A comprehensive regional analysis of genome-wide expression profiles for major depressive disorder

We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value <1x10^(-5) ) for MDD. These significant regions have genes mapped to within 400kb of them. The genes mapped for height have been reported to be associated with height in humans, whiles those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.

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Genome-wide DNA methylation in 1-year-old infants of mothers with major depressive disorder

Development and Psychopathology ◽

10.1017/s0954579416000912 ◽

2016 ◽

Vol 28 (4pt2) ◽

pp. 1413-1419 ◽

Cited By ~ 5

Author(s):

Dante Cicchetti ◽

Susan Hetzel ◽

Fred A. Rogosch ◽

Elizabeth D. Handley ◽

Sheree L. Toth

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Low Income ◽

Neuronal Development ◽

Colonic Neoplasms ◽

Major Depressive ◽

Process Networks ◽

Genome Wide ◽

A Genome ◽

Depressed Mothers

AbstractA genome-wide methylation study was conducted among a sample of 114 infants (M age = 13.2 months, SD = 1.08) of low-income urban women with (n = 73) and without (n = 41) major depressive disorder. The Illumina HumanMethylation450 BeadChip array with a GenomeStudio Methylation Module and Illumina Custom model were used to conduct differential methylation analyses. Using the 5.0 × 10–7p value, 2,119 loci were found to be significantly different between infants of depressed and nondepressed mothers. Infants of depressed mothers had greater methylation at low methylation sites (0%–29%) compared to infants of nondepressed mothers. At high levels of methylation (70%–100%), the infants of depressed mothers were predominantly hypomethylated. The mean difference in methylation between the infants of depressed and infants of nondepressed mothers was 5.23%. Disease by biomarker analyses were also conducted using GeneGo MetaCore Software. The results indicated significant cancer-related differences in biomarker networks such as prostatic neoplasms, ovarian and breast neoplasms, and colonic neoplasms. The results of a process networks analysis indicated significant differences in process networks associated with neuronal development and central nervous system functioning, as well as cardiac development between infants of depressed and nondepressed mothers. These findings indicate that early in development, infants of mothers with major depressive disorder evince epigenetic differences relative to infants of well mothers that suggest risk for later adverse health outcomes.

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