Introduction
The concept of The Developmental Origins of Health and Disease states that early-life environmental exposures may influence an individual’s behaviours and health in adulthood. Reference Gluckman, Buklijas and Hanson1 For example, maternal care and malnutrition are well-established as being associated with later-life mental health and metabolism. Reference Caldji, Tannenbaum, Sharma, Francis, Plotsky and Meaney2,Reference Tamashiro and Moran3 Early-life light exposure has also been suggested to predispose towards health issues in adulthood. Epidemiological studies have found that season of birth is associated with psychiatric conditions, Reference Castrogiovanni, Iapichino, Pacchierotti and Pieraccini4 allergies, Reference Boland, Shahn, Madigan, Hripcsak and Tatonetti5 cardiovascular diseases, Reference Zhang, Devore, Strohmaier, Grodstein and Schernhammer6 cancer, Reference Lewis, Hellmich and Fritschi7 metabolic problems Reference Kahn, Morgan and Case8 and mortality. Reference Doblhammer and Vaupel9 The Perinatal Light Imprinting of Circadian Clocks and Systems (PLICCS) hypothesis suggests that environmental light exposure may disrupt the development of biological rhythms which in turn influence later-life health. Reference Lewis and Erren10 In line with this, day length at birth was associated with chronotype, which is the timing preferences of daily behaviours and which represents the biological rhythm of an individual. Reference Didikoglu, Maharani, Payton, Pendleton and Canal11,Reference Natale and Adan12 Moreover, animal models have shown that seasonal daylight duration can modify developing circadian clocks. Reference Ciarleglio, Axley, Strauss, Gamble and McMahon13 If mice are reared under a summer solstice-like (16 h light:8 h dark) photoperiod environment, the period of their circadian rhythm of gene expression, the period of their free-running activity rhythm in constant darkness and the period of individual neurons of their principal pacemaker, the suprachiasmatic nucleus (SCN) in the brain, all become shorter in adulthood compared to animals reared under a winter solstice-like (8 h light:16 h dark) environment. Reference Ciarleglio, Axley, Strauss, Gamble and McMahon13
Epigenetic regulations are highly dynamic during embryonic and postnatal development, and it has been hypothesised that early-life programming is due to lasting epigenetic remodelling during development. Reference Feil and Fraga14 Season of birth effects may also include early-life epigenetic programming. In the hippocampus and olfactory bulb of mice, long day length was associated with lower concentrations of total 5-Methylcytosine and DNA methyltransferase (DNMT) transcription, and higher DNA hydroxymethylation and Ten-eleven translocation (TET2) transcription, which is an indicator of DNA demethylation. Reference Takaki, Uchiwa, Furuse and Yasuo15 SCN genome-wide DNA methylation and transcription were compared between 22- and 26-hour day length entrained mice. Reference Azzi, Dallmann and Casserly16 Differently methylated DNA regions were enriched in pathways of synapse formation, neuroendocrine system, axon pathfinding and neurophysiology. Reference Azzi, Dallmann and Casserly16 A methyltransferase inhibitor drug prevented adaptation to day length cycle. Reference Azzi, Dallmann and Casserly16 This study is important as it provides evidence supporting circadian epigenetic programming in the mammalian SCN during entrainment to new period length. However, the effect of seasonal day length on epigenetics of the SCN is still largely unknown. In the only human study, blood samples from 367 individuals (age 18) were analysed for global methylation variations in relation to their season of birth. Reference Lockett, Soto-Ramírez and Ray17 Allergic diseases were found associated with autumn-born participants in this cohort, and 92 seasonal differentially methylated CpG sites were identified, two of which were causally associated with allergy. Reference Lockett, Soto-Ramírez and Ray17 Involvement of seasonal epigenetic programming in PLICCS has not been characterised in the human hypothalamus.
In this study, we investigate epigenome-wide DNA methylation differences associated with seasonal photoperiod at birth in the human hypothalamus, which includes biological rhythm and sleep centres, and the inferior temporal gyrus (ITG), which has previously been reported as a candidate brain region for season of birth effect in a brain imaging study. Reference Didikoglu, Canal, Pendleton and Payton18
Methods
Subjects and sample preparation
Subjects in this study were participants of The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age (UMLCHA) cohort. Reference Rabbitt, McInnes and Diggle19 Starting in 1983, this study recruited 6375 healthy individuals without dementia aged between 40 and 90 years. The participants were followed for up to 35 years for changes in self-reported health, cognition, demographics and lifestyle data including diurnal sleeping habits Reference Didikoglu, Maharani, Payton, Pendleton and Canal11 under the approval of The University of Manchester research ethics committee with written consent from all participants. Participants were approached in 2003 for consent to brain donation and 312 individuals agreed to donate their brain after death. Reference Robinson, Davidson, Horan, Pendleton and Mann20 One hemisphere of the postmortem brains was fresh frozen at −80°C and is stored by The Manchester Brain Bank (https://www.bmh.manchester.ac.uk/research/domains/neuroscience-mental-health/manchester-brain-bank), which has ethical approval to distribute tissue and data to researchers. The present study was approved by the Manchester Brain Bank Management Committee (REC reference 19/NE/0242; application number TR83).
Amongst the donated brains, only 16 samples had intact hypothalamus and ITG regions because of tissue sectioning and storing procedures, and usage of the tissues in other studies. These 16 individuals were unrelated with 10 being female. The demographic and brain pathology data of subjects are summarised in Table S1. Hypothalamic tissue blocks were cut into sections with 300 µm thickness using a cryostat (Leica CM 1950). ITG tissue blocks and hypothalamic sections were stored in a −80°C freezer until use. The hypothalamus region was identified by means of a human brain atlas, Reference Mai, Paxinos and Voss21 and 10 punches (1 mm diameter) per participant were obtained. From the ITG tissue blocks, 30–50 mg of tissue was cut. Genomic DNA was isolated with a PureLink Genomic DNA mini kit (Invitrogen, USA). Agarose gel electrophoresis was performed to confirm that DNA was not degraded. For all participants, quantity of extracted DNA was verified to be >500 ng. Bisulphite conversion of DNA was performed using the EZ DNA Methylation™ Kit, following the manufacturer’s protocol (Zymo Research, USA). Epigenome-wide methylation analysis was conducted using the Infinium MethylationEPIC BeadChip using the protocol provided by the manufacturer (Illumina Inc., USA). The arrays were scanned using the iScan System, and signal intensities were recorded as IDAT files by GenomeStudio (Illumina Inc., USA).
Data filtering
Quality control and analyses were carried out in R version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria). IDAT files were imported and preprocessed using the R package minfi (version 1.34.0). Reference Aryee, Jaffe and Corrada-Bravo22 Two ITG samples were excluded because their mean detection P-values were above 0.01. Sex chromosomes were removed from the analysis. Probes that had a mean detection P-value above 0.01 were also excluded. Probes which were cross reactive, or which contained a single nucleotide polymorphism (SNP) on the CpG of interest, were removed. Reference Chen, Lemire and Choufani23 Genomic locations were reported in Genome Reference Consortium Human Build 37 (GRCh37). After quality control, 771,382 CpG probes in 30 samples remained. β-values, the ratio of methylated intensity to total intensity, and M-values, the logit transformed β, were calculated and normalised using SWAN. Reference Maksimovic, Gordon and Oshlack24 Density plots of β-values were controlled for bimodal distributions (Fig. S1). Principal component analysis was performed using the R package pcaMethods (version 1.80.0) to identify potential confounders such as batch effect and tissue type. Reference Stacklies, Redestig, Scholz, Walther and Selbig25 Cell type heterogeneity was inspected using the R packages RefFreeEWAS (version 2.2.0) Reference Houseman, Kile, Christiani, Ince, Kelsey and Marsit26 and FlowSorted.DLPFC.450k (version 1.24.0). Reference Jaffe and Kaminsky27
Epigenome-wide association analysis
Linear models were calculated to examine differentially methylated probes (DMPs) between hypothalamus and ITG using the R package limma (version 3.44.3). Reference Ritchie, Phipson and Wu28 Since different tissue samples were taken from the same individual, a paired analysis was performed to adjust within-individual differences. P-values were adjusted for multiple testing using the Benjamini and Hochberg method to control the false discovery rate (FDR). Significant hypothalamus-specific methylation profiles (FDR < 0.05) were compared with human lateral hypothalamus DNA methylation, Reference Shimada, Miyagawa and Takeshima29 human hypothalamus gene expression in The Genotype-Tissue Expression (GTEx) database, Reference Aguet, Brown and Castel30 and mice suprachiasmatic nucleus gene expression Reference Brown, Williams and Taylor31 using Spearman’s correlation (Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.).
Season of birth was categorised as long photoperiod (LP), March 21–September 22, and short photoperiod (SP), September 23–March 20. Postmortem brains from 8 SP-born and 8 LP-born subjects were used in this study. Linear models were fitted to find DMPs in season of birth groups. Two separate models were fitted for hypothalamus and ITG. Sex and age at death were included as covariates in the models. DMPs with adjusted P-value < 10−5 were accepted as a suggestive association. Power calculations for DNA methylation studies using the Illumina EPIC microarray were performed using the University of Essex EPIC Array Power Calculations. Reference Mansell, Gorrie-Stone and Bao32 In addition, probes that had a log2 fold change (logFC) >3 or <−3 were further investigated. Differentially methylated regions (DMR), where neighbouring CpGs are differentially methylated, were calculated using the R package DMRcate (version 2.2.2). Reference Peters, Buckley and Statham33
Season of birth-associated CpGs and chronotype
With season of birth being correlated with later-life midsleep time, Reference Didikoglu, Maharani, Payton, Pendleton and Canal11 we investigated whether nominally CpGs associated with season of birth predict later-life sleep time. Self-reported sleep timing data were available for 15 subjects. Midsleep time, a measure of chronotype, was used as an outcome for the linear regression model. Candidate CpGs (P < 10−5 or P < 0.05, logFC < −3, logFC > 3) were included in the regression models as the main predictor, adjusted for age and sex. P-value below 0.0017 was accepted as significant with Bonferroni correction of multiple testing.
Pathway analysis and correlations with previous findings
The top 1000 CpGs in terms of logFC from the season of birth epigenome-wide results were tested for potential enrichment in biological pathways, molecular function or cellular components using the Gene Ontology database. Reference Ashburner, Ball and Blake34 The pathway analysis was performed using the R package missMethyl (version 1.22.0) with a P-value threshold <10−5 used to determine statistical significance. Reference Phipson, Maksimovic and Oshlack35
Hypothalamus and ITG methylation profiles that were related to season of birth in this study were compared with previously reported season of birth DNA methylation in blood Reference Lockett, Soto-Ramírez and Ray17 using Spearman’s correlation (Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.). In addition, overlapping methylated CpGs between our season of birth methylation (P < 0.05) and season of birth-associated disorders (Frontal cortex DNA methylation in schizophrenia Reference Jaffe, Gao and Deep-Soboslay36 and Lateral Hypothalamus DNA methylation in narcolepsy Reference Shimada, Miyagawa and Takeshima29 ) were investigated using a chi-squared test.
Candidate probes were further investigated for their association with other phenotypes using the EWAS Atlas. Reference Li, Zou and Li37 Our candidate probes were also compared with primate brain diurnal or seasonal gene expression and DNA methylation, Reference Mure, Le and Benegiamo38,Reference Lim, Klein and Yu39 fetal and early-life DNA methylation in blood and brain, Reference Jaffe, Gao and Deep-Soboslay36,Reference Spiers, Hannon and Schalkwyk40,Reference Pérez, Santamarina and Tejedor41 and season of birth-associated placenta gene expression. Reference Clarkson-Townsend, Kennedy and Everson42
MeQTL analysis
Blood samples of the UMLCHA cohort were previously genotyped and imputed to The Haplotype Reference Consortium. Reference Didikoglu, Maharani, Canal, Pendleton and Payton43 A total of 15 subjects had both DNA methylation and genotype data. Using PLINK v2, SNPs located within 1 million bases around the CpGs that had P-value <10−5 were extracted. Cis-acting methylation quantitative trait loci (meQTL) were investigated using the R package MatrixEQTL (version 2.3.0) with a P-value threshold <10−5 to determine statistical significance. Reference Shabalin44 In addition, previously reported meQTLs in the developing human brain were investigated for our candidate loci. Reference Hannon, Spiers and Viana45
Technical replication using pyrosequencing
Amongst the strongest associated CpG regions, four hypothalamus probes (cg12323699, cg18445760, cg12833267 and cg25628433) and four ITG probes (cg01839373, cg03370588, cg16402757 and cg14859874) were selected as target regions for technical replication using pyrosequencing. Predesigned PyroMark CpG Assays for validating results from Infinium MethylationEPIC BeadChip arrays were used (Qiagen, Germany). Before pyrosequencing, PCR amplification was performed using 10 ng of bisulphite-converted DNA and the PCR product was cleaned using Streptavidin Sepharose High Performance Beads (GE Healthcare, UK). Pyrosequencing was performed using PyroMark Q24 (Qiagen, Germany). β-values from epigenome-wide arrays were compared with the methylation percentage from pyrosequencing using Spearman’s correlation.
Results
Tissue validation
Average age at death was 88.56 (SD = 5.49) years, and average postmortem delay of brain removal was 92.78 (SD = 45.62) hours. We performed principal component analysis using all 30 samples, and the first three principal components were used to separate tissue types (Fig. S2). We identified 37,402 hypermethylated and 81,832 hypomethylated probes that were significantly (adjusted P < 0.05) different between the hypothalamus and ITG (Table S2: https://doi.org/10.48420/14679996). Tissue-specific DMPs in our results positively correlated (Spearman’s Rho = 0.64; P < 0.0001; N = 115,124) with DMPs specific to the lateral hypothalamus compared to the temporal cortex Reference Shimada, Miyagawa and Takeshima29 (Fig. S2). Furthermore, tissue-specific DMPs located upstream of genes (5’UTR, TSS200, TSS1500), which may include promoter regions, were negatively correlated (Spearman’s Rho = −0.31; P < 0.0001; N = 7078) with gene expression differences between human hypothalamus and cortex Reference Aguet, Brown and Castel30 (Fig. S2). Similarly, these DMPs estimated downregulated gene expression (Spearman’s Rho = −0.22; P < 0.0001; N = 2355) in mice hypothalamic SCN compared to whole brain Reference Brown, Williams and Taylor31 (Fig. S2).
Cellular heterogeneity
Since brain samples include different cell types, association analysis may be confounded. Therefore, we used a reference-free deconvolution method to predict cell type proportions using methylation profiles. The estimation revealed that there were two main cell types in the tissue. A proportion of neural cells was subsequently estimated using publicly available data, FlowSorted.DLPFC.450k (version 1.24.0). Reference Jaffe and Kaminsky27 One of the two estimated cell types clustered with neural cells, while the other type clustered with non-neural cells. We found the estimated proportion of neurons to be higher in ITG (26%) compared to hypothalamus (18%) (P = 5.4 × 10−3). The higher glia:neuron ratio of the hypothalamus compared to cortex has been previously shown in primates. Reference Roberts, Killiany and Rosene46 The proportion of neurons did not significantly differ between SP and LP season of birth groups (Fig. 1) in the hypothalamus (P = 0.33) and ITG (P = 0.78).
Fig. 1. Comparisons of the estimated proportions of (a) neurons and (b) non-neurons between season of birth groups in the hypothalamus and inferior temporal gyrus (ITG). SP, Short photoperiod season of birth; LP, Long photoperiod season of birth.
Season of birth and DNA methylation
There was no evidence of epigenome-wide significant (FDR < 0.05) DMP for any tissue (Table S3: https://doi.org/10.48420/14680170, Table S4: https://doi.org/10.48420/14680281, Fig. S3). We observed that two CpGs in the ITG had suggestive significance (Table 1). Probes cg01839373 (P = 1.7 × 10−6) and cg16791508 (P = 7.8 × 10−6) were hypomethylated in SP-born individuals (Fig. 2). Amongst nine suggestively significant CpGs in the hypothalamus, the most significant association was with an open sea probe cg12323699 (P = 8.1 × 10−7) and the highest methylation change was at cg00773142 (13% less methylation in SP-born individuals; P = 3.0 × 10−6), which is at the intron of Phospholipase C Gamma 2 (PLCG2) (Table 1). These nine CpGs were located within either intergenic or intronic regions, but cg12833267 (P = 5.6 × 10−6) is located within the 5’UTR of cAMP-Dependent Protein Kinase Inhibitor Beta (PKIB) (Fig. 2), and cg17733353 (P = 6.0 × 10−6) is in a CpG island of the first exon on Vav Guanine Nucleotide Exchange Factor 2 (VAV2) (Fig. 2). Ten CpGs had a high fold change in the ITG and eight in the hypothalamus (P < 0.05, logFC < −3, logFC > 3). Five of these DMPs were common in both tissues: cg03370588 in a CpG island at the transcription start site of Myosin VA (MYO5A), cg16402757 at the intron of Cullin 2 (CUL2), cg14859874 at the intron of Ubiquitin Associated Protein 2 Like (UBAP2L), and cg06405219 and cg10993517, which are both located at intergenic regions (Table 1).
Table 1. Differentially methylated CpG probes (DMP) associated with season of birth
Chr, chromosome; DMP, differentially methylated probe; Hypo, hypothalamus; ITG, inferior temporal gyrus; LP, long photoperiod season of birth; Methyl, methylation; N/S-Shore, the 2kb sequences upstream or downstream of CpG islands, respectively; Pos, position; SP, short photoperiod season of birth; TSS1500/200, 1500/200 base pairs upstream of the transcription start site; 5'UTR, 5'-untranslated region.
Comparison of DNA methylation between participants born in short photoperiod and long photoperiod season of birth (P < 1E-5 or P < 0.05, logFC < −3, logFC > 3).
Table 2. Differentially methylated regions (DMR) associated with season of birth
Chr, chromosome; DMR, differentially methylated region; FDR, false discovery rate; Hypo, hypothalamus; ITG, inferior temporal gyrus; LP, long photoperiod season of birth; Pos, position; SP, short photoperiod season of birth.
Comparison of DNA methylation between participants born in short photoperiod and long photoperiod season of birth (P < 5E-8).
Fig. 2. Plot of season of birth-associated CpG methylation beta values for the top 9 differentially methylated positions in hypothalamus and the top 2 differentially methylated positions in inferior temporal gyrus (ITG). Scatter plot shows DNA methylation beta values. SP, Short photoperiod season of birth; LP, Long photoperiod season of birth.
Since we found no epigenome-wide significant DMP after correcting for multiple testing, we searched for DMRs using our arbitrary threshold (P < 5 × 10−8) for smoothed estimates (Table 2). There were 4 DMRs in the ITG and 16 DMRs in the hypothalamus showing weak associations. Amongst these DMRs, chr20:57425979–57426931 had the highest number of CpGs (N = 29; P = 1.7 × 10−9) that were annotated to the gene Guanine Nucleotide-Binding Protein G(S) Subunit Alpha Isoforms (GNAS) (Fig. S4). The DMP cg18445760 has also showed regional differential methylation at chr6:31837439–31837445, which is located within the Solute Carrier Family 44 Member 4 (SLC44A4) gene (N = 2; P = 2.6 × 10−13) (Fig. S4).
A total of 75 CpGs in our analysis have been previously reported as season of birth-related blood DNA methylation markers. Reference Lockett, Soto-Ramírez and Ray17 Neither the hypothalamus (Spearman’s Rho = −0.12; P = 0.30) nor the ITG (Spearman’s Rho = 0.15; P = 0.19) results were correlated with blood (Fig. S5). In addition, schizophrenia frontal cortex DMPs Reference Jaffe, Gao and Deep-Soboslay36 were not enriched in our hypothalamus and ITG results. Narcolepsy lateral hypothalamus DMPs Reference Shimada, Miyagawa and Takeshima29 were not enriched in our ITG results, but they were associated with our hypothalamus season of birth DMPs (OR = 1.53; chi2(1) = 102.66; P = 4.0 × 10−24). 6458 DMPs (P < 0.05 and |Δβ| > 0.05) have been previously reported. Amongst these, 6143 CpGs were available in our data set, in which 630 probes had P-value lower than 0.05 in season of birth analysis. In addition, GNAS is one of the top ten DMRs for narcolepsy (Table S5).
Season of birth and clock gene methylation
A total of 699 CpGs in our analysis were annotated to the core clock genes (CLOCK, ARNTL, NPAS2, PER1-3, CRY1-2, RORA, NR1D1, CSNK1D and CSNK1E). Reference Bhatti, Zhang and Song47 After Bonferroni correction for multiple testing (0.05/699 = 7.15 × 10−5), P-values did not provide enough evidence of association. Amongst these, 48 CpGs in the hypothalamus and 24 CpGs in the ITG had a P-value <0.05 (Table S6). The strongest effect size in the hypothalamus was hypomethylation of cg25628433 in SP-born individuals, which is at the intron of the Neuronal PAS Domain Protein 2 (NPAS2) gene (logFC = −0.65; P = 2.4 × 10−3). Nine of the 10 CpGs within the NPAS2 were also hypomethylated (P < 0.05) (Fig. S6). The strongest effect size in the ITG was hypermethylation of cg09161455 in SP-born individuals, which is located within a CpG island at the intron of the Nuclear Receptor Subfamily 1 Group D Member 1 (NR1D1) gene (logFC = 0.57; P = 8.0 × 10−4) (Fig. S6). The second strongest CpG of ITG was cg22387253, which is at the intron of the RAR Related Orphan Receptor A (RORA) gene (logFC = −0.49; P = 1.1 × 10−3). Ten of the 12 CpGs within RORA were also hypomethylated in SP-born individuals (P < 0.05) (Fig. S6).
Season of birth-associated CpGs and later-life chronotype
The UMLCHA cohort has data available for sleep timing (mean age 58.76 (SD = 4.14) years). The average midsleep time was 3:30 am (SD = 26 min). After Bonferroni correction for multiple testing (0.05/29 = 0.0017), P-values did not provide enough evidence of association. Methylation of cg14859874 within the UBAP2L gene in both tissues showed nominal significance to estimate later-life chronotype (Fig. 3). Increased DNA methylation in the hypothalamus was associated with a 30 min earlier chronotype (B = −0.09; SE = 0.04; p = 0.04) and in the ITG, it was associated with a 45 min earlier chronotype (B = −0.13; SE = 0.05; P = 0.02).
Fig. 3. Association between midsleep time (chronotype) with DNA methylation of cg14859874 in (a) hypothalamus and (b) inferior temporal gyrus (ITG). The fit line shows the predicted sleep midpoint (am) in the linear regression after adjusting for age and sex. Scatter plot shows all available sleep midpoint data. The grey area shows 95% CI.
Pathway analysis results
We found no significant enrichment for any biological pathways. The most significant P-value for hypothalamus season of birth-related genes belonged to the biological function of “Specification of animal organ identity” (GO:0010092, P = 4.6 × 10−4). The top results for ITG season of birth-related genes were the biological function of “Proteasome assembly” (GO:0043248, P = 5.1 × 10−5), biological function of “Retina development in camera-type eye” (GO:0060041, P = 1.8 × 10−4), molecular function of “Phosphatidylinositol-3,5-bisphosphate binding” (GO:0080025, P = 6.2 × 10−4) and cellular component of “Proteasome regulatory particle, base subcomplex” (GO:0008540, P = 7.8 × 10−4).
MeQTL analysis results
Methylation β-values of the DMPs that had a P-value lower then 10−5 were interrogated for cis-meQTL separately for each tissue. No SNPs significantly estimated DNA methylation in our study. We searched our target CpGs (P < 10−5 or |Δβ| > 3) in imputed Bonferroni significant meQTLs in fetal brain. We found that methylation of cg18445760, which is located within the SLC44A4 gene, was associated with 39 linked SNPs. The strongest associated variant rs660550 was found to be associated with ITG methylation in our data after adjusting for age and sex (B = −0.018; P = 6.0 × 10−5).
Replication using pyrosequencing
Amongst the remaining bisulphite-converted DNA samples, 24 samples (9 Hypothalamus, 15 ITG) had enough DNA and successfully sequenced using pyrosequencing (Table S7). Methylation array β-values were significantly correlated with pyrosequencing methylation % at the eight target regions (Spearman’s Rho = 0.83; P < 0.0001; N = 24).
Discussion
We investigated associations between photoperiod at birth and human hypothalamus and ITG epigenome-wide DNA methylation patterns. This study is the first of its kind that presents prospective results in the field of early-life seasonal programming via human brain epigenetic modifications. Small sample size may have limited our analyses and results. Nevertheless, suggestive weak associations in this study insinuated that season of birth may generate lasting epigenetic changes, with distinct mechanisms, in different tissues. These results are also in line with the PLICCS hypothesis, since season of birth was weakly associated with hypothalamus DNA methylation, which includes the principal biological clock, and the suggestive significant genes we found may be involved in circadian rhythm pathways. Moreover, reported candidate CpG regions were also enriched in narcolepsy-related DNA methylation, which suggests a relationship between season of birth and narcolepsy in adulthood. Despite limitations, this study is the first to examine the imprinting effects of perinatal light on the human brain and presents unique data that can be used in future meta-analyses and an in-depth evaluation studies of early-life seasonal programming.
Season of birth is associated with traits and behaviours such as height, pubertal timing, educational attainment, biological rhythms and lifetime disease risk. Reference Boland, Shahn, Madigan, Hripcsak and Tatonetti5,Reference Doblhammer and Vaupel9,Reference Natale and Adan12,Reference Day, Forouhi, Ong and Perry48 Day length sunlight exposure is the main seasonal cue, but there are multiple seasonal factors that may be involved in season of birth effect such as temperature, exposure to infectious agents and nutrition. Reference Foster and Roenneberg49–Reference Isen, Rossin-Slater, Walker and Smith52 Seasonal factors may convey their effects via lasting epigenetic modifications, but the exact mechanism of how seasonal cues regulate specific targets is unknown. The strongest candidates are melatonin, thyroid hormone and vitamin-D pathways, all of which are seasonal and have been shown to regulate epigenetic modifier enzymes. Reference Chang, Wu and Lan53–Reference Santi, Spaggiari and Brigante56 Depressive behaviour in mice is associated with postnatal short day length, but when Melatonin receptor 1 was silenced, the mutant animals did not show any postnatal programming in their adulthood depressive behaviour, or midbrain concentration of serotonin and norepinephrine. Reference Green, Jackson, Iwamoto, Tackenberg and McMahon57 In humans, blood epigenome-wide DNA methylation was shown to be postnatally modified by season of birth. Reference Lockett, Soto-Ramírez and Ray17 Specifically, season of birth-associated differentially methylated CpG sites were enriched in development, the cell cycle and apoptosis pathways and were causally related to allergic diseases. Reference Lockett, Soto-Ramírez and Ray17 Neither hypothalamus nor ITG DNA methylation in our study was correlated with season of birth blood DNA methylation patterns. Taken together, these results indicate that early-life seasonal factors can influence epigenetic regulation but there is still little evidence about the exact mechanisms. Furthermore, perinatal programming mechanisms may vary in different tissues.
The circadian biological clock is an endogenous pacemaker that regulates 24-hour rhythms in physiology and behaviour and has the ability to synchronise to the outer rhythmic cues such as light. Reference Hastings, Maywood and Brancaccio58 A negative feedback loop of the molecular clock, located within the neurons of the hypothalamic suprachiasmatic nucleus in mammals, maintains the self-oscillation. Reference Hastings, Maywood and Brancaccio58 Photic input from the eyes entrains the circadian pacemaker and sets the phase of the oscillation. Reference Hastings, Maywood and Brancaccio58 The circadian system is not completely mature at birth; therefore, environmental exposures may programme the later-life function of the biological clock. Reference Brooks and Canal59 The PLICCS hypothesis suggests that the predisposition of the biological rhythm to be programmed by perinatal factors may contribute towards the association between season of birth and later-life health problems. Reference Lewis and Erren10 In line with this, epidemiological studies have shown associations between season of birth and later-life circadian rhythms, and circadian rhythms and health. Narcolepsy is associated with spring season of birth, Reference Dauvilliers, Carlander and Molinari60 insomnia with spring and summer season of birth, Reference Didikoglu, Canal, Pendleton and Payton18 and evening chronotype with summer season of birth. Reference Natale and Adan12 Furthermore, evening-oriented chronotype is associated with psychiatric and metabolic diseases. Reference Didikoglu, Maharani, Payton, Pendleton and Canal11 Similarly, disruption of biological rhythms and sleep is associated with negative health outcomes and mortality. Reference Logan and McClung61,Reference Medic, Wille and Hemels62 Therefore, to examine the perinatal seasonal programming of biological rhythms, we investigated the human hypothalamus.
We found that the NPAS2 gene was the clock gene in the hypothalamus to be most affected by season of birth, with nine CpGs being hypermethylated in LP-born individuals, which points towards a downregulated gene expression in individual born in the summer/spring. The NPAS2 protein is a paralogue of CLOCK, and after dimerisation with BMAL1, it triggers transcription of the PER and CRY clock genes in brain. Reference Dudley, Erbel-Sieler and Estill63 Knock-out of NPAS2 in mice results in a shortened circadian period, altered response to light and sleep disturbances. Reference Dudley, Erbel-Sieler and Estill63 In line with this, LP-reared mice show shortened periods of behavioural and SCN PER1 gene expression rhythms compared to SP-reared animals. Reference Ciarleglio, Axley, Strauss, Gamble and McMahon13 Another factor that influences circadian rhythm period is stability of clock proteins due to degradation. Reference Yoo, Mohawk and Siepka64 A suggestive significant gene in our analysis was CUL2, which targets proteins for degradation by ubiquitination. Reference Petroski and Deshaies65 Cullins are scaffold proteins in the ubiquitin ligases complex and have been shown to work in circadian regulation. Reference Yoo, Mohawk and Siepka64,Reference Szabó, Papin and Cornu66 These findings support the idea that the early-life photoperiod may influence the period of the biological rhythms in adulthood via epigenetic regulations.
Another characteristic of the circadian clock is its ability to entrain to environmental light cycles. However, responses of individuals to the same environmental input vary. Interindividual variations in sensitivity and response to environmental light have been described in humans, where evening light exposure suppressed melatonin expression differently between individuals. Reference Phillips, Vidafar and Burns67 Furthermore, phase differences of circadian genes significantly predicted chronotype. Reference Ferrante, Gellerman and Ay68 In addition, LP-reared mice had invariant rhythm across different seasons compared to SP-reared animals. Reference Ciarleglio, Axley, Strauss, Gamble and McMahon13 Therefore, if early-life light experiences imprint future sensitivity of synchronisation with natural cues, this may explain the association between season of birth and later-life circadian rhythms. Photic entrainment of the circadian clock starts with the retinohypothalamic track conveying light input from the eyes to the SCN through glutamate and PACAP neurotransmission. Reference Jagannath, Butler and Godinho69 Conveyed light input activates Ca2+ influx and cAMP signalling cascades, in turn light-induced response genes, carrying cAMP response elements (CRE) in their promoters, undergo expression and provide the phase shift. Reference Jagannath, Butler and Godinho69 One of the differentially methylated regions in our analysis was the GNAS gene, which was generally hypermethylated in LP-born individuals and is known for its high expression in seasonality-related tissues such as thyroid, pituitary and hypothalamus. GNAS is one of the major regulators of adenylyl cyclases that produce cAMP. Reference Hanoune and Defer70 Through Ca2+/cAMP-dependent circadian entrainment pathways, several protein kinases are involved and another nominal significant gene in our analysis is PKIB, which is a peptide that can inhibits cAMP-dependent protein kinase function. Reference Jagannath, Butler and Godinho69,Reference Dalton and Dewey71 Taken together, lasting epigenetic modifications during postnatal period may alter GNAS and PKIB expression in adulthood and may influence later-life sensitivity to light.
Narcolepsy is a sleep disorder which is characterised by a loss of orexin neurons, likely due to an autoimmune process. Reference Shimada, Miyagawa and Takeshima29,Reference Dauvilliers, Carlander and Molinari60 Genome-wide associations support the involvement of the immune system, and epigenetic analyses indicate differential methylation in myelin production. Reference Shimada, Miyagawa and Takeshima29 Narcolepsy is a season of birth-associated disease. Reference Dauvilliers, Carlander and Molinari60 Season of birth is associated with blood DNA methylation, immune responses and allergies Reference Lockett, Soto-Ramírez and Ray17 ; therefore, it is possible that narcolepsy may also be imprinted via seasonal epigenetic programming. We found that previously described narcolepsy-associated DNA methylation in the lateral hypothalamus Reference Shimada, Miyagawa and Takeshima29 has a significant overlap with our season of birth methylation analysis in the hypothalamus. These findings point towards a causative role of season of birth methylation in narcolepsy. In addition, one of the candidate CpGs in our analyses, cg14859874 within the UBAP2L gene, was associated with both season of birth and later-life chronotype. This may indicate a role of UBAP2L gene methylation by season of birth on later-life circadian behaviour. UBAP2L protein is responsible for the formation of stress granules, which are cytoplasmic dense membraneless structures of mRNA and proteins formed after translation inhibition due to a stress exposure. Reference Cirillo, Cieren and Barbieri72 Stress granules are associated with Alzheimer’s disease pathology and show circadian rhythmic characteristics. Reference Wang, Jiang, Bao, Qin and Xu73 This may also be a link between season of birth and neurodegenerative disorders. Taken together, these findings suggest that early-life seasonal epigenetic programming may have a role in mechanisms linking season of birth and disease.
Early-life light exposure is associated with neurotransmitter levels in adulthood, such as serotonin, norepinephrine and dopamine. Reference Green, Jackson, Iwamoto, Tackenberg and McMahon57,Reference Luykx, Bakker and Lentjes74,Reference Brooks, Waters, Farrington and Canal75 This differential neurotransmitter expression may be due to epigenetic imprinting and may alter health and behaviours in adulthood. In mice, different day length exposure during development resulted in hyper or hypomethylation of genes enriched in synapse formation, neuroendocrine system, axon pathfinding and neurophysiology in the SCN. Reference Azzi, Dallmann and Casserly16 In line with this, a candidate differentially methylated gene in our analyses was SLC44A4, which expresses a choline transporter protein, and was hypermethylated in LP-born individuals. The cholinergic neurotransmission is involved in modulation of wakefulness and REM sleep. Reference Ohno, Hondo and Sakurai76 Even if SLC44A4 has low transcription in brain tissue, it may have a role in brain development and neural tissue. Reference Ma, Xia and Liu77,Reference Inazu78 Season of birth-associated CpG at the SLC44A4 gene was shown to be significantly more methylated in postnatal human brain compared to fetal. Reference Jaffe, Gao and Deep-Soboslay36 The SLC44A4 is also differentially expressed in the placenta in different seasons of birth. Reference Clarkson-Townsend, Kennedy and Everson42 Taken together, season of birth may programme neurotransmitter levels in adulthood.
Some of the candidate genes in the hypothalamus have been previously reported to have roles in brain development. MYO5A is a motor protein that is abundant in neurons and carries synaptic neurotransmitter vesicles, and deficiency of it is associated with developmental brain abnormalities. Reference Landrock, Sullivan and Martini-Stoica79,Reference Wöllert, Patel and Lee80 The Ventral Anterior Homeobox 1 gene is responsible for the development of the anterior ventral forebrain and visual system. Reference Barbieri, Lupo and Bulfone81,Reference Hallonet, Hollemann and Wehr82 The Homeobox A3 gene has a role in the development of the thyroid gland. Reference Manley and Capecchi83 These studies suggest a role of season of birth epigenetic modulation in brain development.
Season of birth has previously been associated with grey matter volume of the left superior temporal gyrus in adult human males. Reference Pantazatos84 The temporal fusiform cortex and inferior temporal gyrus were also shown as suggestively significant with season of birth, with a summer peak. Reference Didikoglu, Canal, Pendleton and Payton18 A reduction in the grey matter volume of the temporal gyri has been linked to schizophrenia and narcolepsy, Reference Kaufmann, Schuld, Pollmächer and Auer85,Reference Kuroki86 both of which are associated with season of birth. Reference Castrogiovanni, Iapichino, Pacchierotti and Pieraccini4,Reference Dauvilliers, Carlander and Molinari60 Therefore, it is possible that season of birth modifies the brain structure in these regions and in turn influences later-life health. We hypothesised that the epigenome of the ITG may be influenced by photoperiodic history and associated with later-life health. We found that neither schizophrenia nor narcolepsy-associated DNA methylation was correlated with ITG season of birth methylation levels.
One of the nominal significances of biological pathways in the ITG was ‘Retina development in camera-type eye’. The ITG has a role in visual processing of faces, colours and shape. Reference Lafer-Sousa and Conway87 This may indicate that season of birth epigenetic programming may influence later-life role of the ITG. In addition, when we examined the probes that had the highest fold change, we observed an overlap between ITG and hypothalamus. We found that the CpGs at CUL2, MYO5A and UBAP2L genes had the highest methylation differences in both ITG and hypothalamus, which indicates a possible common mechanism for these regions.
There are some limitations in our study. First, the small sample size limited the statistical power. This study has over 80% power to detect a mean difference of 10% in only 33% of tested sites using a 10−5 P-value threshold. Reference Mansell, Gorrie-Stone and Bao32 Season of birth effect has a small effect size which may make it difficult to detect in a small sample. Reference Foster and Roenneberg49,Reference Natale, Adan and Fabbri88 Even if we adjusted our analyses for age and sex, other sociocultural, genetic, environmental and latitudinal factors may confound the analyses. Reference Lewis, Hellmich and Fritschi7,Reference Didikoglu, Maharani, Canal, Pendleton and Payton43,Reference Foster and Roenneberg49,Reference Natale, Adan and Fabbri88 We categorised the photoperiod of birth as LP and SP, but using real seasonal day length would provide better insight to postnatal light exposure. Our hypothalamus DNA methylation is correlated with hypothalamus gene expression and DNA methylation in the literature, which support the validity of our tissue blocks. However, the human brain tissue used in the study was slow-frozen, which made it difficult to identify hypothalamus subregions. The hypothalamus comprises many nuclei with distinct functions, cellular and molecular compositions. Therefore, to understand the real association between circadian rhythms and DNA methylation, SCN-specific methylation should be investigated. Furthermore, cellular heterogeneity is one of the major limitations when analysing whole tissue. Nevertheless, we show that neuron and non-neuron proportions were similar in season of birth groups. Finally, DNA methylation may be daily or seasonally rhythmic. Reference Lim, Klein and Yu39 However, none of the reported suggestive significant genes or CpG probe showed circadian or seasonal characteristics in the diurnal transcriptome atlas of baboon SCN Reference Mure, Le and Benegiamo38 and human prefrontal cortex. Reference Lim, Klein and Yu39
In summary, perinatal light exposure may predispose physical and mental health in adulthood. Despite the limitations of the present study, our results suggest that season of birth may programme later-life health and behaviour via brain DNA methylation. In addition, different mechanisms appear to underlie season of birth effects in different tissues and health disorders. Importantly, the photoperiod around birth may influence the development of the circadian rhythm system, which is essential for health. Further studies are required to fully understand the mechanisms behind early-life programming, as a key first step to preventing, diagnosing and treating future health problems in predisposed individuals.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S2040174421000453
Acknowledgements
Altug Didikoglu was supported by a grant from the Republic of Turkey Ministry of National Education. Nisha Nair was supported by Versus Arthritis (previously Arthritis Research UK; grant ref 21754), and we thank the NIHR Manchester Biomedical Research Centre for their support. Tissue samples were supplied by The Manchester Brain Bank, which is part of the Brains for Dementia Research programme, jointly funded by Alzheimer’s Research UK and Alzheimer’s Society. We thank Mihoko Shimada and Taku Miyagawa for sharing results about the differential methylated probes between lateral hypothalamus and temporal cortex.
Conflicts of interest
The authors have no conflict of interest.
Author contributions
AD, MMC and NN designed the study. AP and NP collected behavioural and genotype data of the cohort. ACR and FR collected pathological data and dissected the required tissue blocks. NN and AD scanned the methylation arrays and performed the statistical analysis. AD wrote the manuscript. NN, AP, MMC and NP supervised the project. All authors contributed to the writing and have approved the final manuscript.
Open access
