Genetic variants, neurocognitive outcomes, and functional neuroimaging in survivors of childhood acute lymphoblastic leukemia

Abstract

Background

Genetic predispositions may modulate risk for developing neurocognitive late effects in childhood acute lymphoblastic leukemia (ALL) survivors.

Methods

Long-term ALL survivors (n = 212; mean = 14.3 [SD = 4.77] years; 49% female) treated with chemotherapy completed neurocognitive testing and task-based functional neuroimaging. Based on previous work from our team, genetic variants related to the folate pathway, glucocorticoid regulation, drug metabolism, oxidative stress, and attention were included as predictors of neurocognitive performance, using multivariable models adjusted for age, race, and sex. Subsequent analyses evaluated the impact of these variants on task-based functional neuroimaging. Statistical tests were 2-sided.

Results

Survivors exhibited higher rates of impaired attention (20.8%), motor skills (42.2%), visuo-spatial memory (49.3%-58.3%), processing speed (20.1%), and executive function (24.3%-26.1%) relative to population norms (10%; P < .001). Genetic variants implicated in attention deficit phenotypes predicted impaired attention span (synaptosome associated protein 25, F_(2,172) = 4.07, P = .019) and motor skills (monoamine oxidase A, F_(2,125) = 5.25, P = .007). Visuo-spatial memory and processing speed varied as a function of genetic variants in the folate pathway (methylenetetrahydrofolate reductase [MTHFR_rs1801133], F_(2,165) = 3.48, P = .033; methylenetetrahydrofolate dehydrogenase 1 [MTHFD1_rs2236225], F_(2,135) = 3.8, P = .025; respectively). Executive function performance was modulated by genetic variants in the folate pathway (MTHFD1_rs2236225, F_(2,158) = 3.95, P = .021; MTHFD1_rs1950902, F_(2,154) = 5.55, P = .005) and glucocorticoid regulation (vitamin D receptor, F_(2,158) = 3.29, P = .039; FKBP prolyl isomerase 5, F_(2,154) = 5.6, P = .005). Additionally, MTHFD1_rs2236225 and FKBP prolyl isomerase 5 were associated with altered brain function during attention and working memory (P < .05; family wise error corrected).

Conclusions

Results extend previous findings of genetic risk of neurocognitive impairment following ALL therapy and highlight the importance of examining genetic modulators in relation to neurocognitive deficits.

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, with a peak incidence between the ages of 2 and 5 years (1). Survival rates and quality of life of survivors have considerably improved in recent decades by minimal residual disease–directed treatment and replacement of prophylactic cranial irradiation with a combination of risk-stratified intrathecal therapy, high-dose intravenous methotrexate (MTX), and dexamethasone (2,3). Despite reductions in treatment-induced neurocognitive late effects, ALL survivors treated on contemporary protocols remain at risk for atypical brain function (4-7). Survivors of pediatric ALL commonly display deficits in attention, processing speed, and executive function in the years following therapy (5). These neurocognitive deficits have a negative impact on academic attainment, employment, and quality of life (8,9). However, the degree of neurocognitive impairment varies among survivors, and some of the variation can be attributed to differences in the amount of exposure to neurotoxic agents, age at diagnosis, and/or sex (10). However, the influence of other inherent factors, particularly genetic predisposition, on neurocognitive outcomes remains poorly understood (11).

The anti-folate drug MTX is fundamental in treatment for ALL and is administered orally, intravenously, and intrathecally into the central nervous system. MTX inhibits methylation reactions dependent on folic acid, leading to an increase of homocysteine and oxidative stress (12). Prior research in ALL survivors has demonstrated that folate pathway variants (5,10-methylenetetrahydroreductase [MTHFR], methionine synthase [MS]) correlate with attention and processing speed deficits at the end of therapy and during long-term survivorship (≥5 years from diagnosis) (13,14). Similarly, MTHFR has been associated with a sevenfold increased risk for developing attention-deficit/hyperactivity disorder (ADHD) in ALL survivors (15).

Genetic variants related to glucocorticoid metabolism, oxidative stress, neuroinflammation, and drug metabolism (nitric oxide synthase 3, solute carrier organic anion transporter family member 2A1, catechol-O-methyltransferase) are relevant to ALL therapy and account for variance in intelligence (IQ), executive function, working memory, and attention in ALL survivors (16). Germline genetic variants related to cognitive function may also be relevant in explaining variation in neurocognitive outcomes among ALL survivors. For instance, monoamine oxidase (MAOA) and apolipoprotein E4 have been identified as risk factors for Alzheimer disease (17) and attention deficits in noncancer populations (18), and mediate attention problems in ALL survivors (13). Variation in these genes may modify associations between therapeutic exposures and risk for developing neurocognitive late effects during survivorship.

Although prior investigations have identified genetic variants associated with neurocognitive impairments following ALL therapy, these studies were either limited in the scope and depth of neurocognitive assessment, were conducted at the end of therapy prior to stable long-term outcomes, lacked a neuroimaging component, included a restricted range of genetic variants, or were conducted in a relatively small cohort of survivors who were treated on a variety of treatment protocols (13-16). This study aimed to address these limitations by exploring the impact of genetic variants on a wider variety of neurocognitive outcomes and brain activity in a relatively large cohort of long-term ALL survivors (n = 212) who were treated on the same protocol. First, we aimed to examine associations between genetic variants and neurocognitive function in long-term survivors of childhood ALL. Based on prior literature, candidate genetic variants were selected due to their established associations with folate physiology, glucocorticoid regulation, drug metabolism, oxidative stress, and cognitive impairments (13). Second, we explored the impact of genetic variants on brain activity in response to attention and working memory tasks to provide insight into the neural networks contributing to neurocognitive function in survivors.

Methods

Study population

Between 2000 and 2010, 408 children diagnosed with ALL were treated on the Total XV protocol at St. Jude Children’s Research Hospital (ClinicalTrials.gov, NCT0013711) (2). Survivors were eligible for the separate prospective neuroimaging study if they were aged 5 years or older, from diagnosis of ALL, English speaking, and aged 8 years or older at the time of study enrollment. Survivors were ineligible if they had received cranial radiation therapy, relapsed, had developed secondary neoplasms, had been diagnosed with a genetic disorder associated with cognitive impairments, or had a history of head trauma or neurological conditions (confirmed by a head trauma screening questionnaire and patients’ medical records) unrelated to cancer therapy (Supplementary Figure 1, available online). This study was approved by the institutional review board, and written informed consent was obtained from the participants and/or their legal guardians. Demographic variables including age, sex, and race were self-reported or provided by the legal guardian.

Total therapy XV

Children diagnosed with ALL were treated according to low-risk or standard- or high-risk treatment protocols (19). Patients treated with the low-risk protocol received fewer doses of triple intrathecal treatment with MTX, hydrocortisone, and cytarabine (13-18 vs 16-25), lower dosage of m² intravenous high-dose MTX (2.5 vs 5.0 gm/m²) for every other week for 4 courses as consolidation treatment, and lower dosage of dexamethasone pulses at 8 vs 12 mg/m² per day for 4 days per course for 25 courses compared with patients treated with the standard- or high-risk protocol. Serum concentrations of MTX were also obtained at 3 different time periods following intravenous administration (ie, 6, 23, and 42 hours post administration), and an average area under the curve was computed and included as a covariate in the analysis.

Genotyping

Using existing whole-genome sequencing data (20), genotypes of 39 genetic variants were selected a priori based on their established associations with the folate pathway, glucocorticoid regulation, drug metabolism, oxidative stress, and cognitive deficits (Supplementary Table 1, available online). Assay methods including SNAPSHOT, PCR, and PCR-RFLP were used to extract data for the targeted genetic variants. Genetic variants related to the folate pathway (n = 12) and glucocorticoids, drug metabolism, and oxidative stress (n = 15) were selected due to their relationship with MTX treatment and elevated homocysteine. Genetic variants related to attention and cognitive deficit phenotypes (n = 12) were selected due to the large proportion of ALL survivors who display attention problems, particularly at the end of therapy. Consistent with our previous work (13), the presence of major homozygous, minor homozygous, and heterozygous alleles was assessed for each genetic variant. To ensure adequate dispersion of the data, genetic variants with a small sample size (<10% of the total sample) were removed from the analysis.

Neurocognitive evaluation

Neurocognitive evaluations were administered by certified examiners under the supervision of a board-certified clinical neuropsychologist, and previously described in detail (5). Standardized clinical guidelines for cognitive evaluations were implemented to reduce interference, test order effects, and fatigue. The neurocognitive battery included standardized measures of intelligence (21), executive function (22), attention (23), processing speed (22), working memory (24), cognitive flexibility (25), visuo-spatial memory (26,27), and fine motor dexterity (Supplementary Materials, available online) (28). Neurocognitive impairment was defined as age-adjusted normative scores below the 10th percentile (Z ≤ 1.3).

Functional magnetic resonance imaging (fMRI)

fMRI was performed on 3 T scanners using a 14-channel standard head coil. The functional images were acquired using a single-shot T2*-weighted echo-planar imaging sequence (TR = 2.06 s; TE = 30 ms; FOV = 192 mm; matrix = 64 × 64; slice thickness = 5 mm). The T1-weighted images were acquired with a 3D MPRAGE imaging sequence (TR = 1.98 s; TE = 2.32 ms; TI = 1100 ms; resolution = 0.89 × 0.89 × 1.2 mm³) for registration. Image processing details and task parameters are in the Supplementary Materials (available online). An illustration of the fMRI tasks is depicted in Figure 1. The fMRI data were collected in a subset of participants (n = 151) within 7 days of the neurocognitive evaluations.

Figure 1.

Illustration of functional magnetic resonance imaging task paradigms. Task paradigms were presented in a 3 T scanner via Presentation software. Participants were instructed to respond via a hand-held device interfaced with the experimental computer. For the continuous performance task (top), participants were required to respond to every trial except when the letter X appeared on the screen to measure inhibitory control. The N-Back Task (bottom left) included 3 conditions: 0-back, 1-back, and 2-back. During the 0-back condition, participants responded to the letter X, and withheld their respond otherwise. On the 1-back condition, participants responded only if the letter on the screen was the same as the trial prior. Finally, for the 2-back, participants responded to trials where the letter on the screen was the same as the letter presented 2 trials earlier. For the attention network task (bottom right), participants were provided with center cue, spatial cue, or no cue and asked to respond to the direction of the center arrow.

Statistical analysis

Normative, age-standardized Z scores were calculated to evaluate neurocognitive performance. The first aim was to identify associations between neurocognitive outcomes and genetic variants (major homozygous, heterozygous, minor homozygous). Outcome measures (ie, dependent variables) were evaluated only if survivors exhibited an increased rate of impairment relative to the normative samples normative samples using 1-sample t test. Because neurocognitive impairments in ALL survivors are well established, we used a false discovery rate (FDR) of less than or equal to 10% as the threshold for significance for this step. Genetic variants (ie, independent variables) were first selected through univariate analyses with the previously identified cognitive outcomes, using a threshold of P < .05. Exploration of genetic associations of neurocognitive outcomes is the primary goal of the study; therefore, we used an uncorrected threshold to avoid type II error for this initial exploratory step. Subsequent multivariable models included neurocognitive outcomes as the dependent variables and relevant genetic variants (identified in previous univariate analyses), sex, race, and age at diagnosis as predictors. FDR was used as a threshold for interpreting the significance of the multivariable models. Folate pathway genes significantly associated with neurocognitive impairments were included in post hoc analyses to determine if cumulative MTX dose modulated the association.

Secondly, we evaluated if genetic variation was associated with brain activity (blood oxygen level–dependent [BOLD] signals) during attention and working memory. We initially examined univariate associations between neurocognitive performance, as measured with the standardized neurocognitive battery, and behavioral performance during the fMRI tasks. If an association was significant at FDR ≤ 10%, we selected the genetic variants demonstrated to be associated with the neurocognitive performance under the primary aim. These genetic variants were subsequently used to stratify group-level fMRI contrasts based on allele frequency. Given that there were fewer fMRI observations, we opted for a dominant genetic model where individuals with heterozygous and minor homozygous allele frequencies were combined into a single group and compared with individuals with major homozygous alleles to increase statistical power. Differences in group-level BOLD activity were compared using general linear models in Statistical Parametric Mapping (29) adjusting for age at evaluation, race, and sex. Voxel-level and cluster-level differences were deemed significant if P < .05 with a family-wise error (FWE) correction and a minimum cluster size of 5 voxels (T-threshold = 3.5). Statistical tests were 2-sided. If no significant differences in BOLD activity were detected at the cluster level, we reported voxel-wise thresholds for exploratory purposes.

Results

Sample

The demographic and treatment characteristics for 212 ALL survivors are provided in Table 1.

Table 1.

Demographic and clinical characteristics of the long-term ALL survivors^a

	Female	Male	Overall sample
	(n = 104)	(n = 108)	(n = 212)
Age at diagnosis, no. (%)
<5 y	59 (56.7)	46 (42.6)	105 (49.5)
≥5 y	45 (43.3)	62 (57.4)	107 (50.5)
Age at evaluation, y
Mean (SD)	13.8 (4.74)	14.8 (4.76)	14.3 (4.77)
Median [min, max]	12.3 [8.05, 26.5]	13.5 [8.21, 25.9]	13.2 [8.05, 26.5]
Years since diagnosis
Mean (SD)	7.5 (1.6)	7.8 (1.8)	7.7 (1.7)
Median [min, max]	7.5 [5.1, 11.6]	7.5 [5.1, 12.5]	7.5 [5.1, 12.5]
Race, no. (%)
Non-White	23 (22.1)	16 (14.8)	39 (18.4)
White	81 (77.9)	92 (85.2)	173 (81.6)
Risk category, no. (%)
Low	69 (66.3)	53 (49.1)	122 (57.5)
Standard/high	35 (33.7)	55 (50.9)	90 (42.5)
MTX cumulative dose
Mean (SD)	14428 (4480)	16188 (5322)	15325 (4994)
Median [min, max]	13245 [6072, 31915]	15803 [6304, 38968]	14268 [6072, 38968]
Total IT MTX injections, no.
Mean (SD)	13.6 (3.16)	15.6 (4.55)	14.6 (4.04)
Median [min, max]	12.0 [9.0, 23.0]	14.5 [9.0, 24.0]	13 [9.0, 24.0]

^aALL = acute lymphoblastic leukemia; IT MTX = intrathecal methotrexate; min = minimum, max = maximum.

Rates of neurocognitive impairment

Survivors demonstrated significantly higher impairment relative to the general population in executive function and processing speed (Delis-Kaplan Executive Function System [DKEFS]), attention (Wechsler Digits Forward Task), visuo-spatial memory (Rey-Osterrieth Complex Figure), and fine motor function (Grooved Pegboard Task) (Table 2).

Table 2.

Neurocognitive performance in ALL survivors

Measure	Variable	Mean	95% CI	No. Impaired	% Impaired	95% CI	t(df)	FDR
Rey	Copy	−2.37	−2.70 to −2.04	120	58.25	51.46 to 65.04	t(205) = 14.01	<0.001
	Immediate copy	−1.21	−1.40 to −1.01	101	49.27	42.37 to 56.17	t(204) = 11.22	<0.001
	Delayed copy	−1.28	−1.48 to −1.09	106	51.96	45.05 to 58.87	t(203) = 11.97	<0.001
WASI	Verbal IQ	−0.03	−0.16 to 0.10	22	10.73	6.46 to 15.00	t(204) = 0.34	1
	Performance IQ	−0.18	−0.29 to −0.07	19	9.18	5.21 to 13.14	t(206) = −0.41	1
	Full Scale IQ	−0.11	−0.23 to 0.02	21	10.24	6.06 to 14.43	t(204) = 0.11	1
	Vocabulary	−0.10	−0.24 to 0.05	28	13.66	8.92 to 18.40	t(204) = 1.52	1
	Block design	−0.23	−0.36 to −0.10	32	15.46	10.49 to 20.42	t(206) = 2.17	0.909
	Similarities	0.03	−0.11 to 0.16	22	10.73	6.46 to 15.00	t(204) = 0.34	1
	Matrix reasoning	−0.07	−0.20 to 0.05	22	10.63	6.39 to 14.86	t(206) = 0.29	1
WCST	Error	0.34	0.17 to 0.50	22	10.68	6.43 to 14.93	t(205) = 0.32	1
	Perseverative response	0.40	0.18 to 0.63	28	13.59	8.87 to 18.31	t(205) = 1.50	1
	Perseverative error	0.34	0.12 to .56	29	14.08	9.29 to 18.87	t(205) = 1.68	1
	Nonperseverative error	0.43	0.27 to 0.59	16	7.77	4.08 to 11.45	t(205) = −1.19	1
	Conceptual level response	0.31	0.15 to 0.47	18	8.74	4.85 to 12.63	t(205) = −0.64	1
CPT	Omissions	−0.30	−0.51 to −0.08	30	14.78	9.85 to 19.70	t(202) = 1.91	1
	Commissions	−0.17	−0.33 to −0.01	25	12.32	7.76 to 16.87	t(202) = 1.00	1
	Hit reaction time	−0.11	−0.26 to 0.04	26	12.81	8.17 to 17.44	t(202) = 1.19	1
	Hit standard error	−0.13	−0.30 to 0.03	32	15.76	10.71 to 20.82	t(202) = 2.25	0.77
	Variability of standard error	−0.14	−0.30 to 0.02	31	15.27	10.28 to 20.26	t(202) = 2.08	1
	D-Prime	−0.14	−0.30 to 0.02	21	10.34	6.12 to 14.57	t(202) = 0.16	1
	Beta	−0.07	−0.21 to 0.07	17	8.37	4.53 to 12.22	t(202) = −0.83	1
	Percentile	−0.43	−0.69 to −0.18	30	14.78	9.85 to 19.70	t(202) = 1.91	1
Wechsler	Digit span forward	−0.38	−0.52 to −0.25	43	20.77	15.20 to 26.35	t(206) = 3.81	0.00693
	Digit span backward	−0.28	−0.42 to −0.14	36	17.39	12.18 to 22.60	t(206) = 2.80	0.191
	Processing Speed Index	−0.27	−0.40 to −0.13	31	14.90	10.02 to 19.78	t(207) = 1.98	1
	Digit symbol	−0.41	−0.54 to −0.28	37	17.87	12.61 to 23.14	t(206) = 2.95	0.124
	Symbol search	−0.06	−0.20 to 0.08	28	13.46	8.78 to 18.14	t(207) = 1.46	1
	Spatial span forward	−0.19	−0.32 to −0.06	35	16.83	11.70 to 21.95	t(207) = 2.63	0.298
	Spatial span backward	−0.02	−0.16 to 0.11	25	12.08	7.60 to 16.55	t(206) = 0.91	1
DKEFS	20 question initial abstraction	−0.18	−0.32 to −0.04	37	18.05	12.74 to 23.36	t(204) = 2.99	0.113
	20 question total	−0.12	−0.25 to 0.02	30	14.63	9.76 to 19.51	t(204) = 1.87	1
	Color word read	−0.10	−0.23 to 0.03	23	11.27	6.90 to 15.65	t(203) = 0.57	1
	Color word inhibit	−0.16	−0.30 to −0.02	33	16.26	11.14 to 21.37	t(202) = 2.41	0.522
	Color word inhibit switch	−0.20	−0.34 to −0.06	29	14.36	9.48 to 19.23	t(201) = 1.76	1
	Tower test	−0.11	−0.22 to 0.01	21	10.10	5.97 to 14.22	t(207) = 0.05	1
	TMT number sequence	−0.20	−0.34 to −0.05	36	17.39	12.18 to 22.60	t(206) = 2.80	0.191
	TMT letter sequence	−0.35	−0.51 to −0.19	43	20.77	15.20 to 26.35	t(206) = 3.81	0.00693
	TMT number-letter switch	−0.52	−0.69 to −0.36	54	26.09	20.06 to 32.12	t(206) = 5.26	<0.001
	TMT motor speed	0.03	−0.10 to 0.16	26	12.56	8.01 to 17.11	t(206) = 1.11	1
	VF letter fluency	−0.38	−0.51 to −0.24	50	24.27	18.37 to 30.18	t(205) = 4.77	<0.001
	VF category fluency	0.01	−0.14 to 0.16	30	14.56	9.71 to 19.42	t(205) = 1.85	1
	VF category switch	−0.02	−0.14 to 0.11	22	10.68	6.43 to 14.93	t(205) = 0.32	1
GPB	Dominant hand	−1.31	−1.53 to −1.10	87	42.23	35.43 to 49.03	t(205) = 9.34	<0.001

^aMean scores and impairment rates are listed across outcome variables. The statistics quantify comparisons between impairment rates in survivors and expected impairment rates of normative samples (ie, 10%). ALL = acute lymphoblastic leukemia; CI = confidence interval; CPT = Conners Continuous Performance Test; DKEFS = Delis-Kaplan Executive Function System; GPB = Lafayette Grooved Pegboard Test; IQ = intelligence quotient; Rey = Rey-Osterrieth Complex Figure; TMT = Trail Making Task; VF = Verbal Fluency; WASI = Wechsler Abbreviated Scale of Intelligence; WCST = Wisconsin Card Sorting Test; Wechsler = Weschler Intelligence Scale for Children.

Impact of genetic variation on neurocognitive performance

Associations between genetic variants and neurocognitive performance are presented in Table 3, with significant associations between genetic variants and neurocognitive outcomes visualized in Figure 2.

Table 3.

Genetic variation and neurocognitive function among survivors of childhood ALL

Dependent variable	Independent variable	Contrasts
		Levels	Estimate (STE)	P	FDRa
Grooved pegboard (dominant hand)	Age at diagnosis	<5 y vs ≥5 y	0.200 (0.256)	0.434	1.000
	Sex	Female vs male	−0.247 (0.274)	0.370	1.000
	Race	Non-White vs White	0.805 (0.321)	0.013	0.080
	APOE4 rs429358	Major vs hetero	0.519 (0.293)	0.079	0.476
	MAOA rs1137070	Major vs hetero	−0.675 (0.311)	0.032	0.191
		Major vs minor	−1.068 (0.364)	0.004	0.024
	SNAP25 rs10513112	Major vs hetero	0.588 (0.291)	0.046	0.274
		Major vs minor	0.133 (0.401)	0.741	1.000
	VDR rs1544410	Major vs hetero	−0.326 (0.279)	0.245	1.000
		Major vs minor	−0.051 (0.377)	0.892	1.000
DKEFS trail making task (number letter switching)	Age at diagnosis	<5 y vs ≥5 y	0.045 (0.176)	0.800	1.000
	Sex	Female vs male	−0.388 (0.182)	0.034	0.207
	Race	Non-White vs White	0.679 (0.234)	0.004	0.026
	DRD2 rs6277	Major vs hetero	0.206 (0.205)	0.318	1.000
		Major vs minor	0.500 (0.283)	0.079	0.472
	FKBP5 rs1360780	Major vs hetero	0.250 (0.184)	0.177	1.000
		Major vs minor	−0.754 (0.303)	0.014	0.083
	MTHFD1 rs1950902	Major vs hetero	0.346 (0.192)	0.073	0.438
		Major vs minor	1.317 (0.434)	0.003	0.017
DKEFS trail making task (letter sequencing)	Age at diagnosis	<5 y vs ≥5 y	0.188 (0.188)	0.319	1.000
	Sex	Female vs male	−0.105 (0.188)	0.579	1.000
	Race	Non-White vs White	0.532 (0.263)	0.045	0.271
	FKBP5 rs1360780	Major vs hetero	0.308 (0.227)	0.177	1.000
		Major vs minor	0.0003 (0.395)	0.999	1.000
	FKBP5 rs9470080	Major vs hetero	0.252 (0.225)	0.266	1.000
		Major vs minor	−0.310 (0.376)	0.411	1.000
	MTHFD1 rs2236225	Major vs hetero	−0.014 (0.209)	0.948	1.000
		Major vs minor	−0.715 (0.285)	0.013	0.080
	MTHFR rs1801131	Major vs hetero	−0.219 (0.193)	0.259	1.000
		Major vs minor	0.372 (0.350)	0.290	1.000
Wechsler (digits forward task)	Age at diagnosis	<5 y vs ≥5 y	0.199 (0.147)	0.178	1.000
	Sex	Female vs male	−0.398 (0.145)	0.007	0.040
	Race	Non-White vs White	0.199 (0.189)	0.293	1.000
	FPGS rs10760502	Major vs hetero	0.233 (0.159)	0.144	0.864
		Major vs minor	0.551 (0.243)	0.024	0.146
	SNAP25 rs3746544	Major vs hetero	−0.083 (0.177)	0.640	1.000
		Major vs minor	0.409 (0.172)	0.019	0.111
DKEFS (verbal fluency task)	Age at diagnosis	<5 y vs ≥5 y	−0.387 (0.229)	0.014	0.086
	Sex	Female vs male	−0.139 (0.156)	0.374	1.000
	Race	Non-White vs White	0.013 (0.199)	0.946	1.000
	MTHFD1 rs2236225	Major vs hetero	0.425 (0.171)	0.014	0.083
		Major vs minor	−0.039 (0.238)	0.872	1.000
	VDR rs1544410	Major vs hetero	−0.441 (0.172)	0.011	0.068
		Major vs minor	−0.233 (0.230)	0.311	1.000
Rey-Osterreith complex figure (delayed recall task)	Age at diagnosis	<5 y vs ≥5 y	−0.008 (0.215)	0.972	1.000
	Sex	Female vs male	−0.107 (0.214)	0.618	1.000
	Race	Non-White vs White	0.462 (0.275)	0.095	0.568
	MTHFR rs1801133	Major vs hetero	−0.031 (0.231)	0.893	1.000
		Major vs minor	0.854 (0.352)	0.016	0.097

^aALL = acute lymphoblastic leukemia; DKEFS = Delis-Kaplan Executive Function System. False discovery rate (FDR) was adjusted for the total number of multivariable models that were conducted, that is, 6 models.

Figure 2.

Statistically significant associations between genetic variants and neurocognitive performance in acute lymphoblastic leukemia survivors. Genes and neurocognitive outcomes are listed in the facets at the top of each panel. The y-axes show predicted Z-scores. Means and 95% confidence limits are shown for major homozygous (major), heterozygous (hetero), and minor homozygous (minor) alleles (x-axes). Estimated means were derived from multivariable models adjusted for age at diagnosis and sex, and for other single nucleotide polymorphisms that were associated with the outcome measure at the univariate level. The horizontal lines mark Z = 0, or the normative mean.

Executive function was measured using DKEFS number–letter switching and verbal fluency. Figure 2A illustrates that performance on the former varied significantly as a function of genetic variants involved in glucocorticoid regulation (FKBP5_rs1360780; VDR _rs1544410) and folate metabolism (MTHFD1_rs1950902; MTHFD1_rs2236225). Individuals with minor alleles for FKBP5 had lower scores than those with major or heterozygous alleles (F_(2,154) = 5.60, P = .005). For MTHFD1, those with major alleles had poorer executive function than those with heterozygous alleles (F_(2,154) = 5.55, P = .005). Survivors who expressed heterozygous alleles on MTHFD1_rs2236225 had higher scores on measures of verbal fluency than the other groups (F_(2,158) = 3.95, P = .021). Further, VDR _rs1544410, which regulates glucocorticoid expression, predicted verbal fluency with major allele carriers displaying better performance (F_(2,158) = 3.29, P = .039) (Figure 2B).

Fine motor skills, as assessed by the grooved pegboard task, varied as a function of MAOA_rs1137070, with major allele carriers displaying better fine motor scores than those expressing heterozygous alleles or minor alleles (F_(2,125) = 5.25, P = .007) (Figure 2C).

Processing speed, as measured using DKEFS letter sequencing, was significantly associated with MTHFD1_rs2236225, a folate pathway gene, which was primarily driven by lower scores of the minor allele group than the other groups (F_(2,135) = 3.8, P = .024) (Figure 2D).

Figure 2E shows that attention, as measured using the digit span forward task, was associated with SNAP25_rs3746544 (ie, gene associated with cognitive impairments), with minor allele carriers performing better than those with major or heterozygous alleles (F_(2,172) = 4.07, P = .019). Digit span was also associated with folate pathway-related gene, FPGS_rs10760502 (F_(2,172) = 2.99, P = .05), with minor allele carriers performing better than major allele carriers. However, neither of these associations reached significance when accounting for multiple comparisons (Table 3).

Finally, Figure 2F visualizes associations between visuo-spatial memory scores based on the Rey-Osterrieth Complex Figure task and folate pathway gene MTHFR_rs1801133, with minor allele carriers displaying better performance than the other groups (F_(2,165) = 3.48, P = .033).

Post hoc interactions between folate genes and MTX

The interaction between MTHFD1_rs2236225 and MTX dose predicted verbal fluency performance (estimate = 0.945, 95% confidence interval = 0.001 to 1.890, P = .050; Figure 3; Supplementary Table 2, available online), where poor performance on the task was exacerbated among survivors who expressed the minor alleles and had been exposed to higher doses of MTX. No other significant treatment interactions were identified.

Figure 3.

Interaction between methylenetetrahydrofolate dehydrogenase (MTHFD1_rs12236225) and methotrexate (MTX) dose (low or medium vs high) predicting verbal fluency. Means and 95% confidence limits are shown to illustrate that poor performance on the task was exacerbated among survivors who expressed the minor alleles and had been exposed to higher doses of methotrexate. DKEFS = Delis-Kaplan Executive Function System; Hetero = heterozygous allele; Major = major homozygous allele; Minor = minor homozygous allele.

Functional neuroimaging

Supplementary Table 3 (available online) summarizes the univariate association analyses between neurocognitive measures and behavioral performance on the fMRI tasks. We evaluated the impact of 6 genetic variants (FKBP5_rs1360780, MAOA_rs1137070, MTHFD1_rs1950902, MTHFD1_rs2236225, MTHFR_rs1801133, and SNAP25_rs3746544) on brain activity during attention and working memory tasks.

Three genetic variants significantly corresponded with altered BOLD activity. For the attention network task measure of attention, the presence of minor and heterozygous alleles on folate pathway gene MTHFD1_rs2236225 was associated with reduced activity in the caudate nucleus, basal ganglia, and inferior front gyrus opercular region during cognitive flexibility trials (Figure 4). Results from the attention network task represent cluster-level statistical differences in BOLD activity (P = .005, FWE correction).

Figure 4.

Genetic mediators of functional magnetic resonance imaging (fMRI) activity among childhood acute lymphoblastic leukemia survivors. Group-level fMRI contrasts during the N-Back and attention network tasks based on genetic variants. Individuals with heterozygous and minor homozygous alleles (HeteroMinor) were compared with major homozygous alleles (Major) using multivariable analyses adjusted for age at evaluation and sex. Differences in brain activity were statistically significant for family wise error–corrected P values less than .05. Blood oxygen level–dependent (BOLD) activation differences were observed in A) the left angular gyrus; B) right supramarginal gyrus; C) right orbital inferior frontal gyrus and supramarginal gyrus; and D) left caudate nucleus, basal ganglia, and inferior frontal gyrus.

Additionally, FKBP5_rs1360780, MTHFD1_rs1950902, and MTHFD1_rs2236225, which are involved in glucocorticoid regulation and folate metabolism, were related to BOLD activation during the n-back task measure of working memory. Participants with minor and heterozygous alleles for FKBP5 (glucocorticoid regulating gene) and MTHFD1_rs2236225 exhibited increased BOLD activity in the left angular gyrus (P = .04, FWE correction) during increased working memory load (2-back vs 1-back) and increased BOLD activity in the right orbital frontal (P = .014, FWE correction) and middle temporal gyrus (P = .025, FWE correction) during the highest level of working memory load (2-back vs 0-back). By contrast, the presence of minor and heterozygous alleles for MTHFD1_rs2236225 was associated with reduced activity in the right supramarginal gyrus during the lowest level of working memory load (1-back vs 0-back; P = .043, FWE correction). Although no cluster-level differences were observed for the n-back task, voxel-level statistical differences in BOLD activity were observed (P < .05, FWE correction) (Figure 4).

There were no statistically significant associations between genetic variants and BOLD activity for the continuous performance test (CPT).

Discussion

Our results suggest that certain genetic predispositions may modulate neurocognitive late effects and associated changes in brain function following ALL therapy. We discuss our findings in the context of gene-specific pathways.

 

Genetic variants in the folate pathway are associated with the efficacy of MTX and homocysteine levels (30). Expression of both minor alleles for MTHFD1_rs2236225 was associated with poor performance on executive function and processing speed, and major alleles for MTHFD1_rs1950902 was associated with poorer executive function. These seemingly contrasting findings may be explained by differences in functional brain activity underlying different cognitive processes. Our neuroimaging data support the notion of altered brain function due to genetic variation in folate genes. Expressing the minor or heterozygous alleles for MTHFD1_rs1950902 was associated with decreased brain activity in the right supramarginal gyrus and orbital inferior frontal gyrus during working memory compared with those expressing major alleles. By contrast, minor or heterozygous alleles for MTHFD1_rs223622 corresponded with increased brain activation in the left caudate nucleus, basal ganglia, and inferior frontal gyrus during an attention task and in the right supramarginal gyrus during working memory, relative to those with major alleles. Reductions in basal ganglia activity are related to frontal-posterior connectivity during attention shifting (31), and reduced volume has been noted in children with ADHD (32). Unlike previous research conducted during early survivorship (15), we did not observe direct associations between folate genetic variants and attentional processes (ie, sustained and selective attention). However, executive function and working memory are critically dependent on the ability to alternate, allocate, and divide attentional processes (33). It is possible that subtle impairments in attention processes have downstream consequences on executive function and memory, which were impaired in this study. These findings suggest that folate genes affect different aspects of neurocognitive late effects in survivors, and time off-therapy may modulate this association. Our post hoc analyses further implied that MTX dose may exacerbate the negative impact of folate-related genetic predispositions on neurocognitive performance.

 

Glucocorticoid receptors regulate the stress response of the central nervous system (34). These receptors modulate expression of genes involved in the development and metabolism of innate immune responses by upregulating the expression of proinflammatory cytokines in the nucleus or suppressing inflammatory responses in the cytosol. We observed novel associations between executive function and FKBP5_rs1360780, with minor allele carriers having the greatest impairment. Genetic variation on FKBP5_rs1360780 has been linked with altered stress response of the hypothalamic-pituitary-adrenal axis (35). Survivors expressing the minor or heterogenous allele exhibited reduced activity in the left angular gyrus compared with individuals with major alleles. fMRI studies in noncancer populations, including patients with traumatic brain injury and posttraumatic stress disorder, have likewise demonstrated an association between FKBP5 variation and altered brain function (36,37). These findings imply that disrupted stress responses and related genetic contributions may lead to alterations in functional brain activity underlying executive dysfunction in ALL survivors.

 

While previous work demonstrated that MAOA modulated attention and memory, we observed associations between MAOA and motor function. Notably, survivors’ motor skills were compromised regardless of genetic predispositions because the highest performing subgroups still scored well below the normative mean. Nonetheless, survivors expressing the minor allele on MAOA_rs1137070 experienced greater difficulties in fine motor skills than those expressing the major or heterozygous allele. Variation in MAOA_rs1137070 has been linked with risk of ADHD in noncancer populations, who often exhibit impaired motor control (38-40). The MAOA gene contributes to the catabolism of neurotransmitters, including dopamine, which plays an essential role in motor function and processing speed (41-43). Disruptions in the dopaminergic system by means of MAOA genetic risks may contribute to fine motor deficits in ALL survivors.

The major allele of SNAP25_rs3746544 has also been associated with elevated risk of ADHD (39,44). As expected, ALL survivors who expressed major or heterozygous alleles had poorer attention spans than survivors who expressed the minor alleles. Similar findings have been noted in noncancer populations (45,46). The SNAP25_rs3746544 gene encodes a protein that regulates synaptic vesicle fusion and neurotransmitter release. Disruptions to the SNAP25 protein can impede presynaptic function and contribute to neurocognitive deficits (46). Survivors who express the major alleles may be at greater risk for attention deficits following ALL therapy, and precautions should be taken into account to help mitigate these effects.

The interpretation of the results should be considered within several study limitations. First, we used a candidate gene approach to accommodate the modest sample size. This limitation was compounded by our use of complete case multivariable modeling. Nonetheless, we observed robust neurocognitive associations among the genes with sufficient dispersion. Second, data were acquired on 2 types of MRI scanners. Because both MRIs were developed by the same manufacturer, had the same magnet strengths, and ran the same acquisition protocols, homogeneous data were collected. Third, survivors received vincristine, which is associated with peripheral neuropathy and subsequent problems on fine motor tasks. Only 3 survivors endorsed this problem at the time of neurocognitive evaluation. We therefore postulate that neuropathy had minimal impact on performance on fine motor performance in this sample. Further, the verbal fluency task that was used to assess executive function relies on language processing, which may affect neurocognitive performance (47). Lastly, a dominant genetic model was used for the fMRI portion of this study to increase statistical power. Although the dominant model lacks the specificity of an additive model, valuable information is still obtained to guide future work on the impact of genetic variation on brain activity following ALL therapy.

The present study adds to a growing literature of risk factors that contribute to neurocognitive outcomes following ALL therapy (48). Findings from this study may be used to inform clinicians about the importance of identifying genetic predispositions that increase susceptibility to the neurotoxic effects of contemporary ALL therapy. Early genetic screening should be implemented, when possible, to help identify patients at greater risk for long-term neurocognitive deficits. Treatment modifications or posttherapy interventions could be adjusted, based on certain genetic phenotypes, to help mitigate neurocognitive late effects. Our results also provide insight into the potential mechanisms of neurocognitive difficulty following chemotherapy, which may be useful for developing preventative strategies for patients with genetic risk factors that exacerbate neurocognitive difficulties.

Data availability

The data supporting this article will be shared upon request to the corresponding author.

Author contributions

Kellen Gandy, PhD (Conceptualization; Data curation; Formal analysis; Methodology; Visualization; Writing – original draft; Writing – review & editing), Yadav Sapkota, PhD (Methodology; Writing – review & editing), Matthew A. Scoggins, PhD (Methodology; Writing – review & editing), Lisa M. Jacola, PhD (Writing – review & editing), Timothy R. Koscik, PhD (Writing – review & editing), Melissa M. Hudson, MD (Writing – review & editing), Ching-Hon Pui, MD (Writing – review & editing), Kevin R. Krull, PhD (Conceptualization; Funding acquisition; Methodology; Supervision; Writing – review & editing), Ellen van der Plas, PhD (Conceptualization; Data curation; Formal analysis; Methodology; Visualization; Writing – original draft; Writing – review & editing).

Funding

This work was supported by the National Cancer Institute at the National Institutes of Health T32 Institutional Research Training Grant (T32 CA225590 to KRK), National Institute of Mental Health (MH085849 to KRK), National Cancer Institute (CA195547 to MMH and KN; CA021765 to CR), and by the American Lebanese Syrian Associated Charities (ALSAC).

Conflict of interest

The authors report no conflict of interest or disclosures.