and cognition. Lastly, the relations between PUFAs and cognitive domains will be examined separately within the groups of controls, adults with only ADHD, and adults with only dyslexia. If FAs and their current status are considered to be important for the cognitive domains that characterize these developmental disabilities, one would expect to find significant relations between the two levels of analysis in the combined sample of adult participants. Further, if FAs and their current status are considered to reflect a shared biological factor that is relevant for the cognitive difficulties of those with ADHD and dyslexia, one would expect to find similar relations between FAs and cognition within the groups with ADHD and dyslexia.

2. Patients and methods Full description of the methods used in the project DyAdd can be found in a previous article [36]. 2.1. Patients Subjects with dyslexia and ADHD were required to have a prior diagnosis as an inclusion criterion. The subjects in the ADHD

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group were diagnosed according to DSM-IV criteria [37] using CAADID [38] by a medical doctor specialized in neuropsychiatry (authors SL or PT in most cases). Confounding psychiatric disorders were excluded by SCID-I [39] and SCID-II [40] interviews. Thus, hyperactivity was not a required characteristic, and also those with only inattention were included. Therefore, in this paper the label ADHD refers both to those with attention deficit disorder (ADD) and those with ADHD. The subjects in the dyslexia group were diagnosed by appropriate specialists. Their diagnosis was based on achievement criteria. The current phonological processing and reading status of each subject in the dyslexia and comorbid groups was checked against the age-corrected values of our previous control data [41]. Every subject in these two groups performed below 1 standard deviation in reading or phonological processing as assessed with phonological naming (rapid alternate stimulus naming (RAS) speed/correctness [42]), phonological awareness (phonological synthesis correctness [41]), phonological memory (WAIS digit span forward length [43]), and reading (oral reading speed/ correctness, task details in [41]). Most of the participants with ADHD were recruited through Helsinki University Central Hospital, Clinic for Neuropsychiatry, and the remaining from a private practice of a specialist having experience on ADHD. Majority of those with dyslexia were recruited through HERO (Diverse learners’ association in Helsinki). Other recruitment sources for the dyslexia and control groups were University of Helsinki, large civil service departments of City of Espoo with heterogeneous staff, student organizations at the University of Helsinki, vocational high schools, and vocational schools in the metropolitan area of Helsinki. Participants were volunteers. An informed consent was obtained from all of them and the project DyAdd was accepted by the appropriate ethical committee of Helsinki University Central Hospital. Finnish as mother tongue and age 18–55 years were further inclusion criteria. Exclusion criteria were brain injury, a somatic or psychiatric condition affecting cognitive

Table 1 Demographic characteristics of the subjects. Group

Age (years) FIQ Gender Female Male Handedness Right Left Ambidextrous Educational level Basic Middle High Medication Washed-out None Fatty fish consumption Seldom X1 times/week Use of FA supplements (Yes)

n Mean (SD) Mean (SD)

Control

ADHD

Group dyslexia

Comorbid

36 38.08 (11.71) 113.47 (11.51)

26 32.31 (8.10) 102.23 (15.19)

36 34.78 (10.17) 107.89 (11.30)

9 32.56 (10.31) 105.33 (16.45)

n (%) n (%)

19 (53%) 17 (47%)

11 (42%) 15 (58%)

20 (54%) 17 (46%)

6 (67%) 3 (33%)

n (%) n (%) n (%)

31 (86%) 4 (11%) 1 (3%)

22 (85%) 3 (12%) 1 (4%)

35 (95%) 2 (5%) 0 (0%)

9 (100%) 0 (0%) 0 (0%)

n (%) n (%) n (%)

13 (36%) 10 (28%) 13 (36%)

16 (64%) 4 (16%) 5 (20%)

17 (46%) 12 (32%) 8 (22%)

6 (67%) 2 (22%) 1 (11%)

n (%) n (%)

0 (0%) 36 (100%)

7 (27%) 19 (73%)

0 (0%) 36 (100%)

1 (11%) 8 (89%)

n (%) n (%) n (%)

18 (50%) 18 (50%) 24 (67%)

17 (68%) 8 (32%) 16 (62%)

18 (53%) 16 (47%) 23 (64%)

4 (44%) 5 (56%) 7 (78%)

Abbreviation: FIQ ¼ full Intelligence quotient [43]. NB. Subjects with ADHD participated the project unmedicated. If they had a prescription for methylphenidate, a wash-out period of at least one week was required before and during the appointments. ADHD subjects with medication with a longer half-life were excluded from the project.

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functions (including major depression), medication affecting cognitive functions, and substance abuse. Subjects with ADHD participated in the project unmedicated. If they had a prescription for methylphenidate, a wash-out period of at least one week was required before and during the appointments. ADHD subjects with medication with a longer half-life were excluded from the project. For details, see Table 1. Those with Wechsler Abbreviated Scale of Intelligence (WASI) full intelligence quotient (FIQ) [43] less than 70 (that is, less than 2 standard deviations) were also excluded from every group, due to the ICD-10 criteria for specific reading disorder [44]. This resulted in excluding 1 subject in the dyslexia and 1 in the ADHD groups. Two subjects with ADHD dropped out of the study and their incomplete data was excluded from the analyses. Demographic characteristics of the subjects are presented in Table 1. The groups did not differ in their age (F(3,104) ¼ 1.84, p ¼ 0.144), gender (w2(3) ¼ 1.82, p ¼ 0.610), self-reported handedness (w2(6) ¼ 3.69, p ¼ 0.718), or educational level (w2(6) ¼ 7.53, p ¼ 0.275). The groups differed in their FIQ (F(3,104) ¼ 4.05, p ¼ 0.00), which was lower in the ADHD group than in the controls (p ¼ 0.006).

Table 2 Sum variables (numbered), individual cognitive tasks, and variables (in parentheses) used in the analyses. 1. 2. 3. 4. 5. 6. 7.

8. 9. 10. 11. 12. 13. 14. 15.

2.2. Methods 16.

The cognitive tasks were part of a larger neuropsychological battery, which is described in more detail in a previous study [36]. The current study focused on cognitive domains that characterize dyslexia or ADHD, that is, phonological processing, reading, spelling, arithmetic, executive functions, and attention. In addition to these general domains, several of their sub-components were assessed. These are described below. All three areas of phonological processing were evaluated: phonological awareness (the ability to be aware of the sound structure of spoken language), phonological memory (the ability to code and temporarily store sound-based representations), and phonological naming speed (the ability to rapidly access phonological information stored in long-term memory). Also all three areas of achievement were assessed, that is, reading, spelling, and arithmetic. Within reading, both technical and comprehension performance were assessed. Within executive functions, set shifting (the ability to display flexibility in the face of changing schedules of reinforcement), inhibition (the ability to suppress an overlearned or automatic response), and planning (the ability to formulate and carry out steps towards a desired goal) were assessed. Within attention, both sustained (the ability to maintain a consistent behavioral response during continuous and repetitive activity) and divided (the ability to respond simultaneously to multiple tasks or multiple task demands) aspects were evaluated. The variables that reflect each domain, their sub-components, and the single tasks are presented in Table 2 and in more detail in a previous study [45]. Blood samples were drawn after the subjects had fasted overnight. Serum samples were stored at 70 1C until the FAs in serum phospholipids were analyzed. Lipids were extracted from the serum sample with chloroform-methanol (2:1). Lipid fractions were separated with an aminopropyl column. FA methyl esters were analyzed with a gas-chromatograph (Hewlett-Packard 5890 series II, Hewlett-Packard Company, Waldbronn, Germany) equipped with FFAP-column (length 25 m, inner diameter 2 mm, and film thickness 0.3 mm, Agilent) and helium as the carrier gas. FAs are presented as molar percentage of total FAs [46–48]. The subjects filled in a short dietary questionnaire [49]. The questionnaire included questions on the frequency of fatty fish consumption (never or seldom, 1–2, 3–5, or 6–7 times per week,

17. 18. 19.

Phonological processing (average of 2–4): Awareness (synthesis (correct) [41] and Pig Latin (correct) [57]a) Memory (WMS-III digit span forward length (correct) [58]a and pseudoword span length (correct) [59]) Naming speed (RAS (speeds for two trials) [42] and Stroop color naming (speed) [60]) Reading, technical (average of 6–7): Speed (narrative text (speed) [41] and word list and pseudoword list reading (speed) [57]a) Accuracy (narrative text (correct) [41], word list and pseudoword list reading (correct) [57]a, segregating word chains (correct) [61]a, and searching for misspellings (correct) [61]a) Reading, comprehension: (average of 9–10) Speed (forced choice task (speed) [57]a and searching for incorrect words within a story (speed) [61]a) Accuracy (forced choice task (correct) [57]a and searching for incorrect words within a story (correct) [61]a) Spelling: accuracy (pseudoword writing (correct) [61]a) Arithmetic: accuracy (WAIS-III Arithmetic (correct) [43]a and RMAT (correct) [62]) Executive functions (average of 14–16): Set shifting (CANTAB Intra-extra dimensional set shifting (stages completed, total errors adjusted) [63]b) Inhibition (Stroop (inhibition errors, difference score) [60] and Color Trails Test (difference score) [64]) Planning (CANTAB Stockings of Cambridge (mean initial thinking time 5 moves, problems solved in minimum moves) [63]b) Attention (average of 18–19): Sustained (Dual task (sustained attention for dots, sustained attention for numbers) [60] and Color Trails Test (speed for first trial) [64]) Divided (Dual task (divided attention for dots, divided attention for numbers) [60] and Color Trails Test (speed for second trial) [64])

NB. If the value of a ‘‘correct’’ variable is less than its maximum, it can be explained by either speed of performance, errors, or missing answers. a The task has been standardized for adults in Finland. b The task is computerized.

recoded for the analyses as never or seldom vs. at least once per week) and use of supplements with fish oil, cod liver oil, or evening primrose oil (yes/no). 2.3. Statistical analyses For the sake of simplicity and to reduce the error variance related to individual task scores, both the FA and cognitive variables were analyzed as sum variables. The single FA variables were first z-score standardized within the group of controls. The control group’s means and standard deviations were used also when standardizing the proportions of the remaining groups. After this, the FA variables were summarized into total saturated, monounsaturated, PUFAS, n-6 PUFAs, and n-3 PUFAs. Saturated FAs included the following variables: myristic acid 14:0; palmitic acid 16:0; stearic acid 18:0; arachidic acid 20:0; behenic acid 22:0; and lignoceric acid 24:0. Monounsaturated FAs included the following variables: palmitoleic acid 16:1; oleic acid 18:1, n-9+n-7; gadoleic acid 20:1; erucic acid 22:1; and nervonic acid 24:1. n-6 PUFAs included the following variables: LA 18:2 n-6; g-linolenic acid (GLA) 18:3 n-6; DGLA 20:3 n-6; AA 20:4 n-6; and adrenic acid 22:4 n-6. n-3 PUFAs included the following variables: ALA 18:3 n-3; EPA 20:5 n-3; docosapentaenoic acid 22:5 n-3; and DHA 22:6 n-3. Standardized values were used also for the following ratios: n-6/n-3, AA/EPA, and LA/ALA. Also the cognitive variables were analyzed as sum variables. The individual task scores were z-score standardized based on the control group’s values and averaged (see Table 2 for the description of the sum variables). Finally, the standardized

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cognitive sum variables were converted to indicate better performance with a larger positive value. Thus, in every cognitive sum variable, 0 indicates the control mean, 1 indicates performance that is one standard deviation better than the control mean, and 1 indicates performance that is one standard deviation poorer than the control mean. Sequential regression analyses were performed between a specific FA sum variable (as an independent variable, entered in step 1) and a specific cognitive sum variable (as a dependent variable). The contribution of covariates was controlled by entering in step 2 gender, in step 3 gender and FIQ, and in the final step 4 the group in addition to those variables in step 3 (as two dummy variables: presence or absence of ADHD or dyslexia). Missing values (only in cognitive variables) were not replaced but a pairwise exclusion method was used. The first focus was on, whether the given FA variable alone resulted in a significant R2 at step 1 (po0.05, two-tailed). Then, the changes in the significance level of beta of the FA variable were examined when the covariates were added in steps 2–4. This enabled the assessment of the role of a given FA when gender (step 2); gender and FIQ (step 3); and gender, FIQ and group (step 4) were controlled for. In the first set of additional analyses, the sources of n-3 PUFAs were controlled for by adding two dichotomous independent variables at a new step 5 into the original analyses (frequency of fatty fish consumption and use of supplements with fish oil, cod liver oil, or evening primrose oil). In the second set of additional analyses, we conducted the original PUFA, n-6 PUFA, and n-3 PUFA analyses within the groups of controls, those with only ADHD, and those with only dyslexia. The small comorbid group was excluded from the within group analyses.

3. Results Tables 3 and 4 present the results at the first step, that is, the associations between a FA sum variable and a cognitive sum variable without any of the covariates. Table 3 presents the cognitive sum variables that are traditionally related to dyslexia (phonological processing and achievement) and Table 4 presents those that traditionally relate to ADHD (executive functions and attention). Below we describe in more detail the changes that occurred when all the covariates were added (gender, FIQ, and group), effect of controlling for sources of n-3 PUFAs, and relations within the groups in PUFAs. 3.1. Saturated and monounsaturated fatty acids Saturated FAs were not associated with any of the cognitive domains without or with all the covariates (see Tables 3 and 4). Controlling for the sources of n-3 PUFAs did not affect the results. Monounsaturated FAs were negatively associated with the following cognitive variables without the covariates (see Tables 3 and 4): Reading comprehension accuracy, Spelling, Arithmetic, and Planning. With all the covariates, a negative relation remained only for Arithmetic (b ¼ .168, t(1,102) ¼ 2.309, p ¼ 0.23). Controlling for the sources of n-3 PUFAs did not affect the results. 3.2. Polyunsaturated fatty acids PUFAs were positively associated with the following cognitive variables without the covariates (see Tables 3 and 4): Phonological processing, Phonological naming speed, Executive functions, and Planning. With all the covariates, the positive relations for all but Planning remained (Phonological processing: b ¼ 0.245, t(1,101) ¼

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3.241, p ¼ 0.002; Phonological naming speed: b ¼ 0.278, t(1,101) ¼ 3.283, p ¼ 0.001; Executive functions: b ¼ 0.243, t(1,99) ¼ 2.570, p ¼ 0.012). In addition, new positive relations emerged for aspects of phonological processing and attention (Phonological awareness: b ¼ 0.178, t(1,102) ¼ 2.089, p ¼ 0.039; Attention: b ¼ 0.213, t(1,100) ¼ 2.401, p ¼ 0.018; Divided attention: b ¼ 0.223, t(1,100) ¼ 2.473, p ¼ 0.015). Controlling for the sources of n-3 PUFAs resulted in two changes. One of the previously significant positive relations was diminished to a trend (Phonological awareness: b ¼ 0.173, t(1,96) ¼ 1.918, p ¼ 0.058) and a new positive association emerged for Inhibition (b ¼ 0.200, t(1,94) ¼ 1.998, p ¼ 0.049).

3.3. Within group analyses: PUFAs Within the control group, PUFAs were positively associated with Phonological naming speed without the covariates (b ¼ 0.340, t(1,34) ¼ 2.108, p ¼ 0.042). With all the covariates, this positive relation remained (Phonological naming speed: b ¼ 0.330, t(1,32) ¼ 2.054, p ¼ 0.048). Within the ADHD group, PUFAs were positively associated with Planning without the covariates (b ¼ 0.393, t(1,24) ¼ 2.093, p ¼ 0.047). With all the covariates, this positive relation did not emerge, but there were negative relations for Technical reading (b ¼ 0.482, t(1,22) ¼ 2.271, p ¼ 0.033) and Technical reading speed (b ¼ 0.483, t(1,22) ¼ 2.160, p ¼ 0.042). Within the dyslexia group and without the covariates, PUFAs were positively associated with all the aspects of phonological processing and attention, together with most of the aspects of technical reading (Phonological processing: b ¼ 0.563, t(1,35) ¼ 4.027, po0.001; Phonological awareness: b ¼ 0.448, t(1,35) ¼ 2.961, p ¼ 0.005; Phonological memory: b ¼ 0.507, t(1,35) ¼ 3.480, p ¼ 0.001; Phonological naming speed: b ¼ 0.430, t(1,35) ¼ 2.815, p ¼ 0.008; Technical reading: b ¼ 0.408, t(1,34) ¼ 2.602, p ¼ 0.014; Technical reading accuracy: b ¼ 0.363, t(1,34) ¼ 2.273, p ¼ 0.029; Attention: b ¼ 0.487, t(1,35) ¼ 3.297, p ¼ 0.002; Sustained attention: b ¼ 0.449, t(1,35) ¼ 2.970, p ¼ 0.005; Divided attention: b ¼ 0.429, t(1,35) ¼ 2.813, p ¼ 0.008). With all the covariates, the positive relations remained except for Technical reading accuracy (Phonological processing: b ¼ 0.472, t(1,33) ¼ 3.381, p ¼ 0.002; Phonological awareness: b ¼ 0.331, t(1,33) ¼ 2.195, p ¼ 0.035; Phonological memory: b ¼ 0.368, t(1,33) ¼ 2.653, p ¼ 0.012; Phonological naming speed: b ¼ 0.429, t(1,33) ¼ 2.734, p ¼ 0.010; Technical reading: b ¼ 0.366, t(1,32) ¼ 2.171, p ¼ 0.037; Attention: b ¼ 0.435, t(1,33) ¼ 2.840, p ¼ 0.008; Sustained attention: b ¼ 0.379, t(1,33) ¼ 2.486, p ¼ 0.018; Divided attention: b ¼ 0.409, t(1,33) ¼ 2.492, p ¼ 0.018).

3.4. n-6 polyunsaturated fatty acids n-6 PUFAs were positively associated with the following cognitive variables without the covariates (see Tables 3 and 4): Executive functions, Inhibition, and Planning. With all the covariates, these positive relations remained together with new positive associations for aspects of phonological processing and attention (Phonological processing: b ¼ 0.191, t(1,101) ¼ 2.364, p ¼ 0.020; Phonological naming speed: b ¼ 0.209, t(1,101) ¼ 2.306, p ¼ 0.023; Executive functions: b ¼ 0.358, t(1,99) ¼ 3.741, po0.001; Inhibition: b ¼ 0.330, t(1,100) ¼ 3.467, p ¼ 0.001; Planning: b ¼ 0.209, t(1,101) ¼ 2.092, p ¼ 0.039; Attention: b ¼ 0.193, t(1,100) ¼ 2.063, p ¼ 0.042; Divided attention: b ¼ 0.215, t(1,100) ¼ 2.267, p ¼ 0.026). Controlling for the sources of n-3 PUFAs diminished few of the previously significant positive associations to a trend (Planning: b ¼ 0.181,

84

Table 3 Associations between FA sum variables and dyslexia-related cognitive sum variables without covariates in all subjects (n ¼ 107). Phonological processing

b

R

p

F(1,106)

b

R

p

F(1,106)

b

R

p

0.04 0.77 6.22 0.36 4.29 0.39 0.46 0.01

0.02 0.09 0.24 0.06 0.20 0.06 0.07 0.01

0.00 0.01 0.06 0.00 0.04 0.00 0.00 0.00

0.84 0.38 0.01* 0.55 0.04* 0.54 0.50 0.92

0.00 0.86 3.78 0.37 2.08 0.14 1.54 0.01

0.00 0.09 0.19 0.06 0.14 0.04 0.12 0.01

0.00 0.01 0.03 0.00 0.02 0.00 0.01 0.00

0.97 0.36 0.05 0.54 0.15 0.70 0.22 0.91

0.27 1.79 2.16 0.02 3.31 0.00 0.18 0.03

0.05 0.13 0.14 0.01 0.17 0.00 0.04 0.02

0.00 0.02 0.02 0.00 0.03 0.00 0.00 0.00

0.61 0.18 0.15 0.89 0.07 1.00 0.67 0.86

Technical reading speed 2

Technical reading accuracy 2

R

p

F(1,106)

b

R

p

F(1,104)

b

R

p

0.26 0.01 0.88 0.03 0.71 0.11 0.80 0.00

0.05 0.01 0.09 0.02 0.08 0.03 0.09 0.01

0.00 0.00 0.01 0.00 0.01 0.00 0.01 0.00

0.61 0.90 0.35 0.86 0.40 0.74 0.37 0.95

0.30 1.17 1.30 0.01 1.31 0.09 0.32 0.03

0.05 0.10 0.11 0.01 0.11 0.03 0.05 0.02

0.00 0.01 0.01 0.00 0.01 0.00 0.00 0.00

0.58 0.28 0.26 0.91 0.25 0.77 0.57 0.86

0.02 0.42 1.01 0.04 1.93 0.02 1.06 0.06

0.01 0.06 0.10 0.02 0.14 0.01 0.10 0.02

0.00 0.00 0.01 0.00 0.02 0.00 0.01 0.00

0.90 0.52 0.32 0.83 0.17 0.89 0.31 0.81

F(1,81) 0.00

b 0.00

R2

p

F(1,103)

0.00

0.98

0.04

b

0.00 0.01 6.09 0.94 2.54 1.03 0.00 0.06

b

R2

p

0.00 0.01 0.23 0.09 0.15 0.10 0.00 0.02

0.00 0.00 0.05 0.01 0.02 0.01 0.00 0.00

0.96 0.91 0.02* 0.33 0.11 0.31 0.98 0.81

Spelling

F(1,78)

b

R2

p

0.06 0.36 0.70 0.25 0.11 0.11 0.48 0.43

0.03 0.07 0.09 0.06 0.04 0.04 0.08 0.07

0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.01

0.80 0.55 0.41 0.62 0.75 0.74 0.49 0.52

b

R2

p

Arithmetic

R2

p

F(1,105)

b

R2

p

0.00

0.85

0.41

0.06

0.00

0.52

0.05

0.03 *

6.16

0.24

0.06

0.01 *

0.00

0.67

1.98

0.14

0.02

0.00

0.85

0.27

0.05

0.00

0.79

4.94

0.00

0.93

0.00 0.01

F(1,106) 0.15

0.04

0.00

0.70

13.84

0.34

0.12

0.00 *

0.16

1.92

0.13

0.02

0.17

0.00

0.61

0.96

0.09

0.01

0.33

0.21

0.04

0.03 *

7.72

0.26

0.07

0.01 *

0.19

0.04

0.00

0.66

1.17

0.10

0.01

0.28

0.83

0.00

0.00

0.00

0.97

0.12

0.03

0.00

0.73

0.36

0.37

0.06

0.00

0.54

0.53

0.07

0.01

0.47

0.02 MUFA

0.41

0.07

0.01

0.53

4.88 0.21

PUFA

1.49

0.13

0.02

0.23

0.19 0.04

n-6 PUFA

0.04

0.02

0.00

0.85

0.04 0.02

n-3 PUFA

1.23

0.12

0.01

0.27

0.07 0.03

n-6/n-3

0.10

0.03

0.00

0.75

0.01 0.01

AA/EPA

2.08

0.16

0.03

0.15

0.05 0.02

LA/ALA

0.22

0.05

0.00

0.64

0.83 0.09

Abbreviations: SFA: saturated fatty acids (FAs), MUFA: mononunsaturated FAs, PUFA: polyunsaturated FAs, AA: arachidonic acid, EPA: eicosapentaenoic acid, LA: linoleic acid, ALA: a-linolenic acid. Asterisks refer to significant associations between FAs and cognitive variables (for details, see Section 2.3).

ARTICLE IN PRESS

b

Reading comprehension accuracy

F(1,105)

Reading comprehension 2

F(1,104)

Reading comprehension speed

SFA

Phonological naming speed 2

F(1,105)

Technical reading

SFA MUFA PUFA n6 PUFA n-3 PUFA n-6/n-3 AA/EPA LA/ALA

Phonological memory 2

M. Laasonen et al. / Prostaglandins, Leukotrienes and Essential Fatty Acids 81 (2009) 79–88

SFA MUFA PUFA n-6 PUFA n-3 PUFA n-6/n-3 AA/EPA LA/ALA

Phonological awareness 2

ARTICLE IN PRESS M. Laasonen et al. / Prostaglandins, Leukotrienes and Essential Fatty Acids 81 (2009) 79–88

85

Table 4 Associations between FA sum variables and ADHD-related cognitive sum variables without covariates in all subjects (n ¼ 107). Executive functions

SFA MFA PUFA n-6 PUFA n-3 PUFA n-6/n-3 AA/EPA LA/ALA

Set shifting

Planning

F(1,103)

b

R2

p

F(1,105)

b

R2

p

F(1,104)

b

R2

p

F(1,105)

b

R2

p

0.01 1.64 8.33 9.15 0.07 0.23 0.33 0.29

0.01 0.13 0.27 0.29 0.03 0.05 0.06 0.05

0.00 0.02 0.07 0.08 0.00 0.00 0.00 0.00

0.94 0.20 0.00 * 0.00 * 0.79 0.63 0.57 0.59

0.28 1.15 0.28 0.56 0.08 7.04 3.13 0.00

0.05 0.10 0.05 0.07 0.03 0.25 0.17 0.00

0.00 0.01 0.00 0.01 0.00 0.06 0.03 0.00

0.60 0.29 0.60 0.46 0.78 0.01 * 0.08 0.98

0.01 0.21 2.82 5.77 0.74 0.06 0.03 1.57

0.01 0.05 0.16 0.23 0.08 0.02 0.02 0.12

0.00 0.00 0.03 0.05 0.01 0.00 0.00 0.01

0.91 0.65 0.10 0.02 * 0.39 0.80 0.87 0.21

0.03 4.63 5.85 3.95 0.12 0.04 0.74 0.05

0.02 0.21 0.23 0.19 0.03 0.02 0.08 0.02

0.00 0.04 0.05 0.04 0.00 0.00 0.01 0.00

0.87 0.03* 0.02* 0.05* 0.73 0.85 0.39 0.83

Attention

SFA MFA PUFA n-6 PUFA n-3 PUFA n-6/n-3 AA/EPA LA/ALA

Inhibition

Sustained attention

Divided attention

F(1,105)

b

R2

p

F(1,105)

b

R2

p

F(1,104)

b

R2

p

0.08 0.10 3.73 0.40 1.98 0.08 0.20 0.13

0.03 0.03 0.19 0.06 0.14 0.03 0.04 0.03

0.00 0.00 0.03 0.00 0.02 0.00 0.00 0.00

0.77 0.76 0.06 0.53 0.16 0.78 0.65 0.72

0.41 0.31 2.51 0.11 1.92 0.49 0.08 0.25

0.06 0.05 0.15 0.03 0.13 0.07 0.03 0.05

0.00 0.00 0.02 0.00 0.02 0.00 0.00 0.00

0.53 0.58 0.12 0.74 0.17 0.48 0.78 0.62

0.03 0.01 0.19 0.08 0.12 0.02 0.06 0.01

0.08 0.01 3.76 0.69 1.41 0.06 0.33 0.01

0.00 0.00 0.03 0.01 0.01 0.00 0.00 0.00

0.78 0.94 0.06 0.41 0.24 0.81 0.57 0.93

Abbreviations: SFA: saturated fatty acids (FAs), MUFA: mononunsaturated FAs, PUFA: polyunsaturated FAs, AA: arachidonic acid, EPA: eicosapentaenoic acid, LA: linoleic acid, ALA: a-linolenic acid. Asterisks refer to significant associations between FAs and cognitive variables (for details, see Section 2.3).

t(1,102) ¼ 1.690, p ¼ 0.094; Attention: b ¼ 0.197, t(1,101) ¼ 1.955, p ¼ 0.054).

accuracy (b ¼ .187, t(1,99) ¼ 2.261, p ¼ 0.026). Controlling for the sources of n-3 PUFAs did not affect the results.

3.5. Within group analyses: n-6 PUFAs

3.7. Within group analyses: n-3 PUFAs

Within the control group and without the covariates, n-6 PUFAs were positively associated with Phonological naming speed (b ¼ 0.341, t(1,34) ¼ 2.113, p ¼ 0.042), Executive functions (b ¼ 0.386, t(1,32) ¼ 2.368, p ¼ 0.024), and Inhibition (b ¼ 0.418, t(1,33) ¼ 2.641, p ¼ 0.013). With all the covariates, all these relations remained together with a new positive relation with Phonological processing (Phonological processing: b ¼ 0.297, t(1,32) ¼ 2.043, p ¼ 0.049; Phonological naming speed: b ¼ 0.337, t(1,32) ¼ 2.103, p ¼ 0.043; Executive functions: b ¼ 0.380, t(1,30) ¼ 2.348, p ¼ 0.026; Inhibition: b ¼ 0.418, t(1,31) ¼ 2.627, p ¼ 0.013). Within the ADHD group and without the covariates, n6 PUFAs were negatively associated with Technical reading (b ¼ 0.403, t(1,24) ¼ 2.158, p ¼ 0.041) but positively associated with Executive functions (b ¼ 0.444, t(1,24) ¼ 2.430, p ¼ 0.023) and Planning (b ¼ 0.444, t(1,24) ¼ 2.431, p ¼ 0.023). With all the covariates, a negative association with Technical reading accuracy emerged (b ¼ 0.384, t(1,22) ¼ 2.087, p ¼ 0.049) together with a remaining positive relation with Executive functions (b ¼ 0.407, t(1,22) ¼ 2.334, p ¼ 0.029) and a new one with Inhibition (b ¼ 0.403, t(1,22) ¼ 2.483, p ¼ 0.021). Within the dyslexia group, no associations with n-6 PUFAs emerged without or with all the covariates.

Within the control group, there were no associations with n-3 PUFAs without the covariates. With all the covariates, n-3 PUFAs were negatively associated with Technical reading speed (b ¼ 0.331, t(1,32) ¼ 2.105, p ¼ 0.043) and Inhibition (b ¼ 0.338, t(1,31) ¼ 2.040, p ¼ 0.0499). Within the ADHD group, no associations with n-3 PUFAs emerged without or with all the covariates. Within the dyslexia group, n-3 PUFAs were positively associated with all the aspects of phonological processing and attention together with Spelling (Phonological processing: b ¼ 0.534, t(1,35) ¼ 3.735, p ¼ 0.001; Phonological awareness: b ¼ 0.448, t(1,35) ¼ 2.968, p ¼ 0.005; Phonological memory: b ¼ 0.503, t(1,35) ¼ 3.442, p ¼ 0.002; Phonological naming : b ¼ 0.375, t(1,35) ¼ 2.396, p ¼ 0.022; Spelling: b ¼ 0.354, t(1,35) ¼ 2.242, p ¼ 0.031; Attention: b ¼ 0.447, t(1,35) ¼ 2.958, p ¼ 0.006; Sustained attention: b ¼ 0.458, t(1,35) ¼ 3.052, p ¼ 0.004; Divided attention: b ¼ 0.338, t(1,35) ¼ 2.128, p ¼ 0.040). With all the covariates, only some of the positive relations with aspects of phonological processing remained (Phonological processing: b ¼ 0.408, t(1,33) ¼ 2.449, p ¼ 0.020; Phonological memory: b ¼ 0.384, t(1,33) ¼ 2.439, p ¼ 0.020).

3.8. n-3 Ratios between n-6 and n-3 polyunsaturated fatty acids 3.6. n-3 polyunsaturated fatty acids n-3 PUFAs were positively associated with the following cognitive variables without the covariates (see Tables 3 and 4): Phonological processing, Spelling, and Arithmetic. With all the covariates, none of these associations remained significant but a new negative relation emerged for Reading comprehension

n-6/n-3 ratio was negatively associated with set shifting without the covariates (see Tables 3 and 4) and with all the covariates (b ¼ .265, t(1,101) ¼ 2.696, p ¼ 0.008). Controlling for the sources of n-3 PUFAs did not affect the results. AA/EPA or LA/ALA ratios were not associated with any of the cognitive domains without or with all the covariates (see Tables 3 and 4). Controlling for the sources of n-3 PUFAs did not affect the results.

ARTICLE IN PRESS 86

M. Laasonen et al. / Prostaglandins, Leukotrienes and Essential Fatty Acids 81 (2009) 79–88

4. Discussion and conclusions In the current study, we investigated the associations between FA profiles in serum phospholipids and cognitive domains that characterize dyslexia or ADHD, that is, phonological processing, reading, spelling, arithmetic, executive functions, and attention, in the groups of healthy controls and adults with ADHD, dyslexia, or both. We hypothesized that, if FAs and their current status are considered to be important for the cognitive domains that characterize these developmental disabilities, we would find significant relations between FAs and cognition when all the study subjects were included in the analyses. The results showed that especially PUFAs were positively associated with cognition, but of the cognitive domains reading was least associated with FAs. We investigated also the effects of gender, intelligence, group, and sources of n-3 PUFAs on the associations between FAs and cognition. The results showed that controlling for these variables affected the relations. Lastly, the associations between PUFAs and cognition were inspected separately within the groups of controls, adults with only ADHD, or those with only dyslexia. We hypothesized that, if FAs and their current status are considered to reflect a shared biological factor that is relevant for the cognitive difficulties of those with ADHD and dyslexia, we would find similar relations between FAs and cognition within these groups. The results showed that within the ADHD group, only few associations emerged with PUFAs and n-6 PUFAs, whereas in the dyslexia group the more prevalent associations appeared with PUFAs and n-3 PUFAs. In the following sections, we will firstly describe the associations between FAs and cognition. Secondly we will discuss how these general relations were reflected within the groups of controls, those with only ADHD, and those with only dyslexia. Thirdly we will discuss, which of the covariates had an effect on the relations between FAs and cognition. In this context, we will also describe how controlling for the sources of n-3 PUFAs affected the relations.

4.1. Associations between FAs and cognition Saturated FAs were not related to any of the cognitive domains and in monounsaturated FAs only few negative associations emerged. Contrasted to this, relations with PUFAs were prevalent and all of them were positive. This was reflected both in n-6 and n-3 PUFAs. These results are in line with the suggestions that of the FAs, especially PUFAs are important for cognition (see Introduction for details). It has been also suggested that the ratios between n-6 and n-3 PUFAs could be of special importance [1]. However, these ratios were not generally associated with cognition when all the study subjects were included in the analyses. Most of the areas of executive functions and attention were positively associated with the current status of PUFAs and n-6 PUFAs. This suggests that these FAs may be important for the cognitive domains that characterize ADHD when all the study subjects are included in the analyses. Of the cognitive domains, no associations emerged in any of the areas of technical reading and in most of the areas of reading comprehension. Thus, FAs seem not to be relevant for the cognitive domain of reading that is one characteristic of dyslexia. However, most of the areas of phonological processing together with spelling and arithmetic were positively associated with PUFAs, also n-3 PUFAs. Therefore, the status of these FAs appears to be related to achievement in general and to the most commonly accepted core factor of developmental dyslexia, that is, phonological processing [50,51]. These associations in the total study group suggest that FAs are not related to cognition only in those affected by developmental

challenges. Instead, in a mixed sample with also those with an expected developmental trajectory, the adult FA status was related to the cognitive domains that characterize ADHD or dyslexia. To our knowledge, there are no studies that have investigated the associations between FA status and ADHD-related cognition in a combined group of subjects with or without ADHD. Further, we are aware of only two studies that have investigated the associations between FA status and dyslexia-related cognition in subjects with or without dyslexia. The study by Cyhlarova and colleagues [13] showed in adults that technical reading was negatively related to n-6 PUFAs (only adrenic acid) but positively related to n-3 PUFAs (total n-3 PUFAs, stearidonic acid, and DHA). Also spelling was positively related to n-3 PUFAs (total n-3 PUFAs and DHA). Also we have investigated the associations between FA status and cognitive functions in children with oral clefts [46,47]. This was motivated by the fact that some subgroups of these children have difficulties in phonological processing and reading [52,53]. We showed that phonological processing was positively related to n-3 PUFAs, whereas technical reading was negatively related to both monounsaturated FAs (only palmitoleic acid) and n-6 PUFAs (only GLA) [47]. These three studies seem to be consistent in their relations between FAs, spelling, and phonological processing. However, they appear to be inconsistent in their relations between FAs and technical reading as no associations emerged in the current study. One explanation for this is the differences in the robustness of the variables. The reading-related variables of the previous studies have reflected performance in single tasks. Also in the previous studies, the significant relations were rather general within the n-3 PUFAs, but emerged only in single FAs within the n-6 PUFAs. This may explain why there were no significant relations at the level of the sum variables that were used in the current analyses.

4.2. Associations within controls, those with only ADHD, and those with only dyslexia Within the control group, significant associations emerged with PUFAs, n-6 PUFAs, and n-3 PUFAs. Cyhlarova and colleagues [13] showed in their group of controls that n-3 PUFAs were positively associated with reading (total n-3 PUFAs and DHA) and spelling (only DHA) but no associations emerged with the n-6 PUFAs. In the current study, the relations were rather different, that is, positive for PUFAs and n-6 PUFAs in phonological processing and executive functions but negative for n-3 PUFAs with specific aspects of technical reading and executive functions. This can be explained by various factors, one of which was discussed already above. Others include differences in, for example, participating groups, participant age, language environment, tasks, and statistical analyses. Earlier results have not taken into account confounding factors and therefore differences in statistical analyses are a plausible explanation. In those with ADHD only, significant associations emerged in PUFAs and n-6 PUFAs, but not in n-3 PUFAs. Of note is our previous observation in the same subjects that only the proportion of n-6 PUFAs was higher in ADHD subjects than in other groups [12]. In the Introduction, we summarized previous ADHD research, which suggests that low status of n-3 PUFAs and high status of n-6 PUFAs are associated with elevated symptoms of ADHD. However, these previous relations were shown with rating scales, groups combining subjects with ADHD and controls, ADHD samples that had some methodological limitations, and with statistically liberal methods. All these most probably explain the inconsistencies, as in the current study the PUFA and n-6 PUFA relations were negative with all of the aspects of technical reading but positive with most of the aspects of executive functions. It

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must be noted that most of the current relations were greatly affected by covariates. In the dyslexia group, significant associations emerged in PUFAs and n-3 PUFAs, but not in n-6 PUFAs. In the Introduction, we summarized that similar to ADHD low status of n-3 PUFAs and high status of n-6 PUFAs appear to be associated with the cognitive symptoms of dyslexia, that is, impaired reading and spelling. In the current study, all the significant associations with PUFAs were positive and they emerged in all the aspects of phonological processing and attention, most of the aspects of technical reading, and spelling. The results of the current study are in part in line with the previous study by Cyhlarova and colleagues [13] who showed in their dyslexia group that reading was positively associated with n-3 PUFAs (total n-3 PUFAs and ALA) but negatively related to n-6 PUFAs (only adrenic acid). In our previous sample of cleft children, 54% were overall slow readers and 43% were dyslexic (slow reading combined with average/above intelligence) [47]. In the slow readers, there were prevalent significant relations but all of them were negative: Phonological processing was negatively related to n-6 (only DGLA) and n-3 PUFAs (EPA and docosapentaenoic acid) and reading was negatively related to n-3 PUFAs (only EPA). Again, the rather differing results of this last study emphasize the effect of study populations on the results. Taken together, the current results in the separate groups of controls, those with ADHD only, and those with dyslexia only were rather different from each other. Those with ADHD shared some characteristics with the controls, that is, positive relations between n-6 PUFAs and executive functions. In addition, there were positive relations between PUFAs and phonological processing in those with dyslexia and in controls. However, the two clinical groups did not share any relations with each other. Thus, the summary in the Introduction that suggested a low status of n-3 PUFAs and a high status of n-6 PUFAs to be related to an elevated amount of difficulties in those with ADHD and dyslexia was not confirmed. In other words, we gained no support for the hypothesis that adult FA status could be considered to reflect a shared biological factor that is relevant for the cognitive difficulties of those with ADHD and dyslexia. Further, of the cognitive domains that characterize ADHD, only executive functions resulted in significant associations within the group with ADHD, attention did not. Instead, significant relations with attention emerged within the dyslexia group. Of the cognitive domains that characterize dyslexia, phonological processing, reading, and spelling all resulted in significant associations within the group with dyslexia. Thus, adult FA status appears to be more relevant for the cognition of those with dyslexia and the relations found in these groups of adults suggest that FAs are not related to cognition only during development.

4.3. Effect of covariates gender, FIQ, group, and sources of n-3 PUFAs on the associations between FAs and cognition Controlling for gender affected the relations between especially PUFAs, and also n-3 PUFAs, phonological processing, and attention. This is in line with our previous study with the same sample, where differences in FA status emerged in the total sample and in males but not in females [12]. Secondly, controlling for the group had an effect on the relations between PUFAs, n-6 PUFAs, phonological processing, attention, and specific aspects of executive functions. This is in line with the current analyses within groups and our previous study in the same subjects showing differences in proportions of PUFAs among the groups [12]. Thirdly, controlling for FIQ had an effect on the relations of many FAs, that is, monounsaturated FAs, PUFAs, n-6 PUFAs, and n3 PUFAs. Also many of the cognitive domains were affected, that is, specific aspects of phonological processing, reading compre-

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hension, and executive functions together with spelling and arithmetic. In our previous study with the same subjects, those with ADHD had lower FIQ and thus its effect was controlled for in the analyses of FA status [12]. The current correlative results emphasize further the importance of considering the role of FIQ in FA analyses. Fourthly, controlling for the sources of n-3 PUFAs affected only the relations between PUFAs, n-6 PUFAs, attention, most of the aspects of executive functions, and specific aspects of phonological processing. Little surprisingly, the relations between n-3 PUFAs and cognition were not affected. Taken together, these results suggest that the relations between the cognitive domains that characterize dyslexia or ADHD and especially n-3 PUFAs are different in males and females and those with especially n-6 PUFAs are different in the groups. Further, the relations between many FAs and cognition appear to vary with intelligence. Lastly, the relations of PUFAs, especially n-6 PUFAs, and cognition may be modulated by dietary intake of n-3 PUFAs.

4.4. Conclusions The membrane phospholipid hypothesis [14–16], magnocellular theory of dyslexia [27], and some single studies [54] suggest that dyslexia and ADHD are related to abnormalities in phospholipid or FA metabolism. In our previous study where we compared the FA status among the groups with this same sample [12] we could not rule out altered incorporation and loss of PUFAs from the cell membranes as an explanation for the observed differences [55,56]. Such PUFA imbalances are suggested to result in negative effects already during fetal neuronal migration and synaptogenesis and to affect neuronal connectivity, phospholipids in the cell membranes, and thus also cell size [33]. Based on this, we suggested [12] that the imbalances in FA status in these adult subjects with dyslexia and ADHD reflected factors that may have been present already during fetal development and resulted in altered neuronal connectivity and thereafter cognitive difficulties of the two conditions. The current associations in these same adults suggest that FAs are not related to cognition only during development. Instead, especially PUFAs appear to be related to the cognitive domains that characterize both ADHD and dyslexia. However, the associations between FAs and cognitive domains were not similar in subjects with ADHD and those with dyslexia.

Acknowledgements The authors thank Emma Hietarinta, Sasa Kivisaari, Minna Kuivalainen, Maisa Lehtinen, Mirva Reuhkala, and Meeri Sivonen for participating in gathering of the psychometric data and Kaija Kettunen for analyzing the fatty acids. All the authors participated in designing the experiment and writing the manuscript, PT and SL in collection of the data, ML and ATE in analysis of the data. References [1] R.K. McNamara, S.E. Carlson, Role of omega-3 fatty acids in brain development and function: potential implications for the pathogenesis and prevention of psychopathology, Prostaglandins Leukot. Essent. Fatty Acids 75 (2006) 329–349. [2] L. Lauritzen, H.S. Hansen, M.H. Jorgensen, K.F. Michaelsen, The essentiality of long chain n-3 fatty acids in relation to development and function of the brain and retina, Prog. Lipid Res. 40 (2001) 1–94. [3] B. Hallahan, M.R. Garland, Essential fatty acids and mental health, Br. J. Psychiatry 186 (2005) 275–277. [4] J.R. Marszalek, H.F. Lodish, Docosahexaenoic acid, fatty acid–interacting proteins, and neuronal function: breastmilk and fish are good for you, Annu. Rev. Cell Dev. Biol. 21 (2005) 633–657.

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